AI is Changing How Search Engines Rank Results

A “zero-click search” is when a user queries a search engine but doesn’t click on any of the organic search results, instead obtaining the information from elsewhere on the search engine results page (SERP). These other sources might include snippets—short responses displayed above organic results—or other SERP features that let users view maps, book reservations, or purchase items without ever leaving the page.

Google recently trialed its new search generative experience (SGE), which provides an AI-assisted overview of query responses. These new SERP summaries rank AI material over other results, followed by sponsored results, Google’s own suggestions, and organic content. While SGE is still in an experimental stage, it’s being tested in more than 120 countries and is being billed—for better or for worse—as the future of search.

Actionable Steps

Businesses that rely on search results to reach their audiences need to understand the impact of SGE and adjust their methods accordingly. To remain visible on Google’s SERP:

1. Develop high-quality content more likely to be included in summaries.
2. Use SEO to improve perception of your content as authoritative and relevant.
3. Ensure that content has a steady flow and a human-friendly tone while also being credible, engaging, and trustworthy to earn readers’ confidence.

LLMs are Making AI More Conversational and Useful

Large Language Models (LLMs) like GPT-4 have transformed conversational AI’s ability to comprehend context, generate coherent replies, and emulate human speech patterns, leading to more natural and engaging human interactions with chatbots. Marketing specialists can use LLMs to create chatbots and virtual assistants capable of conversations that closely mimic human communication, increasing user engagement and satisfaction.

Because LLMs can handle complicated queries, provide tailored suggestions, and respond to user demands quickly, they result in a more seamless experience. Chatbots driven by LLMs can also help businesses provide round-the-clock customer care, guaranteeing that consumers receive rapid replies and increasing overall satisfaction. Gartner predicts that the usage of conversational AI solutions will increase by 24 percent by 2024, with a significant focus on customer-facing solutions, including 24/7 support chatbots.

Actionable Steps

Experimenting with the creation and training of chatbots to improve client interactions can help you stay ahead of the curve. Remember, human monitoring is required to ensure they function successfully and appropriately. Here are some steps to get started:

1. Find the right AI solution for your particular need; consider advanced large language model tools like React or Daitaku.
2. To enhance user interactions, update chatbot scripts regularly to mirror real-world conversation patterns, react to changing user demands, and include new information.
3. Track and analyze client interactions with chatbots to uncover typical questions, pain spots, and areas for improvement, then use this information to continuously improve AI responses.

Augmented Reality is Transforming the Customer Experience

Retailers are increasingly using augmented reality (AR) to change the way customers interact with their products, considerably improving the overall customer experience. Using AR, customers can try on outfits, accessories, and cosmetics virtually, resulting in an immersive and entertaining purchase experience. It also allows buyers to envision products in different surroundings by superimposing digital information on the actual world, allowing for more informed purchasing decisions for items like furniture, home décor, and clothes.

According to Threekit, 61 percent of customers choose stores that provide a variety of AR experiences. AR adoption benefits both consumers and sellers by reducing return rates and personalizing the shopping experience to individual preferences, driving engagement. Additionally, AR can lead to cost savings for retailers by attracting tech-savvy consumers and creating memorable interactions, thereby reducing marketing costs.

Actionable Steps

AR technology can be implemented in a variety of ways to help improve your product offerings. To get started:

1. Determine whether you want to employ AR features that allow customers to visually interact with your products via mobile apps or in-store experiences.
2. Explore virtual try-on solutions, interactive product visualizations, and QR code experiences to identify the consumer engagements that will be most compelling for your particular customer base.
3. Once you’ve implemented AR, create marketing initiatives that promote the features and teach consumers about the tailored purchasing experience they can provide.

CGI is Providing New Storytelling Opportunities

Using computer generated imagery (CGI) to create visual content using computer graphics and 3D modeling techniques is opening up a wide range of marketing opportunities by enabling firms to promote products and tell stories in appealing ways. CGI lets marketers create hyperrealistic product renderings with precise representations of everything from smartphones to luxury watches to provide interactive virtual experiences for customers such as virtual try-ons for fashion products or room representations for furniture, improving the online buying experience.

In addition, CGI feeds creative storytelling pathways, allowing marketers to create visually spectacular storylines through animated shorts and immersive 360-degree experiences to deepen brand communication. CGI content’s dynamic visuals and interactive elements catch public attention and enhance brand memorability, leaving a lasting impression on consumers. According to Threekit, consumer preferences align with the adoption of CGI experiences, with 61 percent expressing a preference for retailers providing AR and VR experiences.

Actionable Steps

Investing in CGI technology and skills can help your marketing initiatives succeed, but the bar to entry can be high. Collaborating with skilled CGI artists or firms is the quickest way. Here are some other steps to help you get started:

1. Create immersive campaigns by combining CGI into your marketing materials, creating visually appealing campaigns that captivate attention. Remember, CGI is not just about aesthetics; it’s about creating memorable moments that have a lasting impact for customers.
2. Investigate the possibilities of AR and VR experiences to engage tech-savvy customers and improve brand connection.
3. Promote your CGI material across multiple platforms, such as social media, websites, and advertising channels, to highlight your brand’s originality and creativity.

Automation is Helping Emails Reach New Audiences

AI-powered email automation can help marketers segment lists, customize content, and automate triggers based on user behavior, increasing the efficacy of email marketing efforts. Marketers can use powerful AI authoring tools to create dynamic email sequences that adapt to individual preferences, optimizing send timings and frequency to increase engagement while reducing unsubscribes.

Popular systems provide extensive functionality for personalized communication. As organizations prioritize individualized communication, AI-powered email marketing is projected to gain traction, highlighting its influence on client connections. AI’s predictive analytics abilities let marketers anticipate customer requirements and preferences to offer relevant information at an appropriate time.

Actionable Steps

Start by assessing your existing email workflow to find pain spots and potential for automation. Choose a reputable AI-powered email platform such as MailChimp, Klaviyo, or Drip, and make sure it corresponds with your company objectives. Here’s how to get started:

1. Facilitate targeted communication by using AI to segment email lists based on demographics, activity, and preferences.
2. Set up automated triggers such as welcome emails, abandoned cart reminders, and re-engagement emails and customize the text for each.
3. Use A/B testing to experiment with different aspects and fine-tune your strategy while employing AI analytics to track important metrics and iterate for ongoing improvement.

AI Can Retarget Ads Based on User Behavior

As AI evolves, advertisers are prioritizing the creation of highly relevant and personalized advertising material to capture viewers’ attention. AI-driven campaign evaluation looks at data from past efforts to help marketers produce personalized content that connects with their target demographics and is tuned to consumer interactions.

AI can retarget consumers with suitable offers based on their past interactions, improving ad placement and boosting conversion. AI-driven bidding algorithms change bids in real-time to optimize conversions while staying under budget. Establishing a feedback loop enables ongoing changes in ad content and targeting settings depending on performance indicators.

Actionable Steps

To optimize AI-driven ad targeting, look beyond campaign KPIs and dig deeper into individual data points such as conversion rates and audience demographics as follows:

1. Use AI analytics to customize ads and segment your audience and target messaging to particular consumer categories.
2. Actively interact with user input to develop a better grasp of preferences and attitudes, then refine ad targeting techniques accordingly.
3. Investigate AI content creation tools and ad graders, such as WordStream’s Google Ads Performance grader, for additional optimization and alignment with campaign goals and marketing strategy.

AI is Making Predictive Analytics More Accurate

Predictive analytics is essential for fine-tuning marketing tactics, allocating resources, and accurately forecasting market movements. Predictive models can provide valuable insights for campaign optimization by examining historical data to help segment audiences, target content production, and select the right communications channels. In addition, predictive analytics helps with resource allocation by guiding budget distribution, optimizing the workforce, and controlling inventories based on projected demand patterns.

Predictive models estimate market trends to allow for more proactive decisions in sales, demand forecasting, and price strategy. Enhanced by AI, predictive skills are constantly evolving, resulting in such breakthroughs as tailored product suggestions, churn prediction, and customer lifetime value assessment. Statistical research emphasizes the importance of predictive analytics, indicating that organizations adept in its usage are nearly three times more likely to succeed in revenue development, whereas tailored methods are driven by predictive models that can create substantial revenue increases of up to 15 percent.

Actionable Steps

To effectively use predictive analytics:

1. Assess projections on a regular basis and adjust strategies accordingly to remain attentive to changing trends.
2. Maintain extensive historical data for accurate predictive analysis and informed decision-making.
3. To improve predictive skills and provide actionable insights, explore a variety of predictive analytics tools, including Altair AI Studio, H2O Driverless AI, and IBM Watson Studio.

Real-World Use Case Examples of AI Marketing Trends

AI is transforming the way marketers work in numerous ways, and corporations like Mastercard, Zara, Sephora, and ClickUp are using it to make the best of their marketing strategies and deliver great results.

Mastercard

Mastercard uses social media data analytics to improve business strategies. Recently, the company tested its new AI-powered social listening tool, Digital Engine, to analyze billions of online conversations to identify emerging microtrends and popular travel and entertainment topics. As a result, the company saw a 37 percent increase in click-through rates (CTR), a 43 percent increase in engagement, and a 29 percent reduction in cost per engagement. Mastercard uses social listening intelligence not only for insights but also to shape ideation, product development, brand engagement, reputation tracing, and customer behavior and preferences.

Zara

Zara produces over 450 million items per year. The company uses artificial intelligence and data analytics to make merchandising decisions, personalize customer experiences, and manage its supply chain. With the help of AI, Zara is able to identify appropriate styles, colors, sizes, and types of fittings that their customers prefer by analyzing customer data preferences. In collaboration with Jetlore, an AI consumer behavior analysis and predictive analysis platform, Zara is able to personalize customer experience based on shopping data and make more educated business decisions that let it produce more styles, colors, and sizes that customers prefer.

Sephora

French makeup brand Sephora has been using conversational AI chatbot technology to provide a more personalized and informative customer experience. Based on data collected from the chatbot, Sephora realized that customers are overwhelmed by the number of products it has to offer, making it difficult to find specific items they need. As a result, Sephora launched an interactive quiz to help identify which products to show customers first. Sephora’s chatbot can also provide lipstick shade personalization—an AI color match assistant incorporated into the chatbot gives product suggestions based on customer input.

ClickUp

Needing to optimize 500 blogs for SEO purposes and create more SEO-based content for better organic search traffic, ClickUp turned to SurferSEO’s content editor and used its Content Intelligence features to provide various topics of relevance to its target audience. The company was able to develop a content calendar to produce these blogs and improve rankings on the search engine results page. With the help of this Content Intelligence, ClickUp optimized 130 articles and published 150 more, boosting organic traffic by 85 percent.

The Impact of AI Marketing on Jobs

AI has drastically revolutionized the job market in the marketing field, changing how professionals approach their jobs by increasing efficiency, giving data-driven insights, and encouraging strategic thinking and creativity. By automating tedious processes like data input, lead generation, and social media posting, AI lets marketing specialists focus more on creative strategy. AI-powered technologies also create individualized content, optimize headlines, and identify the best distribution channels, allowing for more scalable content creation.

AI’s predictive analytics and better audience segmentation allow marketing specialists to anticipate customer behavior, optimize campaigns, and provide tailored experiences that increase engagement and conversions. Instead of replacing marketing specialists, AI supplements their experiences by recommending ideal methods and fostering creativity. Using AI technologies like chatbots and recommendation engines ultimately allows marketers to achieve more, innovate, and drive strategic outcomes.

Frequently Asked Questions (FAQs)

How is generative AI changing content creation in marketing?

Content creation production in marketing has sped up the entire process by using different AI content creation tools such as content writing, media creation, and music creation. It allows content creators to elevate their creativity with the help of these AI tools. This doesn’t mean that these AI content creation tools will replace them—it will just help bring their ideas to life.

Why is ethical AI important in marketing?

Ethical AI in marketing supports the responsible and transparent use of artificial intelligence technologies, which is critical for retaining consumer trust and adhering to legislation. Consumers want brands to handle their data in a responsible and transparent manner, and ethical practices in AI assist in creating and maintaining confidence. Brands that value ethical AI not only build great customer interactions but also ensure that their marketing methods comply with privacy rules such as GDPR and CCPA.

What impact will AI have on marketing jobs?

AI has had a positive impact on marketing specialists, with scores of AI tools designed specifically for their field. It can help automate and optimize their jobs, allowing them to focus more on the human side of things such as negotiation, strategizing, and editing certain content to fit the company’s brand voice. AI still needs humans to deliver the best results.

Bottom Line: The Future of AI in Marketing

The future of marketing in the age of AI promises great transformation, with AI-driven personalization improving customer engagement by facilitating tailored experiences through precise customer segmentation, predictive analytics, and dynamic content optimization. AI delivers real-time analysis and decision-making to help marketing specialists manage resources more effectively and respond to market developments more dynamically. As the integration of AI further empowers marketing specialists, businesses worldwide will increasingly use AI tools that accelerate efficiency and effectiveness.

Read our guide to the strategies, tools, and best practices for using AI in content marketing to learn more about how organizations can deploy this powerful new technology to automate work and better engage customers.

The post 7 Top AI Marketing Trends (2024): What’s Hot and Worth Watching appeared first on eWEEK.

This guide explores some of the most common AI and privacy concerns that businesses face. Additionally, it identifies potential solutions and best practices organizations can pursue to achieve better outcomes for their customers, their reputation, and their bottom line.

Major Issues with AI and Privacy

Given that the role of artificial intelligence has grown so rapidly, it’s not surprising that issues like unauthorized incorporation of user data, unclear data policies, and limited regulatory safeguards have created significant issues with AI and privacy.

Unauthorized Incorporation of User Data

When users of AI models input their own data in the form of queries, there’s the possibility that this data will become part of the model’s future training dataset. When this happens, this data can show up as outputs for other users’ queries, which is a particularly big issue if users have input sensitive data into the system.

In a now-famous example, three different Samsung employees leaked sensitive company information to ChatGPT that could now possibly be part of ChatGPT’s training data. Many vendors, including OpenAI, are cracking down on how user inputs are incorporated into future training. But there’s still no guarantee that sensitive data will remain secure and outside of future training sets.

Unregulated Usage of Biometric Data

A growing number of personal devices use facial recognition, fingerprints, voice recognition, and other biometric data security instead of more traditional forms of identity verification. Public surveillance devices are also beginning to use AI to scan for biometric data so individuals can be identified quickly.

While these new biometric security tools are incredibly convenient, there’s limited regulation focused on how AI companies can use this data once it’s collected. In many cases, individuals don’t even know that their biometric data has been collected, much less that it is being stored and used for other purposes.

Covert Metadata Collection Practices

When a user interacts with an ad, a TikTok or other social media video, or pretty much any web property, metadata from that interaction—as well as the person’s search history and interests—can be stored for more precise content targeting in the future.

This method of metadata collection has been going on for years, but with the help of AI, more of that data can be collected and interpreted at scale, making it possible for tech companies to further target their messages at users without their knowledge of how it works. While most user sites have policies that mention these data collection practices and/or require users to opt in, it’s mentioned only briefly and in the midst of other policy text, so most users don’t realize what they’ve agreed to. This veiled metadata collection agreement subjects users and everything on their mobile devices to scrutiny.

Limited Built-In Security Features for AI Models

While some AI vendors may choose to build baseline cybersecurity features and protections into their models, many AI models do not have native cybersecurity safeguards in place. Even the AI technologies that do have basic safeguards rarely come with comprehensive cybersecurity protections. This is because taking the time to create a safer and more secure model can cost AI developers significantly, both in time to market and overall development budget.

Whatever the reason, AI developers’ limited focus on security and data protection makes it much easier for unauthorized users and bad-faith actors to access and use other users’ data, including personally identifiable information (PII).

Extended and Unclear Data Storage Policies

Few AI vendors are transparent about how long, where, and why they store user data. The vendors who are often store data for lengthy periods of time, or use it in ways that clearly do not prioritize privacy.

For example, OpenAI’s privacy policy says it can “provide Personal Information to vendors and service providers, including providers of hosting services, customer service vendors, cloud services, email communication software, web analytics services, and other information technology providers, among others. Pursuant to our instructions, these parties will access, process, or store Personal Information only in the course of performing their duties to us.”

In this case, several types of companies can gain access to your ChatGPT data for various reasons as determined by OpenAI. It’s especially concerning that “among others” is a category of vendors that can collect and store your data, as there’s no information about what these vendors do or how they might choose to use or store your data.

OpenAI’s policy provides additional information about what data is typically stored and what your privacy rights are as a consumer. You can access your data and review some information about how it’s processed, delete your data from OpenAI records, restrict or withdraw information processing consent, and/or submit a formal complaint to OpenAI or local data protection authorities.

This more comprehensive approach to data privacy is a step in the right direction, but the policy still contains certain opacities and concerning elements, especially for Free and Plus plan users who have limited control over or visibility into how their data is used.

Little Regard for Copyright and IP Laws

AI models pull training data from all corners of the web. Unfortunately, many AI vendors either don’t realize or don’t care when they use someone else’s copyrighted artwork, content, or other intellectual property without their consent.

Major legal battles have focused on AI image generation vendors like Stability AI, Midjourney, DeviantArt, and Runway AI. It is alleged that several of these tools scraped artists’ copyrighted images from the internet without permission. Some of the vendors defended their action by citing a lack of laws that prevent them from following this process for AI training.

The problems of using unauthorized copyrighted products and IP grow much worse as AI models are trained, retrained, and fine-tuned with this data over time. Many of today’s AI models are so complex that even their builders can’t confidently say what data is being used, where it came from, and who has access to it.

Limited Regulatory Safeguards

Some countries and regulatory bodies are working on AI regulations and safe use policies, but no overarching standards are officially in place to hold AI vendors accountable for how they build and use artificial intelligence tools. The proposed regulation closest to becoming law is the EU AI Act, expected to be published in the Official Journal of the European Union in summer of 2024. Some aspects of the law will take as long as three years to become enforceable.

With such limited regulation, a number of AI vendors have come under fire for IP violations and opaque training and data collection processes, but little has come from these allegations. In most cases, AI vendors decide their own data storage, cybersecurity, and user rules without interference.

How Data Collection Creates AI Privacy Issues

Unfortunately, the total number and variety of ways that data is collected all but ensures that this data will find its way into some irresponsible uses. From Web scraping to biometric technology to IoT sensors, modern life is essentially lived in service of data collection efforts.

Web Scraping Harvests a Wide Net

Because web scraping and crawling require no special permissions and enable vendors to collect massive amounts of varied data, AI tools often rely on these practices to quickly build training datasets at scale. Content is scraped from publicly available sources on the internet, including third-party websites, wikis, digital libraries, and more. In recent years, user metadata is also increasingly pulled from marketing and advertising datasets and websites with data about targeted audiences and what they engage with most.

User Queries in AI Models Retain Data

When a user inputs a question or other data into an AI model, most AI models store that data for at least a few days. While that data may never be used for anything else, many artificial intelligence tools collect that data and hold onto it for future training purposes.

Biometric Technology Can Be Intrusive

Surveillance equipment—including security cameras, facial and fingerprint scanners, and microphones—can all be used to collect biometric data and identify humans without their knowledge or consent. State by state, rules are getting stricter in the U.S. regarding how transparent companies need to be when using this kind of technology. However, for the most part, they can collect this data, store it, and use it without asking customers for permission.

IoT Sensors and Devices Are Always On

Internet of Things (IoT) sensors and edge computing systems collect massive amounts of moment-by-moment data and process that data nearby to complete larger and quicker computational tasks. AI software often takes advantage of an IoT system’s detailed database and collects its relevant data through methods like data learning, data ingestion, secure IoT protocols and gateways, and APIs.

APIs Interface With Many Applications

APIs give users an interface with different kinds of business software so they can easily collect and integrate different kinds of data for AI analysis and training. With the right API and setup, users can collect data from CRMs, databases, data warehouses, and both cloud-based and on-premises systems. Given how few users pay attention to the data storage and use policies their software platforms follow, it’s likely many users have had their data collected and applied to different AI use cases without their knowledge.

Public Records Are Easy Accessed

Whether records are digitized or not, public records are often collected and incorporated into AI training sets. Information about public companies, current and historical events, criminal and immigration records, and other public information can be collected with no prior authorization required.

User Surveys Drives Personalization

Though this data collection method is more old-fashioned, using surveys and questionnaires are still a tried-and-true way that AI vendors collect data from their users. Users may answer questions about what content they’re most interested in, what they need help with, how their most recent experience with a product or service was, or any other question that gives the AI a better idea about how to personalize interactions.

Emerging Trends in AI and Privacy

Because the AI landscape is evolving so rapidly, the emerging trends shaping AI and privacy issues are also changing at a remarkable pace. Among the leading trends are major advances in AI technology itself, the rise of regulations, and the role of public opinion on AI’s growth.

Advancements in AI Technologies

AI technologies have exploded in terms of technology sophistication, use cases, and public interest and knowledge. This growth has happened with more traditional AI and machine learning technologies but also with generative AI.

Generative AI’s large language models (LLMs) and other massive-scale AI technologies are trained on incredibly large datasets, including internet data and some more private or proprietary datasets. While the data collection and training methodologies have improved, AI vendors and their models often are not transparent in their training or the algorithmic processes they use to generate answers.

To address this issue, many generative AI companies in particular have updated their privacy policies and their data collection and storage standards. Others, such as Anthropic and Google, have worked to develop and release clear research that illustrates how they are working to incorporate more explainable AI practices into their AI models, which improves transparency and ethical data usage across the board.

Impact of AI on Privacy Laws and Regulations

Most privacy laws and regulations do not yet directly address AI and how it can be used or how data can be used in AI models. As a result, AI companies have had a lot of freedom to do what they want. This has led to ethical dilemmas like stolen IP, deepfakes, sensitive data exposed in breaches or training datasets, and AI models that seem to act on hidden biases or malicious intent.

More regulatory bodies—both governmental and industry-specific—are recognizing the threat AI poses and developing privacy laws and regulations that directly address AI issues. Expect more regional, industry-specific, and company-specific regulations to come into play in the coming months and years, with many of them following the EU AI Act as a blueprint for how to protect consumer privacy.

Public Perception and Awareness of AI Privacy Issues

Since ChatGPT was released, the general public has developed a basic knowledge of and interest in AI technologies. Despite the excitement, general public perception of AI technology is fearful—especially as it relates to AI privacy.

Many consumers do not trust the motivations of big AI and tech companies and worry that their personal data and privacy will be compromised by the technology. Frequent mergers, acquisitions, and partnerships in this space can lead to emerging monopolies, and the fear of the power these organizations have.

According to a survey completed by the International Association of Privacy Professionals in 2023, 57 percent of consumers fear that AI is a significant threat to their privacy, while 27 percent felt neutral about AI and privacy issues. Only 12 percent disagreed that AI will significantly harm their personal privacy.

Real-World Examples of AI and Privacy Issues

While there have been several significant and highly publicized security breaches with AI technology and its respective data, many vendors and industries are taking important strides in the direction of better data protections. We cover both failures and success in the following examples.

High-Profile Privacy Issues Involving AI

Here are some of the most major breaches and privacy violations that directly involved AI technology over the past several years:

• Microsoft: Its recent announcement of the Recall feature, which allows business leaders to collect, save, and review user-activity screenshots from their devices, received significant pushback for its lack of privacy design elements, as well as for the company’s recent problems with security breaches. Microsoft will now let users more easily opt in or out of the process, and plans to improve data protection with just-in-time decryption and encrypted search index databases.
• OpenAI: OpenAI experienced its first major outage in March 2023 as a result of a bug that exposed certain users’ chat history data to other users, and even exposed payment and other personal information to unauthorized users for a period of time.
• Google: An ex-Google employee stole AI trade secrets and data to share with the People’s Republic of China. While this does not necessarily impact personal data privacy, the implications of AI and tech companies’ employees being able to get this kind of access are concerning.

Successful Implementations of AI with Strong Privacy Protections

Many AI companies are innovating to create privacy-by-design AI technologies that benefit both businesses and consumers, including the following:

• Anthropic: Especially with its latest Claude 3 model, Anthropic has continued to grow its constitutional AI approach, which enhances model safety and transparency. The company also follows a responsible scaling policy to regularly test and share with the public how its models are performing against biological, cyber, and other important ethicality metrics.
• MOSTLY AI: This is one of several AI vendors that has developed comprehensive technology for synthetic data generation, which protects original data from unnecessary use and exposure. The technology works especially well for responsible AI and ML development, data sharing, and testing and quality assurance.
• Glean: One of the most popular AI enterprise search solutions on the market today, Glean was designed with security and privacy at its core. Its features include zero trust security and a trust layer, user authentication, the principle of least privilege, GDPR compliance, and data encryption at rest and in transit.
• Hippocratic AI: This generative AI product, specifically designed for healthcare services, complies with HIPAA and has been received extensively by nurses, physicians, health systems, and payor partners to ensure data privacy is protected and patient data is used ethically to deliver better care.
• Simplifai: A solution for AI-supported insurance claims and document processing, Simplifai explicitly follows a privacy-by-design approach to protect its customers’ sensitive financial data. Its privacy practices include data masking, limited storage times and regular data deletion; built-in platform, network, and data security components and technology; customer-driven data deletion; data encryption; and the use of regional data centers that comply with regional expectations.

Best Practices for Managing AI and Privacy Issues

While AI presents an array of challenging privacy issues, companies can surmount these concerns by using best practices like focusing on data governance, establishing appropriate use policies and educating all stakeholders.

Invest in Data Governance and Security Tools

Some of the best solutions for protecting AI tools and the rest of your attack surface include extended detection and response (XDR), data loss prevention, and threat intelligence and monitoring software. A number of data-governance-specific tools also exist to help you protect data and ensure all data use remains in compliance with relevant regulations.

Establish an Appropriate Use Policy for AI

Internal business users should know what data they can use and how they should use it when engaging with AI tools. This is particularly important for organizations that work with sensitive customer data, like protected health information (PHI) and payment information.

Read the Fine Print

AI vendors typically offer some kind of documentation or policy that covers how their products work and the basics of how they were trained. Read this documentation carefully to identify any red flags, and if there’s something you’re not sure about or that’s unclear in their policy docs, reach out to a representative for clarification.

Use Only Non-Sensitive Data

As a general rule, do not input your business’s or customers’ most sensitive data in any AI tool, even if it’s a custom-built or fine-tuned solution that feels private. If there’s a particular use case you want to pursue that involves sensitive data, research if there’s a way to safely complete the operation with digital twins, data anonymization, or synthetic data.

Educate Stakeholders and Users on Privacy

Your organization’s stakeholders and employees should receive both general training and role-specific training for how, when, and why they can use AI technologies in their daily work. Training should be an ongoing initiative that focuses on refreshing general knowledge and incorporating information about emerging technologies and best practices.

Enhance Built-In Security Features

When developing and releasing AI models for more general use, you must put in the effort to protect user data at all stages of model lifecycle development and optimization. To improve your model’s security features, focus heavily on data, increasing practices like data masking, data anonymization, and synthetic data usage; also consider investing in more comprehensive and modern cybersecurity tool sets for protection, such as extended detection and response (XDR) software platforms.

Proactively Implement Stricter Regulatory Measures

The EU AI Act and similar overarching regulations are on the horizon, but even before these laws go into effect, AI developers and business leaders should regulate how AI models and data are used. Set and enforce clear data usage policies, provide avenues for users to share feedback and concerns, and consider how AI and its needed training data can be used without compromising industry-specific regulations or consumer expectations.

Improve Transparency in Data Usage

Increasing data usage transparency—which includes being more transparent about data sources, collection methods, and storage methods—is a good business practice all-around. It gives customers greater confidence when using your tools, it provides the necessary blueprints and information AI vendors need to pass a data or compliance audit, and it helps AI developers and vendors to create a clearer picture of what they’re doing with AI and the roadmap they plan to follow in the future.

Reduce Data Storage Periods

The longer data is stored in a third-party repository or AI model (especially one with limited security protections), the more likely that data will fall victim to a breach or bad actor. The simple act of reducing data storage periods to only the exact amount of time that’s necessary for training and quality assurance will help to protect data against unauthorized access and give consumers greater peace of mind when they discover this reduced data storage policy is in place.

Ensure Compliance with Copyright and IP Laws

While current regulations for how AI can incorporate IP and copyrighted assets are murky at best, AI vendors will improve their reputation (and be better prepared for impending regulations) if they vet their sources from the outset. Similarly, business users of AI tools should be diligent in reviewing the documentation AI vendors provide about how their data is sourced; if you have questions or concerns about IP usage, you should contact that vendor immediately or even stop using that tool.

Bottom Line: Addressing AI and Privacy Issues Is Essential

AI tools present businesses and the everyday consumer with all kinds of new conveniences, ranging from task automation and guided Q&A to product design and programming. While these tools can simplify our lives, they also run the risk of violating individual privacy in ways that can damage vendor reputation and consumer trust, cybersecurity, and regulatory compliance.

It takes extra effort to use AI in a responsible way that protects user privacy, yet it’s essential when you consider how privacy violations can impact a company’s public image. Especially as this technology matures and becomes more pervasive in our daily lives, it’s essential to follow AI laws as they’re passed and develop more specific AI use best practices that align with your organization’s culture and customers’ privacy expectations.

For additional tips related to cybersecurity, risk management, and ethical AI use when it comes to generative AI, check out these best practice guides:

• Generative AI Ethics: Concerns and Possible Solutions
• Generative AI and Cybersecurity: Ultimate Guide
• Risks of Generative AI: 6 Risk Management Tips

The post AI and Privacy Issues: Challenges, Solutions, and Best Practices appeared first on eWEEK.

“What we’re seeing is that no one model is sufficient to solve or address all use cases,” said Ankur Mehrotra, GM of SageMaker at AWS. “Customers are finding that one model may be better at building a particular kind of user experiences—let’s say a chat-based application—while another generative AI model may be better at assisting with coding or software development.” 

As the executive in charge of a platform that many companies use to build their generative AI models, Mehrotra understands the AI sector as well as anyone. Watch my extended interview with him to hear his thoughts about how companies are strategizing to build better AI models, along with a range of other AI-related topics.

Watch the full interview or jump to select interview highlights below.

AI Models Require Major Compute and Major Support

The long list of companies that have used AWS SageMaker to train and deploy their generative AI models includes AI pioneers like Perplexity AI, Hugging Face, and AI21 Labs. These companies come to AWS (and other top cloud companies) because they need massive compute power to train their AI models. On the AWS platform, an AI model training task gets distributed across a large number of compute instances, which are powered by Nvidia GPUs or AWS’s own silicon, Tranium.

As the model building process has evolved, more professionals are now required to create advanced models. “A few years ago, AI was mostly a data scientist activity, but over the years the number of personas involved in building AI-based solutions has really increased,” Mehrotra said. “We now have machine learning engineers get involved; they became responsible for taking these models and deploying them into production. And then other business stakeholders get involved to help convert a business problem into an ML problem, and then data engineers get involved to help prepare the data.”

This evolution has prompted SageMaker to continually evolve its toolset. “We’re really focused on ‘working backwards’ from our customers – understanding the need and building the right tool for the right job and the right persona.”

Shifting From Models to Model Systems

There’s a major trend developing in the world of artificial intelligence model building: even as many generative AI models are getting larger and more powerful, there are also plenty of smaller, highly focused models being created. Companies are thinking less about a one-size-fits-all model and more about niche business scenarios.

“When I talk to customers, what I hear is that they now foresee having to use multiple models,” Mehrotra said. “Some may be task-specific and others are more generalized, working together to achieve their goals. And the ability to do that quickly and safely and securely is very important to them.”

In essence, the development of AI models is turning into the process of building AI model systems.

“For example, one of our customers is deploying a set of different models where one model is responsible for redacting PII from text, then another model is taking that text and summarizing it,” he said. “So we are going to see that customers will think of these systems as model systems and use a combination of different models that are deployed together. We are also seeing trends where customers want the data to be co-located with these models [to help] create these model systems they’re using in production.”

(These comments have been edited for length and clarity.)

For more information about generative AI providers, read our in-depth guide: Generative AI Companies: Top 20 Leaders

The post AWS’s Ankur Mehrotra on Building Generative AI Models appeared first on eWEEK.

Here are our picks for the best AI meeting assistants of 2024:

• Fireflies.ai: Best for Advanced Features
• Fathom: Best Free AI Meeting Assistant
• Avoma: Best for Conversation Analysis and Insights
• Sembly: Best for Comprehensive Meeting Summaries
• Otter: Best for Transcription
• Krisp: Best for High-Quality Meeting Audio
• tl;dv: Best for UX and Product Teams
• MeetJamie: Best for Quick Meeting Summaries
• Airgram: Best for Team Collaboration
• MeetGreek: Best for Meeting Highlights and Keyword Detection
• Gong: Best for Sales Coaching

Best AI Meeting Assistants

The following table shows how the best AI meeting assistants compare at a glance, followed by detailed writeups of each of our picks.

Fireflies.ai

Best For Advanced Features

The Fireflies.ai AI-powered meeting assistant helps you to transcribe, summarize, record, filter, and analyze your virtual meetings and conversations. Like a fly on the wall, Fireflies joins your virtual meeting and captures video and audio recordings along with AI-powered notes so you can read, listen to, or share them.

This has a wide range of use cases, from recruiters reviewing hiring interviews to managers checking action items from their meetings to salespeople analyzing their recent sales calls to learn what went wrong.

With its advanced recording search and filtering feature, you can also find and listen to key points of the call. The conversation intelligence tool lets you track speaker time, sentiment, objections, competitors, and other custom data points you want to monitor and analyze.

In setting up Fireflies.ai, I liked how it prompted me to set rules for when it attends meetings and how it sends recaps that let me automate who receives the notes to ensure they don’t go to clients unless I specify.

Pros and Cons

Pricing

• Free: Up to 800 minutes of storage per seat
• Pro: $10 per user, per month billed annually; month-to-month plan costs $18 per user
• Business: $19 per user, per month billed annually; month-to-month plan costs $29 per user
• Enterprise: Custom quote

Features

• Integrates with more than 40 third-party tools across 10 categories
• Variable meeting audio playback speed
• Video screen capture capability
• Conversational intelligence
• Collaboration capabilities

Fathom

Best Free AI Meeting Assistant

Fathom is a free AI meeting note-taking tool that can record, transcribe, highlight, and summarize your meetings with no usage limitations. It works with Zoom, Microsoft Teams, and Google Meet and integrates with tools like HubSpot, Salesforce, and Zapier to enable the automatic transfer of meeting notes to these systems.

Although the free plan should suffice for most users, the company does offer a Fathom Premium plan and Team additions that offer advanced AI summaries and AI-triggered actions. You can try Fathom Premium for free for 30 days.

After exploring the demo, I noticed that the user interface is clean, and the meeting summaries are accurate and concise. The one thing that surprised me most about Fathom’s AI meeting minute-taking capabilities was how quickly it generated a summary with time stamps from the video call. In the demo, the summary outline was ready in less than 30 seconds. Action items are also automatically captured and saved on the sidebar, making it hard to forget them.

Pros and Cons

Pricing

• Free edition: Ideal for personal use
• Premium: $15 per user, per month
• Team Standard: $19 per user, per month
• Team Pro: $29 per user, per month

Features

• CRM sync (HubSpot, Salesforce, and Close)
• Okta SSO/SCIM integration
• Searchable repository for calls
• Unified view of all conversations with customers
• Keyword alerts

Avoma

Best for Conversation Analysis and Insights

Avoma is an end-to-end AI meeting assistant, conversation intelligence, and revenue intelligence tool that allows individuals and teams to capture, transcribe, analyze, and take automatic notes on meetings and sales calls.

Its powerful conversational intelligence feature sets it apart by helping business leaders and sales professionals glean critical insights from conversations about what is and isn’t working. For example, you can see which topics the most successful reps are discussing on their calls with prospects or create scorecards to objectively score conversations based on your chosen criteria, whether that’s the number of questions asked or time spent on a specific topic.

As I see it, the main benefit here goes to the sales leaders looking to develop more data-driven sales training plans. Yet it can also be useful for managers who want to teach their direct reports how to succeed in internal meetings.

Pros and Cons

Pricing

• Basic: Free for up to five meetings per month
• Starter: $19 per user, per month for up to 20 meetings, billed annually; $24 per user, per month for up to 20 meetings, billed monthly
• Plus: $49 per user, per month for unlimited meetings, billed annually; $59 per user, per month for unlimited meetings, billed monthly
• Business: $79 per user, per month, billed annually
• Enterprise: $149 per user, per month, billed annually

Features

• Scheduling capabilities, from access scheduling to group scheduling
• Meeting recording
• Tool to upload pre-recorded audio or video files
• Transcription and AI notes
• Conversational AI and automatic scorecard
• Integrations with CRM, video conferencing, and dialer tools

Sembly

Best for Creating Comprehensive Meeting Summaries and Minutes

Sembly is an end-to-end meeting assistant that transcribes, takes notes, and generates insights for your professional meetings. The solution also helps with scheduling. By syncing Sembly with your Outlook or Google calendar, you can permit it to automatically join all of your calls without downloading or installing any software. I found this automatic record feature of Sembly to be very helpful, as it saves time for users.

Best of all in my view, Sembly’s AI identifies key items in the discussion—such as actions, decisions, issues, risks, events, and requirements—and summarizes it all for you into a neat paragraph at the top of the notes. This feature enables you to get the gist of what was said and decided without reading through the entire text.

Pros and Cons

Pricing

• Personal: Free for a four-hour record limit and one-hour monthly upload, limited to one member
• Professional: $10 per month for one user, billed annually; $15 per month for one user, billed monthly
• Team: $20 per user, per month, billed annually, or $29 per user, per month, billed monthly; limited to 40 members
• Enterprise: Custom quotes

Features

• Integrates with task management tools such as HubSpot and Zapier
• Works with Zoom and other meeting apps
• Record and transcribe capabilities
• In-depth meeting notes
• Voice identification capability

Read our guide to the Best Artificial Intelligence Software to learn about the larger landscape of leading AI software.

OtterPilot

Best for Transcription

OtterPilot is an AI-powered meeting assistant that provides transcription and collaboration features, and when you connect it to your Google or Outlook calendars, it will automatically join your Zoom, Microsoft Teams, and Google Meet meetings.

The service is capable of transcribing both in-person and virtual meetings. It can be used for various purposes, including transcribing interviews, meetings, lectures, and podcasts, and works for audio and video files as well as YouTube. To save you time, the tool will also provide AI-powered summaries of the transcription, condensing as much as an hour of conversation into a 30-second brief.

In exploring the free version, I found the in-app AI chatbot helpful. It could summarize calls from last week, tell me the status of a deal, and even help me prepare for a meeting. I also found the user interface to be self-explanatory and the platform easy to navigate.

Pros and Cons

Pricing

• Basic: Up to 300 monthly transcription minutes
• Pro: $10 per user, per month, billed annually; $16.99 per user, per month, billed monthly
• Business: $20 per user, per month, billed annually; $30 per user, per month, billed monthly
• Enterprise: Quote available upon request

Features

• Automatic transcription
• Automatic sync of audio/video files from Dropbox
• Recording and playback capabilities
• AES-256 encryption for real-time content
• Search and keyword analysis
• Auto-sends meeting summaries to attendees

Krisp

Best for High-Quality Meeting Audio

Krisp is an AI-powered voice clarity and meeting assistant tool. It removes the background voices of other people talking in the same room and keeps only your voice on the call. If there’s a lot of noise at your home or corporate office—landscapers, kids playing, fellow salespeople—Krisp may be the perfect meeting assistant for you.

Its AI voice clarity technology offers background voice cancellation, noise cancellation, echo cancellation, and accent localization so clients, partners, colleagues, and peers won’t be distracted by other noises.

Krisp’s other meeting assistant capabilities include AI-powered meeting transcription and meeting notes, but in my view, the focus on audio quality is what helps Krisp stand out in a business environment increasingly prone to distraction.

Pros and Cons

Pricing

• Free: 60 minutes per day of noise, background voice, and echo cancellation; unlimited transcriptions
• Pro: $8 per user, per month, billed annually; $12 per user, per month, billed monthly
• Enterprise: Custom quotes

Features

• Automatic summarization
• Outbound and inbound noise cancellation
• Real-time meeting transcriptions
• Echo and background voice cancellation
• User management option

Tl;dv

Best for UX and Product Teams

tl;dv is an AI meeting assistant that automatically summarizes and takes notes on your meetings. Most notably in my view, it includes a full range of features that can help UX and product teams build better products more quickly. For example, it can automatically capture customer feedback and feature requests from sales meetings and send them to the product team.

It also makes collaborating on product development easier by allowing you to share snippets of product conversations and customer research calls with your other team members. Its AI keyword and topic identification tool helps you analyze all your customer calls to gain insight into their specific desires, letting you create feedback-driven products.

Pros and Cons

Pricing

• Free forever: No cost for small teams and individuals
• Pro: $18 per user, per month
• Business: $59 per user, per month
• Enterprise: Custom quotes

Features

• Transcribe and summarize in more than 20 languages
• Spot trends in customer conversations
• Capture customer feedback and feature requests
• Combine clips into reels
• Embed recordings and clips to WordPress and Notion
• Automatic speaker recognition

MeetJamie

Best for Automatic Meeting Summary

MeetJamie is an AI notetaker for meetings that works across 15 languages and most popular meeting tools, including Zoom, Teams, and Google Meet. MeetJamie is also capable of extracting tasks and detecting decisions in a meeting so that nothing falls through the cracks in your business meetings.

What I found most notable about the app was that, unlike the many artificial intelligence meeting assistant tools that automatically sync with your calendar and join your call when it’s meeting time, MeetJamie doesn’t send a bot to your meeting—instead, it records your meeting audio and generates transcripts and summaries. This is preferable for people who don’t want a bot hanging around in their virtual meetings and calls because they find it awkward or intrusive.

Pros and Cons

Pricing

• Free: Five monthly meeting credits for meetings up to 30 minutes
• Standard plan: $25 per user, per month
• Pro plan: $49 per user, per month
• Executive plan: $105 per user, per month

Features

• Automatic generation of summary and action items
• Custom note templates
• Meeting highlight
• Meeting recordings

Read our guide to the Top 20 Generative AI Tools and Apps to learn more about the leading artificial intelligence tools being used by enterprise companies.

Airgram

Best for Team Collaboration

Airgram is an AI meeting assistant that helps you record, transcribe, and share your meetings and conversations. It automatically turns speech into searchable, editable text that you can easily export to popular tools like Notion or Slack. This is great for looping in team members who were absent or not invited to the meeting but would still get value out of the key insights in the conversation.

Once transcribed, multiple people can comment on and edit the transcript of meeting notes, making it easy to collaborate with team members and clarify action items post-meeting.

Unlike other tools, Airgram also offers several meeting agenda templates and options, making it easy to set up meetings with a predefined structure. I found the tool’s templates to streamline the process of agenda-setting to be useful and user-friendly.

Pros and Cons

Pricing

• Free: 30 minutes maximum call duration
• Plus: $18 per user, per month

Features

• Share meeting snippets and links with internal and external contacts
• Transcribe imported audio and video files
• Associate notes from recurring meetings
• Works with Zoom and Google Meet

MeetGeek

Best for Highlights and Keyword Detection

MeetGeek integrates with your video conferencing tools to record, transcribe, and distribute meeting highlights to meeting participants. I found the distribution feature to be especially useful, and the tool’s keyword detection abilities mean many teams—including sales, HR, and marketing, for example—can benefit.

The sales team can use it to automatically capture notes and insights from customer calls, thereby pushing tasks and highlights into their CRM tools such as HubSpot, Pipedrive, or Salesforce. Meanwhile, HR teams can automatically sync meeting notes and recordings with their applicant tracking systems (ATS) to create rich candidate profiles that can be analyzed later.

Additionally, marketing teams can use it to make a repository of customers’ insights, allowing them to turn feedback into case studies.

Pros and Cons

Pricing

• Basic: Free plan
• Pro: $15 per user, per month, billed annually; $19 per user, per month, billed monthly
• Business: $29 per user, per month, billed annually; $39 per user, per month, billed monthly
• Enterprise: Starts at $59 per month

Features

• User management capability
• Integrations with third-party services, including HubSpot and Slack
• Automatic sharing for participants
• Highlight-capture and keyword-detection
• Exports transcripts to Google Docs, Word, and XLS

Gong

Best for Sales Coaching

Gong is an AI conversation intelligence platform designed to help sales reps and coaches record and analyze sales calls to identify best practices and mistakes. The coaching capability is what truly distinguishes Gong—coaches can drill into an individual rep’s or entire team’s sales call to identify talk ratio, question rate, topic duration, and other data points. With analytics, they can also quickly figure out which tactics work best and use these insights to develop sales training programs.

When a coach isn’t around, reps can also access a library of call recordings to self-teach themselves. They can watch and listen to what top performers are doing. Gong can also automate coaching with the AI insights which identify teachable moments in calls and offer reps data-driven recommendations.

Pros and Cons

Pricing

• Call for quote
• Pricing depends on license and number of users

Features

• Conversational intelligence
• Keyword tracking
• Topic duration analysis
• Sales call best practice identification
• Automatic call recordings and call library

Key Features of AI Meeting Assistant Software

While AI meeting assistant solutions vary from vendor to vendor on how they implement various features, the key features across most tools include meeting notes, action item tracking, integration with third-party services, and intelligent meeting search.

Meeting Notes and Transcript

Meeting notes are a critical component of AI meeting assistant software, as they help you remember the important details from your meeting and any action items that you or other team members need to complete before the next meeting. The transcription capability helps you capture every word spoken and creates a searchable record to refer to later.

Action Item Tracking

AI meeting assistants can track action items assigned during meetings and remind participants to complete them. Some software may even integrate with project management tools or task trackers to streamline this process. For example, Sembly and MeetGeek integrate with task and project management tools.

Integration with Third-Party Services

Another important feature to consider is integration with third-party apps. Syncing your AI meeting assistant tool with Calender apps like Google and Outlook and video conferencing software like Zoom, Google Meet, and Microsoft Teams will allow it to join your meetings and take notes for you automatically. Just be aware that not all AI meeting assistants integrate with all video conferencing tools. You need to verify that your selected tool can connect with your company’s existing software and tools.

​​Intelligent Meeting Search

AI-powered intelligent meeting tools allow you to use keywords to search through your AI meeting assistant’s past meeting notes, documents, and recordings to retrieve relevant information, eliminating the need for manual searching and saving time.

How to Choose the Right AI Meeting Assistant Tool for Your Business

The best AI meeting assistant for your business depends on your needs and preference—there is no one-size fits all AI meeting app. To choose the right AI meeting assistant for your business, consider the following:

• Company Needs: Specific pain points and challenges you hope to address with an AI meeting assistant. Do you need mainly transcription, or are you looking for an array of advanced tools?
• Organization Size: The size of your organization and the number of employees using the AI meeting assistant. You may select the enterprise plan, which typically offers a number of advantages.
• Budget: Some meeting assistant tools may be more affordable than others, while some may offer more advanced features but come at a higher cost.
• Integration with Existing Tools: Can it connect with your current tech stack?
• Features: Look for features that are beneficial to your organization and worth the cost that the AI meeting tool charges. What upgrades is the vendor planning?

How we Evaluated these Tools

We analyzed more than 30 AI meeting assistant tools and scored them based on five key data points: core features, customer service and support, cost, integrations, and ease of use. We assigned a score to each AI meeting assistant tool based on these factors to determine their overall ranking.

We selected the top 10 AI meeting assistant tools based on their scores and further evaluated them by conducting in-depth research including reading customer reviews, analyzing case studies and testimonials, and studying website and product documentation. We signed up for a free trial or free plan where possible to gain hands-on experience.

Frequently Asked Questions (FAQs)

What Is the Best AI Meeting Note Taker?

The best meeting note taker depends on your team’s current budget priorities. If you need a free AI meeting assistant with basic note-taking abilities, for instance, you can’t go wrong with Fathom.

Is There an AI to Take Notes on Team Meetings?

AI meeting assistants like Sembly can take notes on team meetings, record them, transcribe them, and even provide AI summaries and outlines of the conversation.

Can AI Transcribe a Meeting?

AI meeting assistants and note-taking apps like Avoma can connect with your meeting app and transcribe your voice and video meetings into text that is searchable and exportable to a variety of platforms.

Is There a Free AI to Take Notes During Meetings?

Fathom offers a generous free AI note-taking assistant that will take notes for you during your meetings. Most other AI meeting assistants also offer free plans with basic note-taking abilities.

What are the Different Types of AI Meeting Assistants?

The majority of AI meeting assistants are primarily note-taking apps that automatically transcribe and summarize meetings, but there are also AI meeting assistants that are more conversational intelligence tools, which not only transcribe but also analyze the conversations to identify trends, issues, and best practices.

What Is an AI Meeting Assistant?

An AI meeting assistant is an app or platform that automatically takes notes on your meetings, captures key decisions and action items, and records it in audio and/or video for review in a searchable, filterable database.

Why Do AI Meeting Assistants Matter?

AI meeting assistants automate meeting note-taking so that you can focus on engaging completely in your conversations with peers and clients instead of jotting down notes. These tools also make it easy to transcribe, record, and share aspects of your conversations, so you can easily review meetings and collaborate.

Bottom Line: The Best AI Meeting Assistants Greatly Enhance Productivity

The best AI meeting assistant tools enhance productivity and efficiency in meetings. However, be aware that AI meeting assistant software varies considerably from app to app. Though it may look like they offer the same value proposition and capabilities on the surface, accuracy can vary greatly between different providers. All the tools we reviewed offer free plans, which is a good starting point—sign up for a free plan and use it to get a feel for whether the tool will meet your needs.

Read our guide to AI Sales Tools and Software for a deeper understanding of today’s AI software for sales.

The post 11 Best AI Meeting Assistant (2024): Top Tools for Seamless Meetings appeared first on eWEEK.

What is AI Marketing?

AI marketing is the use of AI technologies to automate and optimize marketing processes based on data collection and analysis and the observation of trends. It enables faster, more personalized customer engagement through machine learning (ML), deep learning and natural language processing (NLP). Beyond data analysis, AI marketing tools also automate repetitive tasks like email campaigns and customer inquiries, letting marketing teams focus on crafting strategic campaign designs.

How to Use AI for Your Marketing Strategy

Integrating AI into your marketing strategy can substantially increase your brand’s reach, engagement, and conversion rates. Understanding how to use AI in marketing-related tasks gives you a competitive edge and turbocharges your marketing strategies.

• Content Creation: AI-powered tools can generate high-quality blog posts, social media updates, and even entire articles based on target keywords and topics, saving you time and ensuring a consistent brand voice across all your marketing channels.
• Personalization: By analyzing vast datasets, AI can determine individual customer preferences and behaviors, helping you to deliver personalized offers and recommendations.
• Ad Enhancement and Targeting: AI can predict ad performance using past ad data so you can adjust your ads to be more relevant to your target market.
• Creative Ideas: AI tools can aid in generating ideas for blog posts and article headlines, sparking creativity and adding a solid foundation for your marketing team to build upon.
• AI-Powered Chatbots: AI-powered chatbots can give seamless, personalized customer support by anticipating user needs and presenting relevant solutions, bringing customer experience to the next level and fostering loyalty.
• Intelligent Marketing Automation: AI marketing tools can automate repetitive tasks like managing subscriber lists and sending automated customer support messages, freeing up your team to focus on crafting personalized marketing campaigns, developing creative content, and strategizing for future growth.

Steps to Implement AI Marketing Strategy in Your Organization

Developing an AI marketing strategy shares similarities with traditional digital marketing approaches, but it relies on advanced automated technologies in the planning and data analysis phases. You need a structured approach to achieve successful AI marketing implementation. Here’s a step-by-step guide to seamlessly integrate AI into your marketing initiatives:

1. Define Marketing Goals and KPIs

Clearly outline marketing objectives that AI will support, such as lead generation. Develop specific Key Performance Indicators (KPIs) to measure success, aligning with qualitative goals, like improving customer experience.

2. Analyze Marketing Workflows and Needs

Assess your current workflows and find specific areas where AI can add value. Consider time allocation, bottlenecks, and effectiveness to prioritize AI solutions addressing specific pain points.

3. Select AI Solutions Aligned With Goals

Once you’ve established your marketing requirements, start researching AI solutions aligned with your needs. Consider factors like pricing, usability, integration, and scalability. Find solutions that are compatible with your existing workflows and have the necessary functionalities.

4. Conduct Team Training

Invest in training for your team to use AI tools effectively. Offer comprehensive sessions and workshops to build proficiency in data science and AI concepts.

5. Establish Data Privacy Standards

One of the biggest challenges of using AI is data privacy, making it important to define and implement robust privacy guidelines into your AI marketing platforms and ensure compliance with regulations to maintain consumer trust and mitigate legal risks.

6. Maintain Data Quality

Inaccurate or inconsistent data can lead to flawed AI outputs, leading to poor decision-making. You should enforce data management processes for data consistency and accuracy. This involves collaborating with data management teams to establish data cleansing frameworks, preventing errors that could compromise AI effectiveness.

7. Monitor Performance and Iterate

Continuously monitor AI marketing strategies against your established KPIs to track progress and uncover areas for improvement. Gather feedback to iterate on strategies and optimize outcomes.

8. Foster Continuous Learning

AI constantly and rapidly changing, Hence, you must encourage ongoing education within your marketing team to stay abreast of AI advancements. Equip your employee with training resources and experimentation opportunities to drive continuous improvement.

6 Benefits of Using AI Marketing Strategies

Adding AI into your marketing efforts introduces a multitude of benefits that can enhance your existing processes and propel your business forward. By applying AI, you can streamline tasks, gain valuable insights, and make data-driven decisions for better results.

Enhanced Efficiency and Productivity

AI accelerates content creation, automates routine tasks, and offers important data-driven insights. This allows for strategic allocation of time and resources. For example, AI-powered content generation tools can produce high-quality content at a faster rate, making sure you can generate a steady flow of high-quality content for your sites. Your human writers can concentrate on developing innovative story ideas, crafting compelling narratives, and adding their unique voice and perspective to the content.

Personalized Marketing and Customer Engagement

You can tailor your marketing strategies based on individual customer behavior and desires with AI, solidifying customer engagement and satisfaction. AI-driven chatbots also can give personalized recommendations and address your customers’ queries in real-time, creating a level of personalized interaction that boosts customer satisfaction and conversion rates.

Optimized Revenue and Campaign Performance

AI tools show valuable insights for making informed decisions about marketing budgets. They also aid with real-time adjustments to campaigns for better impact, leading to improved return on investment (ROI). For example, predictive analytics can help you refine your marketing campaigns based on past data. In addition, since AI can automate the monitoring and adjustment of advertising campaigns and optimize ad placements, you can minimize wasted ad spending.

Competitive Advantage and Scalability

AI marketing platforms automate processes for cost savings and allow you to scale your marketing initiatives. Along with innovative marketing techniques like chatbots, this provides you with a competitive edge. Automating data analysis, lead scoring, and campaign optimization enables you to handle larger volumes of data and customer interactions so that you can increase the effectiveness and reach of your marketing campaigns.

Predictive Analysis

AI’s ability to predict future customer behavior lets you anticipate needs and adjust your strategies accordingly. AI-driven predictive analytics can analyze large amounts of data to spot trends and patterns, so you can develop proactive marketing strategies that are more likely to resonate with your customers.

Improved Customer Support

Chatbots and virtual assistants powered by AI ensure immediate customer support 24/7. These tools can handle common customer queries, recommend products, and facilitate transactions. With prompt customer support, your business can elevate customer satisfaction and build trust.

3 Major Types of AI Marketing

The three main types of AI marketing–machine learning, computer vision, and natural language processing–can make your marketing more efficient, your campaigns more effective, and your insights more valuable.

Machine Learning

Machine learning (ML) is a powerful type of AI marketing that involves training algorithms on data to make predictions or decisions without being explicitly programmed to do so. It enables analysis of vast datasets to uncover patterns and trends, building first audience understanding and then audience engagement. ML continuously learns from new data, improving over time, and can facilitate sales forecasting and customer behavior analysis and refine campaign targeting.

Predictive Analytics

Predictive analytics in AI marketing uses ML to anticipate future outcomes by sifting through past data to identify patterns and trends, enabling you to forecast future consumer behaviors and market changes. A practical application of this AI marketing type is in forecasting product popularity in upcoming seasons for retail businesses.

Personalization

Personalization employs ML to customize marketing content and experiences to align with individual user preferences and behaviors. Commonly applied in e-commerce platforms, personalization is a way to offer better product recommendations based on past purchases and browsing history.

Generative AI

Through advanced ML techniques, generative AI (GenAI) brings a fresh approach to audience targeting, segmentation, and content creation. GenAI tools go beyond the scope of traditional personalization by creating one-of-a-kind marketing assets from scratch. These can range from personalized product recommendations to targeted social media posts or dynamic email campaigns tailored to individual customer preferences.

Computer Vision

In AI marketing, computer vision analyzes visual data such as images and videos to extract valuable insights. For example, it can identify patterns in customer behavior from video data, or analyze social media images for brand sentiment. These insights can then be used to personalize campaigns and enhance customer experiences, making marketing efforts more effective and targeted.

Image Recognition

Image recognition, a subset of computer vision, uses AI to identify and interpret objects and scenes within images. This technology is particularly useful in e-commerce, where customers can search for products by means of images instead of text. Image recognition is also employed in targeted advertising, analyzing user-generated content to serve more relevant ads.

Natural Language Processing

Natural language processing (NLP) enables machines to understand and respond to human language. This technology is pivotal in creating more interactive and intuitive customer service solutions like chatbots that can handle customer inquiries in real-time.

Semantic Search

This type of AI marketing uses NLP to understand search queries’ context and meaning to deliver relevant results. Unlike traditional keyword-based searches, it considers context, synonyms, and user intent. As a result, it heightens the accuracy of search results on e-commerce sites, which leads to better user experience.

Sentiment Analysis

This branch of NLP aims to determine the emotional tone conveyed in a piece of text, whether it’s positive, negative, or neutral. In AI marketing, sentiment analysis helps you understand public opinion, gauge customer feedback, and analyze brand sentiment derived from social media, online reviews, and surveys.

Chatbots

Chatbots use NLP algorithms to understand and respond to user queries or commands in natural language, such as text or speech. They can be deployed on websites, messaging platforms, or mobile apps to engage with customers, answer questions, provide support, and even assist in making purchasing decisions. With NLP, chatbots can simulate human-like conversations, personalize interactions, and enhance the overall customer experience, making them a valuable tool in AI marketing strategies.

3 Best AI Marketing Tools and Their Use Cases

While a number of AI companies offer solutions to help you incorporate AI into your business processes, we recommend Jasper AI, Grammarly, and Sprout Social for their strength in marketing.

Jasper AI

Jasper AI is a leading AI platform for enterprise marketing teams seeking exceptional outcomes rather than merely faster output. This AI-powered marketing tool streamlines marketing campaign creation, product description authoring for retailers, text and headline rewriting, and topic idea generation. It recognizes the nuances of various marketing channels and tailors its writing style accordingly, producing engaging social media captions, persuasive ad copy, and compelling email subject lines. It can assist in making your marketing copy more relevant and impactful.

Use Case

Creating and managing integrated marketing campaigns is one of the specialties of Jasper AI. If you upload a campaign brief, it can generate assets that you can use for a complete marketing campaign. This AI marketing tool also lets you repurpose your content across marketing channels, turning a single piece into multiple platform-specific assets for brand consistency. Jasper AI ensures alignment with your brand’s style by setting appropriate tone and formatting rules based on content analysis.

Grammarly

Grammarly is primarily an AI-powered writing assistant designed to cultivate communication through real-time feedback. While not specifically designed for marketing, this AI tool can aid you in writing high-quality marketing content and maintaining brand consistency across your organization. It comes with features such as Style Guides and Brand Tones, which can establish and enforce your brand’s voice and style across all written communications. You can make sure that every piece of your content is well-polished and aligns with your brand identity, building recognition with your audience.

Use Case

Grammarly can be used in content creation and editing in the marketing sector. For example, you can rely on it to generate ideas for your new campaign and receive feedback on your written content. You can adjust the length, complexity, or tone of your work, ensuring that the final output is engaging, error-free, and aligned with your brand’s identity.

Sprout Social

Sprout Social is a comprehensive social media management solution that employs AI for social listening across various platforms, which is highly valuable in marketing. It brings insightful data to aid in marketing content creation, customer care personalization, and marketing strategy optimization. Sprout Social seamlessly integrates with Facebook, Instagram, Twitter, LinkedIn, YouTube, Pinterest, TikTok, and WhatsApp, giving you the chance to reach a broader audience, maintain consistent branding across all platforms, and gather valuable data for analysis in a single place.

Use Case

Sprout Social is excellent in scheduling and publishing content across all your social media platforms, as well as handling digital ads and email campaigns. This accelerates the process and allows you to dedicate more time on strategy-building.

Frequently Asked Questions (FAQs)

How Can I Use AI to Boost Sales?

You can use AI to boost sales in several ways, including personalization, optimization, and data analysis. Here’s how it works:

• Personalization: AI-powered chatbots and recommendation engines can provide a personalized customer experience and deliver tailored offers, elevating customer engagement.
• Optimization: AI can be used for lead scoring and sales task automation, helping you prioritize potential customers and raises the productivity of your sales team, leading to increased sales.
• Data Analysis: AI can analyze customer data to uncover insights, test marketing campaigns, and shed light on how to adjust sales rep performance, so you can refine your sales strategies.

What Jobs are AI Proof?

AI is still in its early stages of development and lacks the ability to effectively handle tasks that require a deep level of human interaction, empathy, creativity, and decision-making based on complex factors. However, it’s important to note that AI is a rapidly evolving field and its impact on industries and jobs can change over time. Here are some of the jobs that can be considered for now:

• Social Work: This involves understanding human behavior and navigating complex social situations.
• Teaching: Education centers around building human connections, showing empathy, and fostering understanding in students.
• Creative Professionals: Working as artists, writers, musicians, and designers calls for a level of creativity and innovation that AI currently cannot replicate.
• Healthcare Professionals: Nurses and doctors need a thorough understanding of human biology and psychology to diagnose, treat, and care for patients.

Bottom Line: Future-Proof Your Business With an AI Marketing Strategy

AI’s influence in marketing is inevitable and continues to grow. Just a few years ago the idea of automating content creation or personalized advertising seemed far-fetched, but now it’s standard practice, with major corporations harnessing AI to tailor marketing efforts and engage with customers on a deeper level. Embracing AI in marketing allows you to use its power to enhance your strategies.

This ultimate guide is meant to help you gain a deeper understanding on how you can use AI to the fullest to support your marketing initiatives by developing an AI marketing strategy that aligns with your business’s needs and prepares it for the future.

AI is changing the game in numerous fields, not just in marketing. Find out how AI is making waves in project management by reading our article on AI’s benefits, use cases, and key considerations.

The post AI Marketing Strategy: How to Use AI for Marketing (Examples & Tools) appeared first on eWEEK.

We evaluated the best generative AI chatbots on the market to see how they compare on cost, feature set, ease of use, quality of output, and support to help you determine the best bot for your business. Here are our picks for the top 21 generative AI chatbots for 2024.

Top Generative AI Chatbot Software

The following chart shows at a glance how the top generative AI chatbot software we evaluated compares on features, query limit, language model, and price—as well as whether the vendor provides a Chrome extension to improve ease of use—to help you determine the best option for your needs.

Freshchat

Best for Automating Self-Service

Overall Rating: 4.6

• Cost: 5
• Feature Set: 5
• Ease of Use: 5
• Quality of Output: 5
• Support: 2.5

Freshchat enables businesses to automate customer interactions through chatbots and also offers live chat capabilities for real-time customer support. It allows companies to manage and streamline customer conversations across various channels and an array of integrated apps.

Freshchat provides features like customizable chat widgets, agent collaboration, customer context, and analytics to track chat performance and customer satisfaction. What distinguishes Freshchat is that it enables sales and marketing—and even support teams—to not only reach customers but to scale those interactions so that the expertise of each live company staffer can be used to converse with many customers.

It does this using its unified agent workspace—which holds a full menu of past conversations—as well as responses from sales, marketing, and support, which an agent can quickly and easily share with an interested customer.

What I found most interesting was that the app has a “Freddy Insights” tool that provides key trends and insights that can be fed into a conversation at opportune moments to prompt a faster decision.

Pros and Cons

Pricing

• Free: Up to 10 agents
• Growth: $23 per agent, per month, or $228 per agent billed annually
• Pro: $59 per agent, per month, or $588 per agent billed annually
• Enterprise: $95 per agent, per month, or $948 billed annually

Features

• Chatbot analytics
• Canned responses
• Customer satisfaction (CSAT) survey and report
• Analytics and reporting
• Multi-channel communication

Crisp Chatbot

Best for Lead Nurturing

Overall Rating: 4.6

• Cost: 5
• Feature Set: 3.5
• Ease of Use: 5
• Quality of Output: 5
• Support: 5

Crisp Chatbot uses artificial intelligence to understand user queries and provide relevant responses. It can handle basic inquiries, provide product information, schedule appointments, and collect customer feedback.

In a growing trend across the AI chatbot sector, the Crisp Chatbot can be customized to match a business’s branding and tone. This is increasingly important in crowded markets where a number of companies are seeking to create a distinct brand to cut through the clutter.

In my conversations with Crispchat, I found the bot extremely helpful at answering my questions. When I asked whether it was good for small businesses, it answered in the affirmative and gave me two salient reasons why—24/7 support and ease-of-use—while also explaining the positive impact these would have on my company’s customer experience.

Pros and Cons

Pricing

• Free: 14-day trial
• Basic: Free forever for two seats
• Pro: $25 per month, per workspace for up to four seats
• Unlimited: $95 per month, per workspace for up to 20 seats
• Enterprise: Contact for custom quote

Features

• Integrations with social apps like Facebook Messenger, WhatsApp, Line, and Instagram
• Conversation routing capability
• Capable of sending multilingual messages
• MagicReply feature provides suggested AI-powered chatbot answers on multiple channels, in several languages

ChatGPT

Best Chatbot for Versatility and Advanced Generative AI Chat Features

Overall Rating: 4.5

• Cost: 4.2
• Feature Set: 4.4
• Ease of Use: 5
• Quality of Output: 3.8
• Support: 5

Developed by OpenAI as part of the GPT (generative pre-trained transformer) series of models, ChatGPT is more than just another natural language processing (NLP) tool designed to engage in human-quality conversations with users. The fact that it was developed by OpenAI means this generative AI app benefits from the pioneering work done by this leading AI company. ChatGPT was the first generative AI app to come to market, launching in November of 2022.

The OpenAI platform can perform NLP tasks such as answering questions, providing recommendations, summarizing text, and translating languages. Aside from content generation, developers can also use ChatGPT to assist with coding tasks, including code generation, debugging help, and programming-related question responses.

I have used ChatGPT for various tasks, from summarizing long articles for research purposes to brainstorming business plans and customer pain points. The output is almost always satisfactory, in-depth, and surprisingly nuanced.

OpenAI has received significant funding from Microsoft and will likely be a leader in the years ahead, both in terms of advanced functionality (depth and versatility of toolset) and its ability to offer technology that’s ahead of the curve.

Pros and Cons

Pricing

• Free: Access to limited features
• ChatGPT Plus: $20 per month
• Enterprise: Contact OpenAI for a custom quote

Features

• Analytics dashboard for enterprise users
• Can understand and generate text in multiple languages
• Offers contextual understanding of extended conversation

Kommunicate

Best for e-Commerce Businesses

Overall Rating: 4.5

• Cost: 3.3
• Feature Set: 5
• Ease of Use: 5
• Quality of Output: 5
• Support: 4

Kommunicate is a generative AI-powered chatbot designed to help businesses optimize customer support and improve the customer experience. One of its chief goals is assisting and completing sales for e-commerce vendors, though it also handles support and the full range of customer queries.

The app provides automated conversational capabilities through chatbots, live chat, and omnichannel customer support. Kommunicate can be integrated into websites, mobile apps, and social media platforms, allowing businesses to engage with customers in real time and provide instant assistance regarding any issue that involves a sale or service.

To assist with this, it offers a FAQ bot to lessen the load of simple, repetitive customer queries. The app’s feature set is far more robust due to a long list of integrations, including OpenAI, IBM Watson, Zapier, and Shopify. It enables easy, seamless hand-off from chatbot to a human operator for those interactions that call for it.

Pros and Cons

Pricing

• Free: 30-day trial
• Lite: $100 month-to-month, or $1,000 billed annually, for up to two teammates; $20 per month for each additional teammate
• Advanced: $200 month-to-month, or $2,000 billed annually, for up to five teammates; $30 per month for each additional teammate
• Enterprise: Custom pricing

Features

• Omnichannel—web, mobile, and social media
• CSAT rating
• Integrations with third-party services
• Can manage customer conversations through bots, live chat, Facebook, WhatsApp, and Line

Claude

Best Chatbot for Long Conversational Memory

Overall Rating: 4.4

• Cost: 5
• Feature Set: 3.5
• Ease of Use: 5
• Quality of Output: 5
• Support: 4

Claude is Anthropic’s free AI chatbot. It runs Claude 3, a powerful LLM known for its large context window of 200,000 tokens per prompt, or around 150,000 words. This gives it one of the best conversational memories around.

To put that in perspective, you can be at the tail end of a conversation the size of Jane Austen’s Pride and Prejudice and Claude will still remember everything that was said, taking your previous questions, file uploads, and responses into account when it responds to your newest prompts.

Its ability to analyze and summarize long documents is excellent, and its answers tend to be more straightforward than those of Chat-GPT. When trying Claude, I was constantly surprised at how concise its answers were to my questions. It felt like I was messaging a true human expert rather than someone going out and finding the answers and regurgitating them back to me. All of this makes Claude a valuable research assistant and creative collaborator

Pros and Cons

Pricing

• Free: Unlimited access to Claude.ai chat
• Claude Pro: $20 per month

Features

• 200,000 token context window (around 500 pages)
• Document summarization and analysis
• Straightforward, clear responses
• Integrates with 600 apps through Zapier

ChatSpot

Best for HubSpot Customers

Overall Rating: 4.4

• Cost: 5
• Feature Set:5
• Ease of Use: 5
• Quality of Output: 5
• Support: 1

ChatSpot combines the capabilities of ChatGPT and HubSpot CRM into one solution. With this tool, you can draft blog posts and tweets and also create AI-generated images, or you can feed it a prompt to enable you to get specific data from your HubSpot CRM.

ChatSpot allows you to perform many functions, including adding contacts and creating tasks and notes. You can also ask it to summarize your CRM data or generate a bar chart of results to understand your company’s performance.

If you’re a HubSpot customer, this chatbot app can be a useful choice, given that Hubspot offers so many ways to connect with third party tools—literally hundreds of business apps. And HubSpot, as its users are well aware, is a platform that offers great functionality for sales reps. This chatbot will likely remain a top candidate for sales and marketing professionals who need improved functionality for customer sales and service.

Pros and Cons

Pricing

• ChatSpot is free

Features

• Uses OpenAI’s GPT-3 and GPT-4
• Integration with ChatGPT, HubSpot, DALL-E, and Google Docs
• Prompt templates and library

Intercom

Best for Handling Support Queries

Overall Rating: 4.3

• Cost: 2.3
• Feature Set: 5
• Ease of Use: 4.5
• Quality of Output: 5
• Support: 5

Intercom AI’s chatbot, Fin, powered by large language models from OpenAI, aims to improve customer experience, automate support processes, and enhance user engagement. The fact that OpenAI (with all of its deep funding and vast expertise) provides Intercom’s underlying engine is clearly a plus.

Intercom can engage in realistic conversations with customers, helping to resolve common issues, answer questions, and initiate actions. It’s an app aimed clearly at the lucrative call center sector. In trying Intercom while acting as a customer seeking assistance, I found that its answers to my questions were helpful and quick. It also felt like there was a human on the other end of the chatbox.

So, what distinguishes it? It has gained wide adoption in the industry and is used by companies ranging from Amazon to Microsoft to Meta. It also offers a “plug and play” chatbot architecture to make setup relatively easy. And Intercom’s “Composer AI” feature enables a call center rep to rephrase a message with one click, turning a single phrase into longer, more detailed response. It can easily summarize entire conversations with one click.

Pros and Cons

Pricing

• Free: 14-day trial
• Fin AI Chatbot: Usage measured in resolutions; $0.99 per resolution.
• Essential: ​​$39 per seat, per month
• Advanced: $99 per seat, per month
• Expert: $139 per seat, per month

Features

• Supports up to 43 languages
• Integrates with Facebook and Instagram
• Answers customer questions based on support content
• Makes article suggestions

Google Gemini

Best Chatbot for Brainstorming Ideas

Overall Rating: 4.3

• Cost: 5
• Feature Set: 5
• Ease of Use: 4.5
• Quality of Output: 5
• Support: 1

Formerly known as Bard, Google Gemini is an AI-powered LLM chatbot built on the PaLM2 (Pathways Language Model, version 2) AI model. You can export your Google Gemini conversation to Google Docs or Draft in Gmail, and the platform allows you to create a shareable public link you can send to a third party, making it useful in collaborative workflows for professional work environments.

It’s a major plus for this app that it’s developed and supported by Google. Admittedly, this app had some difficulties when it was first rolled out. Apparently scrambling to keep up with the phenomenal success of OpenAI’s ChatGPT, Google didn’t iron out all the bugs first. However, Gemini is being actively developed and will benefit greatly from Google’s deep resources and legions of top AI developers.

An important benefit of using Google Gemini is that its supporting knowledge base is as large as any chatbot’s—it’s created and updated by Google. So if your team is looking to brainstorm ideas or check an existing plan against a huge database, the Gemini app can be very useful due to its deep and constantly updated reservoir of data.

Pros and Cons

Pricing

• Free to use

Features

• Can export conversations
• “Google it” function directs you to search engine to provide more information
• Can generate code in 20 programming languages

For an in-depth comparison of two leading chatbots, read our guide: ChatGPT vs. Google Bard: Generative AI Comparison

Jasper

Best Chatbot for Marketing and Sales Teams

Overall Rating: 4.2

• Cost: 2.7
• Feature Set: 5
• Ease of Use: 5
• Quality of Output: 5
• Support: 3

The Jasper generative AI chatbot can be trained on your brand voice to interact with your customers in a personalized manner. Jasper partners with OpenAI and uses GPT-3.5 and GPT-4 language models and their proprietary AI engine. The company also sources from other models such as Neo X, T5, and Bloom.

Jasper’s strongest upside is its brand voice functionality, which allows teams and organizations to create highly specific, on-brand content. This capability is invaluable for marketing and sales teams that need to ensure that all chatbot communications are created with an accurate brand identity.

Out of the box, Jasper offers more than 50 templates—you won’t need to create a chatbot persona from scratch. The wide array of models that Jasper accesses and its focus on customizing for brand identity means this is a choice that marketing teams should at least audition before they make any final selections for an AI chatbot.

Pros and Cons

Pricing

• Creator: $49 per month billed monthly, or $468 billed annually
• Pro: $69 per month billed monthly, or $708 billed annually
• Business: Custom quotes

Features

• Browser extension available
• Supports up to 30 languages.
• Integrates with Zapier, Webflow, Make, Google Sheets, and other tools
• Collaboration capability

For a full portrait of today’s generative AI leaders, see our guide: Generative AI Companies: Top 12 Leaders

Tidio

Best for Small and Medium-Sized Businesses

Overall Rating: 4.2

• Cost: 4.1
• Feature Set: 3.5
• Ease of Use: 5
• Quality of Output: 5
• Support: 4

SMBs looking for an easy-to-use AI chatbot to scale their support capacity may find Tidio to be a suitable solution. Tidio Lyro lets businesses automate customer support processes, reduce response times, and handle tasks such as answering frequently asked questions. You can also use Tidio Lyro to answer customer inquiries, provide automated responses, and assist with basic analytics, allowing you to manage customer support efficiently.

Tidio fits the SMB market because it offers solid functionality at a reasonable price. SMBs are under pressure to offer basic customer service at a low cost; to address this, Tidio allows the creation of a wide array of prewritten responses for simple questions that customers ask again and again. Tidio also offers add-ons at no extra cost, including sales templates to save time with setup.

Additionally, the quality of Tidio’s output was ranked highly in our research, so even as the AI chatbot focuses on affordability, it offers a quality toolset.

Pros and Cons

Pricing

• Free: Up to 50 live chat conversations
• Lyro AI: Starts at $39 per month for up to 200 conversations
• Tidio+: Starts at $499 per month

Features

• Live chat capability
• Integration with Messenger, Instagram, WhatsApp, and email services
• Multi-language support
• Canned responses

Perplexity AI

Best Chatbot for Finding Information on the Internet

Overall Rating: 4.2

• Cost: 4.2
• Feature Set: 4.4
• Ease of Use: 5
• Quality of Output: 5
• Support: 2

Perplexity AI is a generative AI chatbot, search, and answer engine that allows users to express queries in natural language​​ and provides answers based on information gathered from various sources on the web. When you ask a question of Perplexity AI, it does more than provide the answer to your query—it also suggests related follow-up questions. In response, you can either select from the suggested related questions or type your own in the text field.

Perplexity AI’s Copilot feature can guide users through the search process with interactive multiple searches and summarized results. This capability is helpful when exploring complex topics. However, it’s limited to five searches every four hours for free plan users and up to 300 searches for paid users.

Perplexity AI’s strength in searching the internet means this tool is ideal for advanced researchers, from academic to small business to large enterprise, including companies that want to explore how they’re viewed on the web. Because AI enables it to understand your search query at a multi-dimensional level, the app can guide you in directions you might not have thought of, making it “serious researcher’s best friend.”

Pros and Cons

Pricing

• Free: Limited features
• Pro: $20 per month, or $200 per year

Features

• Supports Claude 3, Llama 3, and GPT-4
• Supports 30 languages, including English, Bengali, and Danish
• Text and PDF file upload capability

LivePerson

Best for Conversation Analytics

Overall Rating: 4.1

• Cost: 0.6
• Feature Set: 5
• Ease of Use: 5
• Quality of Output: 5
• Support: 5

The LivePerson AI chatbot can simulate human conversation and interact with users in a natural, conversational manner. Its goal is to discover customer intent—the core of most successful sales interactions—using analytics. To this end, LivePerson offers what it calls a “meaningful automated conversation score,” a metric that attempts to quantify whether a given bot-human interaction was successful in terms of company branding and service.

Additionally, the platform enables you to convert webpages, PDFs, and FAQs into interactive AI chatbot experiences that use natural human language to showcase your brand’s expertise. The bot’s entire strategy is based on making as much content as possible available in a conversational format.

LivePerson can be deployed on various digital channels, such as websites and messaging apps, to automate customer interactions, provide instant responses to inquiries, assist with transactions, and offer personalized recommendations. Significantly, LivePerson is also geared to be embedded in social media platforms, so it certainly aims to reach a large consumer base.

Pros and Cons

Pricing

• Conversational Cloud: Pay-as–you-go, per resolution
• Generative AI: Pay-as-you-go, per resolution

Features

• Conversation builder and orchestrator
• Administrative function includes the ability to create and manage users and skills
• Supports 19 messaging channels, including Facebook, Instagram, X  and WhatsApp.
• Reporting and analytics

Chatsonic

Best Chatbot for Individuals in the Creative Industries

Overall Rating: 4

• Cost: 4.6
• Feature Set: 4.4
• Ease of Use: 5
• Quality of Output: 2.5
• Support: 2

Trained and powered by Google Search to converse with users based on current events, Chatsonic positions itself as a ChatGPT alternative. The AI chatbot is a product of Writesonic, an AI platform geared for content creation. Chatsonic lets you toggle on the “Include latest Google data” button while using the chatbot to add real-time trending information.

The benefit of this “latest data” approach is that it helps individuals in creative fields like advertising and marketing stay up to date on current trends. In contrast, some of the more advanced chatbots use large language models that are updated infrequently, so those looking for this week’s information won’t find what they need.

This current events approach makes the Chatsonic app very useful for a company that wants to consistently monitor any comments or concerns about its products based on current news coverage. Some companies will use this app in combination with other AI chatbot apps with the Chatsonic chatbot reserved specifically to perform a broad and deep brand response monitoring function.

Pros and Cons

Pricing

• Free: Up to 10,000 words per month
• Unlimited: $20 per month billed monthly, or $192 billed annually for one user
• Business: $19 per month billed monthly, or $152 billed annually for one user; up to 200,000 words for GPT 3.5 or 33,333 words for GPT 4.0; add words and users for additional cost
• Enterprise: Custom quote

Features

• Google Docs-like Sonic Editor
• Integration with third-party apps
• More than 100 AI templates

Poe

Best Chatbot for Testing Multiple AI Chatbots

Overall Rating: 3.9

• Cost: 5
• Feature Set: 2.8
• Ease of Use: 4.5
• Quality of Output: 5
• Support: 3.9

Poe is a chatbot tool that allows you to try out different AI models—including GPT-4, Gemini, Playground, and others listed in this article—in a single interface. This is helpful for people who want to pit them against each other to decide which tool to purchase. It’s also great for those who plan to use multiple LLM models and unlock their various strengths for a low price of $16.67 per month when paid annually.

For example, if you plan to use Claude 3 for conversational chat and GPT 4 for content generation—their respective specialties—you can get both by subscribing to Poe rather than paying for each separately, which would cost $40 per month. Developers can also use Poe to build their own chatbots using one of the popular models as the foundation, streamlining the process.

Pros and Cons

Pricing

• Free: Limited access
• Poe Subscription: Starts at $16.67 per month; includes unlimited daily messages and access to exclusive bots like GPT 4 and Claude-3-Opus

Features

• Test and compare multiple popular AI chatbots
• Access multiple AI chatbots like GPT-4 and Claude-3-Opus for low price
• Free version available
• Streamlines building your own AI chatbot using a top LLM as your model

Drift

Best for Businesses that Rely on B2B Sales and Marketing

Overall Rating: 3.8

• Cost: 1.8
• Feature Set: 5
• Ease of Use: 4.5
• Quality of Output: 5
• Support: 2

Drift’s AI is trained on more than 100 million B2B sales and marketing conversations, enabling it to understand and respond to B2B customer inquiries in the conversational manner that’s expected in this market sector—including multi-language support.

The Drift AI chatbot is designed to handle different types of conversations, including lead nurturing, customer support, and sales assistance. It can engage with website visitors and provide relevant information or route inquiries to the appropriate human representative.

Drift can be custom-trained for your B2B business in fine detail, allowing it to learn your brand’s voice and respond in a manner similar to your in-house reps. The B2B market is a specific use case for AI chatbots, and Drift’s focus on this market means that a B2B company can set up a highly functional chatbot that will evolve with the B2B market over time with less work.

Pros and Cons

Pricing

• Premium: $30,000 billed annually
• Advanced: Available upon request
• Enterprise: Custom quote

Features

• User administration with role-based access control
• Live chat, custom chatbots, and AI-powered chatbots
• Meeting scheduler with Google, Office 365, and Teams integration
• Conversation and conversion reporting capability

Ada

Best for Customer Service Automation

Overall Rating: 3.8

• Cost: 0.6
• Feature Set: 5
• Ease of Use: 5
• Quality of Output: 5
• Support: 2.5

Ada is an AI-powered customer service automation platform that uses natural language processing and machine learning algorithms to automate customer service tasks. It is designed to help resolve customer issues, allowing businesses to streamline customer service operations and enhance the customer experience.

There are two ways to use Ada. You can either connect it to your knowledgebase and use generative AI to answer questions grounded in your existing content, or build a hard-coded chatbot using Ada’s natural language understanding and its drag-and-drop platform for a pre-scripted easy and fast setup.

In either case, Ada enables you to monitor and measure your bot KPI metrics across digital and voice channels—for example, automated resolution rate, average handle time, containment rate, CSAT, and handoff rate. It also offers predictive suggestions for answers, allowing the app to stay ahead of customer interactions. Ada’s user interface is intuitive and easy to use, which creates a faster onboarding process for customer service reps.

Pros and Cons

Pricing

• Generative: Contact Ada’s sales team for quote
• Scripted: Contact Ada’s sales team for quote

Features

• Integrations with third-party apps like Shopify, Marketo, and Clearbit
• Automated resolution measurement
• Advanced branding including additional customizations

YouChat

Best Chatbot for Students

Overall Rating: 3.6

• Cost: 5
• Feature Set: 2.9
• Ease of Use: 5
• Quality of Output: 3.8
• Support: 1

Designed by You.com, YouChat is an AI-powered generative chatbot that can summarize text, write code, suggest ideas, compose emails, and answer general questions based on information available on the web.

It also cites its information source, making it easy to fact-check the chatbot’s answers to your queries. YouChat combines various elements in search results, including images, videos, news, maps, social, code, and search engine results on the subject.

In essence, YouChat is a lighter weight tool with an affordable price plan that performs a wide array of tasks—particularly those needed by students. YouChat offers an easy user interface that will appeal to a busy user base that wants to jump right in without undergoing a lot of technical training.

The upside of this kind of easy-to-use app is that, as generative AI advances, today’s fairly lightweight tools will likely offer an enormous level of functionality. So any student or SMB user who starts with it now will probably reap greater benefits in the months and years ahead.

Pros and Cons

Pricing

• Free: Up to 10 AI writing generations
• YouPro: $14.99 per month
• YouPro for Education: $6.99 per month

Features

• Code generator
• Multimodal search capability
• Support for social media profiles

HuggingChat

Best Chatbot for Developers

Overall Rating: 3.3

• Cost: 5
• Feature Set: 2.9
• Ease of Use: 4.8
• Quality of Output: 1.3
• Support: 1

Developed by Hugging Face, HuggingChat is a chatbot based on the Open Assistant Conversational AI Model. It uses NLP and ML algorithms to interact with users and can generate answers to questions, write essays, write code, translate text, and construct emails. The platform has been trained on a large dataset of diverse conversations and can learn from new interactions.

Hugging Face has a large and enthusiastic following among developers—it’s something of a favorite in the development community. Its platform is set up as an ideal environment to mix and match chatbot elements, including datasets ranging from Berkeley’s Nectar to Wikipedia/Wikimedia, and the AI models available range from Anthropic to Playground AI.

Many of these resources may not mean much to the SMB owner or enterprise manager, but they mean a great deal to developers with the expertise to use a deep resource base to customize an AI chatbot. Given that HuggingChat offers such a rich developer-centric platform, users can expect it to grow rapidly as AI chatbots are still gaining more adoption.

Pros and Cons

Pricing

• Free: Limited access
• Pro: $9 per month; gives early access to new features
• Enterprise Hub: $20 per user, per month

Features

• Web search functionality complements response with web content
• Multilingual support
• Can debug and write code and create Excel formulas

Replika

Best for Personal Use

Overall Rating: 3.2

• Cost: 5
• Feature Set: 0.6
• Ease of Use: 5
• Quality of Output: 5
• Support: 1.5

Replika is an artificial intelligence chatbot designed to have meaningful and empathetic-seeming conversations with users. It’s focused more on entertaining and engaging personal interaction rather than straightforward business purposes.

To support its goal, Replika uses natural language processing and machine learning algorithms to understand and respond to text-based conversations. Replika aims to be a virtual friend or companion that learns from and adapts to your personality and preferences.

To better engage, the platform learns your texting style and mimics it. Of course, this means that the longer you interface with the app, the more accurately Replika can mimic your style.

Its motto is “My AI Friend,” and the vendor claims that it can offer dialogue geared for emotional support. To that end, it can engage in a wide variety of topics or even help you learn new things.

Pros and Cons

Pricing

• Free: Limited access
• Month-to-Month: $19.99
• Annual: $69.96.
• Lifetime: $299.99

Features

• Role-playing activities
• Communication through text, pictures, voice calls, and video calls
• Can engage in conversations about a wide range of topics, from personal interests to general knowledge
• Guides users through specific conversation topics such as mindfulness, stress management, or self-care

Bing Chat Enterprise

Best Chatbot for Organizations in the Microsoft Ecosystem

Overall Rating: 3.1

• Cost: 4
• Feature Set: 3.5
• Ease of Use: 1.8
• Quality of Output: 2.5
• Support: 4

Microsoft generative AI tool Bing Chat Enterprise uses GPT-4, which includes a top large language model, to generate natural language responses to user queries. Bing Chat Enterprise has three conversation styles: creative, balanced, and precise. These styles help you set the tone for the expected response to your query.

Bing Chat Enterprise is available in 160 regions. Users can also access it via the Windows Copilot Sidebar, making this app easily accessible. Microsoft is incorporating AI across its product portfolio, so this chat app will likely show up in a number of applications. If your company uses Microsoft, this chat app is a good choice.

The greatest strong point for the Bing Chat tool is that it’s produced by Microsoft, arguably the leader in AI today. The company’s deep resources and dominant technical expertise in AI software should support this chat app very well in the years ahead.

Microsoft is also skilled at serving both the consumer and the business market, so this chat app can be configured for a variety of levels of performance. It has the depth of features needed to serve the SMB market and large enterprise.

Pros and Cons

Pricing

• Free: Available to customers licensed for Microsoft 365 E3, E5, Business Standard, Business Premium, or A3 or A5 for faculty
• Standalone: $5 per user, per month

Features

• Versatile mix of conversation styles for different enterprise AI use cases
• Citation capability lets you fact-check output
• Lets users upload images or can generate images

OpenAI Playground

Best Chatbot for Customizability

Overall rating: 3.0

• Cost: 4.15
• Feature Set: 5
• Ease of Use: 0.55
• Quality of Output: 2.5
• Support: 2

OpenAI Playground was designed by the same generative AI company that created ChatGPT (see above). As such, it is well funded and is continuously improved by some of the best developers in the AI industry. Expect it to stay ahead of the curve in terms of feature set.

The platform is a web-based environment allowing users to experiment with different OpenAI models, including GPT-4, GPT-3.5 Turbo, and others. OpenAI Playground is suitable for advanced users looking for a customizable generative AI chatbot model that they can fine-tune to suit their business needs. This advanced platform enables a vast level of choices and approaches in an AI chatbot.

OpenAI Playground’s focus on customizability means that it is ideal for companies that need a very specific focus to their chatbot. For instance, a sophisticated branding effort or an approach that requires a very proprietary large language model, like finance or healthcare. Given that this app needs true developer expertise to be fully customizable, it is not the best choice for small businesses or companies on a tight budget.

Pros and Cons

Pricing

Priced per 1,000 tokens, about 750 words; varies by model choice. New users get $5 in free credit to use for their first three months.

• GPT-4 Models: Input costs $0.03, output costs $0.06 for 8,000 context; input costs $0.06, output costs $0.12 for 32,000 context
• GPT-3.5 Turbo: Input costs $0.0015, output costs $0.002 for 4,000 context; input costs $0.003, output costs $0.004 for 16,000 context

Features

• Text and completion summarization
• Multiple options for model selection
• Language translation
• Sentiment analysis

Key Features of Generative AI Chatbots

Generative AI chatbots require a number of advanced features to accomplish their many tasks, ranging from context understanding to personalization.

Natural Language Processing

Natural language processing is a critical feature of a generative AI chatbot. NLP enables the AI chatbot to understand and interpret casual conversational input from users, allowing you to have more human-like conversations. With NLP capabilities, generative AI chatbots can recognize context, intent, and entities within the conversation.

Context Understanding

Context understanding is a chatbot’s ability to comprehend and retain context during conversations—this enables a more seamless and human-like conversation flow. A high-quality artificial intelligence chatbot can maintain context and remember previous interactions, providing more personalized and relevant responses based on the conversation history. This enables chatbots to provide more coherent and relevant replies.

Personalization

When shopping for generative AI chatbot software, customization and personalization capabilities are important factors to consider as they enable the tool to tailor responses based on user preferences and history. ChatGPT, for instance, allows businesses to train and fine-tune chatbots to align with their brand, industry-specific terminology, and user preferences.

Multilingual Support

An AI chatbot’s ability to communicate in multiple languages makes it appealing to global audiences. This functionality also allows the chatbot to translate text from one language to another.

How to Choose the Best Generative AI Chatbot For Your Business

The best generative AI chatbot for your company serves your business’s needs and balances quality service with moderately expensive or lower cost pricing based on what works with your budget. Additionally, you’ll need to ensure it has all the necessary AI features you need for your operations, and that these features will be supported going forward.

Organizations in the Microsoft ecosystem may find Bing Chat Enterprise beneficial, as it works better on the Edge browser. ChatGPT does not cite its data sources, but it is one of the most versatile and creative AI chatbots. Google Bard cites data sources and provides up-to-date information, but its response time is sometimes slow. Chatsonic can generate AI images as part of the answer to your query.

What appear to be positives to you may be negatives to another user, and vice versa. The best tool for your business is unique to you—conduct your own research to fully understand the chatbot market, identify your overall AI goals, and shop for a chatbot tool that offers features and capabilities that meet your requirements.

How We Evaluated the Best Generative AI Chatbots

We evaluated today’s leading AI chatbots with a rubric that balanced factors like cost, feature set, quality of output, and support.

Feature Set | 30 percent

Features carry the most weight in our evaluation process. We evaluated various capabilities offered by each generative AI software, including multi-language support, the ability to accept spoken word input, the programmability of the solution, the kind of users it is built for, and customization options.

Ease of Use | 25 percent

We assessed each generative AI software’s user interface and overall user experience. This included evaluating the ease of installation, setup process, and navigation within the platform. A well-designed and intuitive interface with clear documentation, support materials, and the AI chatbot response time contributed to a higher score in this category.

Cost | 20 percent

We reviewed each AI chatbot pricing model and available plans, plus the availability of a free trial to test out the platform. Our research found that some platforms are completely free, while some offer both free and paid plans—a tool like Google Bard gives you access to all its features for free, ChatGPT has a free plan with access to GPT 3.5 capabilities, while GPT 4 requires a monthly subscription. On the other hand, Jasper is a paid chatbot offering a seven-day free trial.

Support | 15 percent

Our analysis also considered the level of support provided by the AI software provider. We assessed the availability and responsiveness of customer support, including customer service hours, email support, live chat support and knowledge base.

Quality of Output | 10 percent

To determine the output quality generated by the AI chatbot software, we analyzed the accuracy of responses, coherence in conversation flow, and ability to understand and respond appropriately to user inputs. We selected our top solutions based on their ability to produce high-quality and contextually relevant responses consistently.

AI Chatbots: Frequently Asked Questions (FAQs)

Below, we provide answers to the most commonly asked questions about AI chatbots.

What Features Should Businesses Look for in AI Chatbots?

Key features to look for in AI chatbots include NLP capabilities, contextual understanding, multi-language support, pre-trained knowledge and conversation flow management. It is also important to look for a tool with a high accuracy rating, even if the questions asked are complex or open-ended.

Why are AI Chatbots Important for Businesses?

AI chatbots are important to businesses because they enhance customer experience and provide various operational benefits, such as improved customer experience, personalized experiences, cost reduction, and increased productivity. Most important: they provide customer service at a far lower cost.

How Can AI Chatbots Enhance Customer Support and Engagement?

AI chatbots can boost customer support by providing 24/7 support, answering common questions, and personalizing interaction based on customer preferences. (For instance, multilingual AI chatbots can communicate in multiple languages, enabling businesses to assist customers from different regions).

What are Traditional Chatbot Builders?

Traditional chatbot builders are tools that help you build conventional rule-based chatbots that stick to a prewritten script. Compared to AI chatbots, they lack natural language processing abilities and feel far less human-like.

Bottom Line: Today’s Top AI Chatbots Take Highly Varied Approaches

Determining the “best” generative AI chatbot software can be subjective, as it largely depends on a business’s specific needs and objectives. Chatbot software is enormously varied and continuously evolving,  and new chatbot entrants may offer innovative features and improvements over existing solutions. The best chatbot for your business will vary based on factors such as industry, use case, budget, desired features, and your own experience with AI. There is no “one size fits all” chatbot solution.

For a full portrait of today’s top AI companies, read our guide: 150+ Top AI Companies

The post 21 Best Generative AI Chatbots in 2024 appeared first on eWEEK.

We tested the top AI writing software to see how it compares on features, pricing, and relative strengths and weaknesses, and to see how well it meets a variety of common use cases. Here are our picks for the best AI writing tools in 2024:

• Copy.ai: Best for Beating Writer’s Block
• Rytr: Best for Copywriters
• Quillbot: Best for Paraphrasing
• Frase.io: Best for SEO Teams and Content Managers
• Anyword: Best for Copywriting Performance Analysis
• Grammarly: Best for Grammatical and Punctuation Error Detection
• Hemingway Editor: Best for Content Readability Measurement
• Writesonic: Best for Blog Content Writing
• AI Writer: Best for High-Output Bloggers
• ContentScale.ai: Best for Creating Long-Form Articles

Comparing the Top AI Writing Tools

The following chart shows at-a-glance how each of the AI writing tools compare on key features, pricing, and availability of a free version.

Copy.ai

Best for Beating Writer’s Block

Copy.ai is an artificial intelligence writing tool designed to help marketers, business owners, and copywriters create various forms of content, including website copy, sales landing pages, email, and social media and blog posts. A boon to content marketers, Copy.ai can automatically conduct SEO research and produce content briefs for writers, streamlining the production process and giving writers guidance.

Another distinctive feature is the thought leadership tool, which automatically turns raw transcripts from interviews with experts into a variety of content assets, including blog posts, social media posts, and newsletters. This dramatically reduces the time it takes to manage content repurposing. The AI writing tool also lets you easily generate copy that aligns with your organization’s persona.

Copy.ai’s in-platform AI chatbot acts as a writing assistant to help beat writer’s block by aiding with brainstorming. For example, I asked it to give me 10 Instagram post ideas for fashion week—it delivered 10 useable ideas I could use as the basis for my social posts. These features enable your team to create and distribute more high-quality content at a lower cost than before.

Pros and Cons

Pricing

• Free: Up to 2,000 words per month
• Starter: $49 per month or $36 per month billed annually for one seat, unlimited words
• Advanced: $249 per month or $186 per month billed annually for up to five seats
• Enterprise: Call for quote

Key Features

• More than 90 copywriting tools included
• Allows you to save and reuse key information via its Infobase feature
• Streamlines SEO content research and brief creation
• Automates content repurposing
• Chat feature enables sales and marketing teams to interact more naturally with AI
• Easy content brainstorming
• Automated sales email writing
• Supports 25 languages

For an in-depth guide to the best AI detection tools, read our guide: AI Detector Tools

Rytr

Best for Copywriters

Rytr is an AI-powered writing tool capable of producing copywriting content on various topics. It’s one of the best AI writing tools for commercial copywriting jobs, where copywriters can use it to automate the creation of post and caption ideas, paragraph content, SEO meta titles, emails, call to actions, replies, and other less complex copywriting assets.

The platform also supports more than 40 other use cases, including generating blog ideas and creating job descriptions. In addition, paid users can create their own use cases by training Rytr for their specific needs.

I tested Rytr out for copywriting and asked it to write me a call-to-action for “A knee pad that protects middle-aged gardeners from hurting themselves.” In response to my prompt, it provided the following two variants:

• “Safeguard your knees, garden with ease.”
• “Safeguard your knees, garden in comfort.”

When I changed the tone from “convincing” to “humorous,” it generated two more options that were not useable out-of-the-box but were still useful for ideation:

• “Kneel with confidence, gardenlords!”
• “Unleash your inner knee-jerk green thumb!”

Overall, Rytr its a useful AI writing tool for copywriters who want to streamline their writing process and come up with more ideas for a variety of content types.

Pros and Cons

Pricing

• Free: Up to 10,000 characters per month
• Saver: $9 per month, or $90 per year; up to 100,000 characters per month
• Unlimited: $29 per month, or $290 per year

Key Features

• Content outline and brief generator
• Chrome extension for improving your writing
• Business idea generator
• Supports copywriting frameworks like AIDA (Attention–Interest–Desire–Action) and PAS (Problem–Agitation–Solution)
• Serves as keyword extractor and generator
• Creates SEO meta descriptions
• Writes calls-to-action

To see top AI software in several categories, see our guide: Best Artificial Intelligence Software

QuillBot

Best for Paraphrasing

QuillBot is an AI-powered writing assistant that, unlike most AI writing tools, focuses on helping you paraphrase and summarize texts. This makes it great for content marketers who often have to write repetitive copy with slight variations across their different content assets or even within the same blog post. For example, instead of writing “automate your administrative accounting tasks” five times, they could use QuillBot to spin that into five different variations.

It also functions as a citation generation tool, making it somewhat useful for academics—but it may not be the best tool for writing essays and research papers, as its output doesn’t consistently pass AI detection tools.

One of QuillBot’s standout features is the ability to choose from nine modes of paraphrased output. You can select from natural, academic, simple, creative, shortened, expanded, and more. As an example, when I prompted it with “The shift to agriculture took thousands of years” in academic mode, the output read, “The transition to an agrarian society spanned several millennia.”

Overall, I found the tool helpful for the outwardly simple but cognitively-taxing task of coming up with new ways to express your ideas in writing.

Pros and Cons

Pricing

• Free: Limited capability
• Premium: $19.95 per month, $13.33 per month billed semi-annually, and $8.33 per month billed annually
• Team: Varies depending on the number of users

Key Features

• Offers Chrome and Word extensions for grammar checking
• Can create source citations in various styles, including APA, MLA, and Chicago
• Nine paraphrasing modes
• Language translator capability

See the very best of today’s generative AI tools: Top Generative AI Apps and Tools

Frase.io

Best for SEO Teams and Content Managers

Frase.io is an AI writing tool designed to help you generate content, provide suggestions for better writing, and optimize articles for SEO. SEO teams and content managers use its templates and outline builder to automatically produce article structures that align with the intent of the searcher, and as a result, increase the chances that the article will rank highly in search engine results pages (SERPs).

Frase’s keyword optimization feature will identify important keywords while you write, make suggestions about how frequently to use them, and track how often they are used in the copy. In addition to keyword tips, it also tells you the ideal number of headings, words, links, and images your articles should have to outrank the competition.

Many of the SEO managers I’ve worked with have used Frase, and I’ve found it especially helpful for optimizing articles for SEO. Watching the SEO “topic score” go up as I make edits is motivating and lets me know I’m on the right track.

Pros and Cons

Pricing

• Trial: $1 for five days
• Solo: $15 per user, per month, or $144 billed annually
• Basic: $45 per user, per month, or $456 billed annually
• Team: $115 per month, or $97 billed annually, for three users; $25 per month for each additional seat

Frase also offers a Pro Add-On that allows unlimited AI content for $35 per month, but does not offer a free plan.

Key Features

• Automated content briefs and outlines
• Content SEO topic scoring capability
• AI written SEO-optimized copy
• Suggestions on keyword optimization
• Google Search Console (GSC) integration

For a detailed look at a leading AI tool, see our guide: ChatGPT: Understanding the ChatGPT ChatBot

Anyword

Best for Copywriting Performance Analysis

Anyword is an AI writing tool that uses machine learning algorithms to generate content and analyze the performance of your copy across various channels. What distinguishes the tool is its Copy Intelligence functionality, which analyzes all of your previously published content to determine which messaging works best on your website, ads, socials, and email channels while clueing you into opportunities to improve your copy.

Its Target Audience feature lets copywriters and marketers define their ideal readers down to their key problems and desires. The AI writing tool will then take this into account when creating and analyzing content.

I found Anyword’s templates extremely helpful for prompting the AI writer to create content that fit my needs. In addition, its self-guided wizards walked me through the information I needed to provide the tool for it to write a blog post or ad campaign for my needs.

Pros and Cons

Pricing

• Starter: $49 per user, per month, or $468 billed annually
• Data Driven: $99 per month, or $948 billed annually for three users
• Business: $499 per month, or $5,988 billed annually for three users
• Enterprise: Custom pricing

Key Features

• Supports up to 30 languages
• Google Chrome extension available
• More than 100 performance-driven templates
• Integrates with Grammarly
• Analyzes copy performance
• Identifies ways to enhance your content
• Adheres to your brand guidelines and target audience data

Grammarly

Best for Grammatical and Punctuation Error Detection

Grammarly is a popular AI writing app that helps you improve your writing by checking for grammatical and spelling mistakes and offering suggestions for enhancing clarity, tone, conciseness, and style. It can be used in a wide range of contexts, including writing emails, reports, essays, or social media posts.

Grammarly can be used as a browser extension, a desktop application, or a mobile app. It’s free to use with limited features, or is available with additional functionalities as a premium subscription.

I’ve found Grammarly’s free version to be extremely useful as an AI editing tool. When I use it to run a final grammar and spelling check on a finished article, it inevitably catches mistakes and offers solutions to fix them. I also use it when writing emails to get the tone right. For example, when emailing a new client, I like to make sure the tone is confident and upbeat—Grammarly’s tone detector helps me achieve that goal.

Pros and Cons

Pricing

• Free: Free version lacks some high-end features
• Premium: $30 per month, or $144 billed annually
• Business: $25 per month, or $300 billed annually

Key Features

• Real-time grammar correction
• Generative AI assistance
• Plagiarism checker
• Advanced clarity suggestions
• Writing tone detector
• Checks grammar, spelling, and punctuation

Hemingway Editor

Best for Content Readability Measurement

Named after a writer known for his concise and simple prose, Hemingway Editor is a writing tool that helps you enhance the clarity, grammar, and readability of your written work. It analyzes text and provides various readability suggestions while highlighting lengthy, complex sentences, excessive adverbs, passive voice, and hard-to-read phrases.

It also assigns a readability score based on the grade level required to understand the text. If the score is too high, content writers can tweak the highlighted sentences to lower the grade level. It is available both as a web-based application and as a desktop app.

I’ve used Hemingway in various capacities and I find that it does its main job of measuring content readability extremely well. Its passive voice detector is my favorite part of the tool.

That said, one of the risks of using an AI editing tool like Hemingway is that, if you follow its suggestions without thinking, you may edit all the rhythm, flow, and personality out of your writing, leaving you with text that’s plain, lifeless, and stilted and suited for a grade level well below your target. Overall, though, I’ve found it a useful tool for making sure blog content is clear and easy to understand while streamlining the editing process.

Pros and Cons

Pricing

The platform is free to use.

Key Features

• Improves writing clarity and conciseness
• Provides a readability score
• Offers alternative word suggestions
• Detects passive voice and excessive adverbs
• Highlights hard-to-read sentences

To see a comparison between two leading AI tools, read our guide: ChatGPT vs. Google Bard

Writesonic

Best for Blog Content Writing

Writesonic uses artificial intelligence technology, specifically natural language processing (NLP), to provide content generation services. It’s one of the best AI writing tools for creating full blog posts.

Writesonic’s AI can generate text based on prompts and user input. In the case of creating a blog post, the wizard will ask you to input information such as article length, keywords, number of headings, topic, and references. Once you’ve approved of the outline, it’ll generate a blog post following these instructions as well as SEO optimization best practices.

While it can be a helpful resource for automated content creation, the quality of generated content may vary, and human editing is often required to ensure accuracy and coherence.

Pros and Cons

Pricing

• Free: 25 generations per month
• Standard: $948 billed annually
• Professional: $2,388 billed annually
• Advanced: $4,788 billed annually

Key Features

• Supports GPT 3.5 and GPT 4
• AI article and blog writer
• Article rewriter
• Sentence expander
• Text summarizer
• Story generator
• Landing page generator

AI Writer

Best for High-Output Bloggers

AI Writer is designed to generate full-length articles in minutes, making it great for high-output bloggers, affiliate marketers, and other people who need articles fast. The platform lets you tailor the AI’s writing to your specific needs by selecting from a long list of recommended keywords for your topic or by manually inputting your chosen keywords. It also suggests sub-topics for your article and helps you structure your content with headings. The tool even cites its sources, displaying journalistic responsibility.

Significantly, it helps you choose topics about which to write. While exploring the platform, I found its topic generator helpful for coming up with article topics using a seed keyword—after prompting with “cold calling,” for example, I received a long list of article keywords and their associated traffic. I then selected Research and Write, a one-click article feature for Cold Calling Leads, and within minutes, I had a basis for a new 600-word article on the topic.

Compared to other AI writing tools, AI Writer’s blog content creation was incredibly quick. However, a note on quality—although AI Writer’s articles are typically well-written, SEO-friendly, and factually correct, they could benefit from a writer’s touch. When I took another pass to add personality, anecdotes, actionable insights, and personal experiences to the copy, it became more appealing to readers and search engines.

Pros and Cons

Pricing

• Basic: $29 per user, per month
• Standard: $49 per month for three users
• Power: $375 per month for 10 users

Key Features

• AI text generator
• SEO editor
• One-click article writer
• Topic generator based on seed keywords (with traffic estimate)
• Can publish to WordPress
• Email composer
• Text rewording capability

ContentatScale.ai

Best for Creating Long-Form Articles

Those looking for an AI writing tool to automatically create long-form articles (over 2,000 words) may find ContentatScale features suitable. After plugging in your topic and further context, it will automatically generate body text, headers, subheaders, a title, bulleted lists, a call to action, and other content elements necessary for effective long-form SEO articles. Not only will it write the blog post—it will also help you come up with ideas, outlines, and relevant keywords in a fraction of the time it would take you to do it manually.

The platform claims to pass AI detection tests, indicating that its generated content mimics human writing and is not easily distinguishable from human-written content. ContentatScale also offers an AI detector solution that ranks as one of best reviewed AI detector tools. Overall, it can be helpful for streamlining the long-form content writing process.

Pros and Cons

Pricing

• Trial: Seven days; $39.99
• Solo: $250 monthly for eight posts
• Starter: $500 per month for 20 posts
• Scaling: $1,000 per month for 50 posts, or $1,500 per month for 100 posts

Key Features

• Keyword, YouTube, podcast, file, blog outputs
• Unique Voice AI Training options
• AI detection capability
• Natural language processing analysis

How to Choose the Best AI Writing Software for Your Business

Choosing the best AI writing tool for your business depends on your AI writing needs and your budget. Our “best-for” use cases are a good starting point to help you decide. In addition, here’s a little more information to help you narrow down your choice:

• Copy.ai and Rytr are best for copywriters and social media managers looking to create short-form content and marketing copy.
• AI Writer, Anyword, and Writersonic are solid options for those looking to create blog posts at scale.
• Frase can help you optimize your content for SEO.
• Grammarly and Hemingway are great options for checking grammar, spelling, and style in your AI-generated content.
• QuillBot and Writesonic may be the best for paraphrasing.

Other factors to consider when choosing the best AI writing tools for your business include features, content quality, user interface, and customization options. Keep in mind that it doesn’t have to be an either-or choice—these tools can be used together for better quality content. For example, you can use QuillBot to paraphrase Anyword’s AI-generated text, Grammarly to correct spelling and punctuation errors, and the Hemmingway App to improve readability.

How We Evaluated the Best AI Writing Tools

We weighed the best tools across five categories. Each category has subcategories that helped us evaluate and compare the AI writing tools.

Feature Set | 30 percent

We assessed the writing capabilities of each tool, including its grammar and spelling correction, sentence rephrasing, and content generation capabilities. We looked for tools that provided accurate and high-quality writing suggestions.

Quality of Output | 25 percent

We evaluated the accuracy and coherence of the generated content produced by each AI writing tool. Tools that could generate clear, well-structured, and error-free content received higher scores.

Cost | 20 percent

We examined the different pricing plans offered by each AI writing tool. This included evaluating the cost of the tool on a monthly or annual basis, as well as any additional fees or hidden costs. We compared each tool’s cost to its value, looking for tools that offer a high level of functionality for a reasonable price.

Support | 15 percent

We assessed the availability and responsiveness of customer support channels, such as email, live chat, or phone support. Prompt and helpful customer support is essential for users who may encounter issues or need assistance with the tool. We also considered the availability of resources and documentation, such as user guides, tutorials, or knowledge bases.

Ease of Use | 10 percent

We looked for tools that have an intuitive and user-friendly interface, allowing users to navigate and utilize the tool’s features easily.

FAQs (Frequently Asked Questions)

Is there a free AI writing tool?

There are plenty of free AI writing tools for content creation, editing, and paraphrasing, including some of those reviewed in this guide. While many of the AI writing tools’ advanced features are restricted to paid users, some writers will find the feature sets in the free plans sufficient for their needs.

How can companies benefit from AI writing tools?

Companies can benefit from AI writing tools by using them to streamline the content creation and editing process across various marketing channels, from social media to SEO blog content. These tools can automatically generate content, help with brainstorming, and suggest edits to improve your copy. Overall, AI writing tools help businesses improve efficiency and increase content marketing output and quality.

Will the content created by AI writing tools seem robotic?

The output of AI writing tools will not have the compelling quality of writing created by human writers. After all, AI writing tools are merely generating text—they’re not thinking, considering personal anecdotes, or making unique connections between ideas. Ultimately, the output of AI writing tools need a human touch to create quality writing.

Bottom Line: Top AI Writing Tools Improve Efficiency

This guide highlights our recommendations for the best AI writing tools to help with your writing needs, but they may not fit every use case perfectly. AI is a tool that can help with idea and content generation and quality improvement, but the best results still require a skilled human touch. When used properly, these tools can boost efficiency and are likely to continue driving changes in any market sector that relies on written content.

Read next: for more assistance with your projects, read our analysis of the best AI chatbots and the top conversational AI tools.

The post 10 Best AI Writing Tools (2024): Enhance Your Writing with AI Magic appeared first on eWEEK.

5 Benefits of Using AI Personalization for Marketing

Personalizing your marketing campaigns can give your content a human touch and boost revenue, letting you deliver tailored experiences to better engage individual customers, make data-driven campaign decisions, and increase sales.

Highly Targeted Ads

Targeted advertising lets you reach the right audience with the right message at the right time. Customer data plays an important role in personalizing ad experiences. AI algorithms can analyze vast amounts of data to identify patterns and preferences. Unlike traditional advertising, AI helps brands enhance ad targeting and segment audiences based on demographics, interests, buying histories, and more. With AI, marketers can launch hyper-targeted advertising campaigns that resonate with individual consumers.

Engaging and Relevant Customer Experience

While AI solutions don’t replace human support agents, they optimize workflows and deliver customized content to customers. Businesses can use AI technologies such as natural language processing (NLP), machine learning, and sentiment analysis to understand individual preferences and behavior across various touchpoints. Marketers can identify patterns and factors used to build more valuable relationships, so they can tailor recommendations for products and services or deliver personalized support.

Increased Sales and Conversion Rates

AI can analyze customer preferences, purchase histories, and browsing behaviors to help you customize offers and discounts for individual customers. With AI, your business can implement statistical data modeling and machine learning techniques to predict buying patterns, sales opportunities, and market trends. Understanding customer needs better enables brands to make products more appealing to customers and can significantly increase the likelihood of conversion.

Enhanced Customer Loyalty

Personalization helps companies develop comprehensive and customized profiles of customers to better understand how to serve and retain them. Businesses can use them to tailor loyalty programs and relevant rewards. AI can also predict future purchases or the likely churn rate, which refers to the percentage of subscribers who discontinue subscribing to a service or product. AI also automates campaigns, so personalized content can reach customers at the right time via the right marketing channel.

Optimized Marketing Efforts

AI algorithms can consistently monitor and analyze campaign performance, helping marketers adjust their strategies in real time to maximize results. AI generates data-driven recommendations so businesses can optimize their resources and enhance campaigns for specific marketing channels, increase brand awareness, and engage with customers effectively. AI can also predict future customer behavior and preferences, letting you know which products, services, or content you should offer over a certain period.

Practical Applications of AI-Based Personalization in Marketing

For marketers, AI is a game-changer. As we’ve shown, it can analyze vast amounts of customer data to create targeted campaigns. But according to Babak Hodjat, CTO of technology solutions provider Cognizant, AI’s real power in marketing comes from orchestrating it alongside your business data to help make decisions that drive your key performance indicators. Your business has a range of options for how it might best implement AI-based personalization.

Watch eWeek’s interview with Cognizant CTO Babak Hodjat to hear more of his insights about the power of AI to reshape marketing.

Personalized Emails and Messaging

AI email personalization uses AI algorithms to customize email content for individual customers, which can significantly improve open rates, click-through rates, and conversions. According to HubSpot’s 2023 State of Generative AI Report, around 95 percent of marketers who use generative AI for email creation find the technology effective—and 54 percent rate it as very effective. Email marketing platforms analyze customer data, including past purchases, browsing history, demographics, and social media data, to send targeted emails with personalized product recommendations, offers, and content.

Tailored Product Recommendations

An AI-based product recommendation engine can analyze vast amounts of customer data to suggest products that align with individuals’ interests and preferences. By generating new data points from learned patterns, AI can recommend products disseminated on websites, apps, and by email to enhance the customer experience, increase sales, or improve retention.

Dynamic Website Content

Machine learning algorithms analyze huge amounts of data to understand a consumer’s behavior and preferences. With this data, AI can personalize website content and display product recommendations, customized banners, and relevant call-to-actions, leading to a more engaging experience.

Predictive Analytics and Forecasting

Using AI for predictive analytics is more efficient than doing it manually because you can quickly collect, organize, and analyze data from multiple sources. Businesses use AI-powered predictive analytics models to forecast future sales volumes, trends, purchase likelihood, churn risk, and more. You can use the patterns and correlations in past sales data to launch targeted campaigns to encourage purchases and retain customers.

Language and Sentiment Analysis

AI sentiment analysis employs AI and deep learning techniques to determine the overall sentiment, opinion, or emotional tone behind textual data. AI-powered sentiment analysis tools can analyze customer feedback, social media posts, and reviews to understand sentiment and identify areas for improvement, so businesses can address concerns and improve their products or services.

Assistive Search Features

AI-powered search engines play an important role in enhancing the user experience, using advanced algorithms to analyze user queries and provide personalized search results based on user history, preferences, and context. This helps users find relevant information more quickly and accurately.

Challenges and Considerations for Implementing AI Personalization

While AI personalization provides numerous benefits for marketers and businesses, there are also several challenges and considerations—including costs, ethical issues, and data privacy and security concerns—that you need to be aware of before implementation.

Data Privacy and Security Concerns

AI personalization relies primarily on collecting and analyzing customer data, which can raise concerns about data privacy and security. Businesses need to ensure that customer data is collected and used appropriately in compliance with relevant regulations. Because AI technology isn’t confined to one state or jurisdiction, it can be challenging to create and maintain standard privacy practices and governance. Common data privacy and security concerns in AI personalization include the following:

• Data Collection and Consent: AI personalization relies heavily on collecting vast amounts of personal data, and it’s necessary to inform customers about what data is being collected and how it’s being used.
• Data Security and Breaches: Securing vast amounts of data increases the risks of data breaches and cyberattacks, making it essential to implement robust security measures.
• Data Bias and Discrimination: AI algorithms can cause biases if they learn from data that is unbalanced or reflects discrimination; AI models must be trained on diverse and representative data to avoid discrimination against certain groups.
• Filter Bubbles: One of the most common implications of AI-driven personalization is the creation of filter bubbles caused by excessive personalization, which happens when users are only exposed to information that aligns with existing beliefs, reinforcing existing biases.

Implementation Costs and Resources

AI implementation for marketing personalization requires a significant investment of financial and technical resources. However, the cost can vary depending on the complexity of the AI solution, business size, and marketing personalization goals. Common costs involved in implementing AI personalization include the following:

• Software and Platform: Licensing fees for solutions can range from hundreds to thousands of dollars per month depending on features, customization, and users, and some platforms offer pay-as-you-go pricing models or annual subscriptions; determine which pricing structure fits your budget.
• Infrastructure and Hardware: For customized AI solutions, consider the cost of servers, storage, and networking infrastructure; for more cost-effective solutions, consider cloud-based AI platforms to avoid the additional cost of on-premises infrastructure.
• Data Preparation: Before you can use customer data you need to collect, clean, duplicate, and format it. This process can be time-consuming and expensive if you need to deal with a large amount of data.
• Technical Expertise: Creating a team of experts—including data scientists, machine learning engineers, and AI specialists—can be expensive, and you’ll also need to train your marketing team to understand and use personalization platforms, which can incur additional costs.

Ethical Considerations

While AI personalization can enhance marketing strategies, it also poses several ethical concerns that businesses should carefully consider. Here are the most common:

• Transparency and Consent: Companies must be transparent about how they use AI solutions for personalization and should obtain explicit consent from users; customers should be fully aware of how their data is being used and should have control over what they want to share.
• Data Minimization: Businesses or researchers should collect only the necessary data for personalization and use it solely for the intended purpose; avoid gathering excessive or irrelevant information that might cause privacy concerns.
• Avoiding Manipulation and Coercion: Respect users’ autonomy and avoid manipulating them; manipulation and coercion might include restricting the available and acceptable options for users or offering material incentives.
• Bias Mitigation: This involves employing various techniques and methodologies to reduce the impact of biased data and algorithms; companies should also regularly audit and monitor algorithms to detect and correct biases.

Best Practices for Effective AI Personalization Marketing

Using the right AI personalization tools can improve marketing effectiveness. However, businesses should implement the solution strategically and ethically to optimize the investment they make.

Identify Audience and Goals

Before implementing your AI personalization strategy, clearly define your goals and identify your target audience. Be as detailed as possible in determining the outcomes you want to achieve, the resources you can invest, and the customer segment you need to reach.

Collect Data Thoroughly and Ethically

Ensure that your data collection practices are ethical and adhere to privacy regulations. Integrate data from other sources, like CRM systems, social media tools, and analytics platforms, to get a more comprehensive view of your customers.

Use the Right Tools

Invest in the right AI solutions or marketing tools to fit your goals, needs, and budget. Also consider the solution’s usability, scalability, built-in AI features, and customization options.

Monitor and Refine

Continuously test different strategies and monitor your results, so you can refine your marketing campaign based on data-driven insights.

Add a Human Touch

Incorporate human touch into your personalization strategy—for example, use AI to segment customers quickly but let a human customer support representative follow up on questions or concerns.

Remain Compliant

Comply with data privacy regulations such as the European Union’s General Data Protection Regulation (GDPR) and AI Act and the California Consumer Privacy Act (CCPA).

5 Essential Tools for AI Personalization Marketing

A wide range of tools are available to help marketers analyze customer data and use AI to personalize campaigns. They can generally be sorted into five types: customer data platforms, machine learning algorithms, marketing automation tools, personalization engines, and analytics and reporting tools.

Customer Data Platforms

Customer data platforms (CDPs) centralize customer data from various sources to create a unified customer profile. They allow businesses to pull customer data from any channel, system, or data stream and combine it into an accessible database to help companies create personalized customer experiences.

For example, Salesforce Data Cloud is a leading CDP deeply embedded in Salesforce’s Einstein 1 platform that combines CRM, AI, data, and transparency. This solution allows users to integrate an external data lake or warehouse directly into your CRM platform and offers features such as real-time data unification, AI-powered insights, and easy integration with Salesforce Marketing Cloud.

Machine Learning Algorithms

Machine learning algorithms are the backbone of AI personalization, as they allow users to view trends in customer behavior and business trends. Machine learning tools enable marketers to easily identify patterns, predict behaviors, and segment their customer base.

For example, Alteryx provides a powerful platform for users to employ machine learning models to reduce bottlenecks and scale data science processes. This ML solution has easy-to-use machine learning models, making it easier for the user community to share knowledge and collaborate. Alteryx is also flexible, providing users with a robust solution for building and deploying custom machine learning models specifically for marketing use cases.

Marketing Automation Tools

AI marketing tools streamline marketing tasks and campaigns to let marketers focus on more creative endeavors and strategic planning. Integrating AI into marketing efforts helps you automate repetitive tasks, improve targeting and segmentation, enhance personalization, and predict trends.

For example, Jasper AI helps marketers generate personalized content for email marketing, social media, and customer service. Marketers can ideate and execute campaigns, communicate better with their teams, and optimize content with Jasper AI’s tools for automation, copywriting, analytics, and more.

Personalization Engines

Personalization engines help marketers deliver and measure the optimum experience for customers by using AI algorithms to personalize content based on past interactions, current engagement, and predicted intent.

For example, MarketMuse is an AI-powered content strategy platform that helps marketers create personalized content relevant to their target audiences. Marketing teams can back their content planning, creation, and optimization with data-driven insights.

Analytics and Reporting Tools

AI-powered analytics and reporting tools make it easier for marketers to deliver personalized experiences by analyzing marketing campaigns, tracking personalization efforts, and determining opportunities for improvement. The right analytics and reporting tools empower businesses to make informed and strategic decisions for their marketing efforts and campaigns.

Microsoft Power BI is a robust AI-powered analytics and reporting tool specifically designed for business intelligence. This platform allows marketers to collect, visualize, and analyze marketing data to measure the impact of their personalized marketing solutions almost in real-time.

3 Recommended Coursera Courses for Learning AI Personalization Marketing

A number of online education providers offer training on all manner of artificial intelligence technologies. We recommend three in particular, provided by Meta, the University of Virginia, and the University of Colorado.

Artificial Intelligence in Marketing, University of Virginia

Developed at the Darden School of Business, this course delves into the fundamentals of AI and its application in marketing. You will learn about the three important factors that enable AI in marketing strategies: algorithms, networks, and data. You can explore how to harness data-driven AI solutions for improving customer experiences and see real-world examples of successful companies shaping their respective industries using AI. No prior experience is needed to participate in the course, making it an ideal introductory course for beginners.

Meta Social Media Marketing Professional Certificate, Meta

This professional certificate course helps prepare you for a career in social media marketing. You can receive professional-level training from Meta for using Meta Ads Manager to launch Facebook and Instagram ad campaigns and interpret results from these campaigns. After completing the six-course series, you can demonstrate proficiency in portfolio-ready projects and earn an employer-recognized certificate from Meta. Beginners who want to qualify for in-demand job titles such as social media manager, social media specialist, and social media coordinator will find this professional certification beneficial for their careers.

Machine Learning for Marketers, University of Colorado

This course helps you apply machine learning techniques to marketing and strategic decision-making, and you’ll learn to analyze and forecast customer behaviors using advanced algorithms. As part of the Data Science for Marketing Specialization, enrollment in this course also enrolls you in this specialization. Upon completion, you’ll gain skills such as campaign analysis and testing, predictive analytics in marketing, machine learning, personalized marketing strategies, and more. This course is offered at an intermediate level, so experience in marketing and a basic understanding of data analytics are recommended.

Bottom Line: The Future of AI Personalization Marketing

AI personalization is transforming how marketers and businesses connect with their customers, offering tailored experiences that boost conversions and drive growth. AI personalization in marketing entails various challenges and ethical considerations, necessitating an in-depth understanding of how to balance the use of AI with protecting customer privacy. The right AI tools and strategies will not only help businesses harness the full potential of AI in campaigns but also create a future where marketing is truly personalized for every individual.

Read our list of the top AI companies in 2024 and the leading AI startups to learn more about the businesses driving AI forward in marketing and other industries.

The post AI Personalization Marketing: The Future of Customized Advertising appeared first on eWEEK.

Top 5 Benefits Of Using AI In Content Marketing

Utilizing AI in content marketing provides a range of benefits that change the way you create, distribute, and deliver your content.

Boosting Content Marketing ROI

AI marketing tools help campaigns achieve superior quality, boosting the return on investment. Through advanced data analysis, it helps you understand which strategies yield the best results for better resource allocation. AI solutions also automate content distribution to give you full confidence that your targeted message will reach your intended audience at the most opportune moment.

Saving Time and Resources

AI tools can perform repetitive tasks such as keyword research, content scheduling, and performance monitoring to streamline your content marketing. By handling routine activities, it frees up valuable time to focus on the creative aspects of your work. AI can also help generate content ideas, draft articles, and create visuals, reducing the need for extensive human effort and cutting down on operational costs.

Improving Content Quality

You can use AI content recommendations to refine your writing and make sure it aligns with audience preferences. AI solutions can help you analyze which type of content will have the most impact with your target demographics, providing insights that guide you to produce relevant, accurate, and compelling content.

Ranking Higher In Search

AI algorithms can identify trending keywords, evaluate competitor strategies, and predict changes in search engine algorithms to optimize SEO content. With AI, you can also enhance the crawlability and indexability of your content by adjusting on-page elements like meta tags, headings, and alt text.

Making Your Content More Engaging and Consistent

AI analyzes user behavior and preferences, enabling you to tailor content that appeals to the individual tastes of your audience and increasing engagement. It helps maintain a consistent brand voice and messaging, even when content is produced at scale or by different team members. This uniformity contributes to building a stronger brand identity.

How To Use AI In Content Marketing: Top 5 Uses

There are many ways to use AI in content marketing, from brainstorming ideas to automating content-related processes.

Researching Content Ideas

AI excels at researching content ideas by analyzing vast amounts of data from social media, forums, and search trends. It helps you determine emerging topics, forecast what subjects will appeal to the audiences, and uncover gaps in existing content. It can also help you craft interesting and timely ideas that will help you connect with your target audience.

Creating Content

Natural language processing (NLP) and machine learning (ML) can support you in drafting high-quality articles, blog posts, and social media updates quickly and at scale, often indistinguishable from human-written text. By automating the writing process with AI content creation tools, you can compose a large volume of content, meeting the increasing demand for fresh material while freeing up human writers for more complex tasks.

Rewriting And Optimizing Your Content for SEO

Optimizing content for SEO by rewriting text to better align with search engine algorithms is another thing AI does well. It analyzes your current content’s performance, detects keyword opportunities, and offers necessary adjustments in structure, readability, and keyword density. You can make sure that your content includes the right mix of keywords, meta tags, and backlinks, increasing its visibility and ranking on search engine results pages.

Building A Content Marketing Strategy

You can develop a content marketing strategy with data-driven insights and recommendations from AI. By analyzing past performance, audience behavior, and market trends, AI solutions can suggest the most effective content types, distribution channels, and posting schedules. It can also predict future trends and audience needs, allowing you to plan proactive and responsive AI content strategies.

Common Challenges In AI Content Marketing And How To Overcome Them

Using AI for content marketing presents challenges that require preparation. Addressing these challenges will help you harness its full potential and maintain an effective and authentic strategy, while considering AI content ethics.

Ensuring Content Originality

AI-generated content can sometimes lack originality, producing repetitive material. This can diminish the uniqueness and value of your content, potentially harming your brand’s reputation and SEO performance. Use AI solutions with plagiarism detection features, and input diverse data during content generation. Combine AI capabilities with human creativity for unique perspectives, experiences, and originality.

Balancing Automation And Human Touch

Although AI can automate many aspects of content creation and marketing, over-reliance on this capability can make your content feel impersonal and mechanical. Achieve a balance by using AI to accelerate data analysis and idea creation, but use human input for final editing and adding a personal touch. Leveraging the strengths of both AI and human creativity will help ensure your content is both efficient and impactful.

Algorithm Bias

AI systems can inherit biases present in the data they are trained on, leading to biased content. Carefully select diverse data sets to train AI and conduct regular audits of AI outputs to find and correct biases. You can also implement ethical AI guidelines that can further help mitigate this issue.

Tips For Using AI In Content Marketing To Get the Best Results

It is essential to approach AI thoughtfully and strategically to get the most out of it for content marketing. Here are some tips to help you effectively use this powerful technology to your advantage:

• Maintain Human Oversight: Ensure that a human keeps an eye on the AI-enhanced content to maintain quality, authenticity, and relevance. By having a human monitor the output, you can catch any errors and ensure AI content accuracy.
• Integrate Personality Into AI Content: Add your brand’s unique personality into AI-generated content to make it more relatable. Use your brand’s voice, values, and style to develop content that strengthens your brand identity.
• Highlight First-Hand Experience and Expertise: Demonstrating your firsthand experience and expertise in your AI content establishes credibility and authority in your industry. By showcasing your knowledge, you can position yourself as a thought leader and differentiate your content from competitors.
• Structure Content To Maintain Traffic: By organizing your content into easily digestible sections through headings, bullet points, and visuals, you can improve readability, user experience, and traffic volumes. This engages readers and encourages them to explore more of your content.
• Use AI To Analyze Audience Behavior: Employ AI to understand your audience’s preferences, browsing habits, and engagement patterns so you can customize your content strategy to meet their needs effectively. As a result, you can deliver relevant content that interests your audience.

The Top 3 AI Content Creator Tools

There are several AI content creator tools on the market to help you fine tune your content and marketing strategies, including our top three recommendations: Jasper AI, Grammarly, and Writesonic.

Jasper AI

Jasper AI automates content marketing processes to save time and resources while maintaining quality, strengthening content marketing efforts. Its key features include AI content generation through NLP for blog posts, social media updates, and marketing copy. In addition, it suggests relevant keywords for better content visibility and ranking.

Jasper AI provides only limited customization options compared to other AI content marketing tools, but its intuitive interface and robust keyword suggestions make it an excellent choice if you want to improve your content marketing strategies.

Grammarly

Grammarly is an AI writing tool renowned for refining written content quality, which is needed to maintain credibility in content marketing. Its AI-powered assistance ensures error-free, clear, and compelling content, optimizing communication with the audience. Its grammar and spelling check features detect and correct errors and give suggestions to make your sentences clearer and easier to read. Grammarly also brings insights into tone and style to help you maintain a consistent brand voice and audience connection.

A downside of this AI tool is that it primarily focuses on language and grammar corrections and lacks in-depth content optimization features. But Grammarly’s precise error detection makes it an indispensable tool for producing polished and professional content.

Writesonic

Writesonic’s AI-driven capabilities facilitate creating different content types for a variety of content marketing strategies. It has content generation features through ML algorithms based on user inputs and preferences, and it provides templates for social media posts, product descriptions, and email campaigns. This AI content marketing software also offers SEO recommendations and headline analysis to elevate content engagement.

Writesonic doesn’t offer as many advanced features as some other AI writing tools on the market, but its versatile templates can equip your business in generating a wide range of engaging content.

Frequently Asked Questions (FAQs)

What Is The Future Of AI In Content Marketing?

The future of content marketing using AI is promising and transformative. The technology will continue to drive personalized content delivery, elevate content creation and curation, and optimize SEO and content. However, it will also raise ethical considerations such as transparency, bias, and data privacy. Striking a balance between leveraging AI’s capabilities and upholding ethical standards will be of utmost importance in building trust with your audiences.

Will AI Take Over Content Creators?

AI stands to complement the efforts of content creators rather than replacing them outright. While AI can handle specific tasks like text generation and data analysis, human creativity, intuition, and empathy are irreplaceable for crafting relatable narratives, comprehending audience intricacies, and staying abreast of shifting trends. Rather than displacing content creators, AI serves as a beneficial aid, streamlining workflows and increasing productivity.

Is There A Free AI Content Generator?

Yes. Among the many free AI content generators are the following:

• Squibler: This AI story writer helps you develop book chapters or screenplay scenes and assists with character creation and setting development.
• NeuralText: This AI platform facilitates content creation and SEO with features like live SERP analysis and a writing assistant.
• Copy.ai: This AI-powered writing tool uses ML to generate blog headlines, emails, and social media content.

Bottom Line: Advancing Strategies With AI In Content Marketing

AI enhances content marketing by facilitating personalized, efficient, and engaging content creation. You can use it for brainstorming ideas, writing SEO-friendly articles, and making sure your content is relevant and consistent. However, despite the benefits AI brings to the table, using this advanced technology has its challenges that require human intervention.

No matter how valuable AI is in content marketing, it is imperative to recognize that AI remains just that—a tool. Its primary function is to augment human capabilities, not replace them entirely. While AI can automate certain tasks, it’s ultimately the creativity and strategic thinking of humans that breathe life into content, making it impactful. By combining AI’s efficiency with human intuition, your content marketing strategies can thrive.

Read our article on the top 150 AI companies for 2024 and find out the front runners in the AI industry today.

The post AI for Content Marketing: Strategies, Tools, and Best Practices appeared first on eWEEK.

How to Create Prompts for AI Sales Prospecting

Understanding the foundational elements of AI prompts lets you maximize your use of AI in your sales process. AI prompts serve as the building blocks for engaging potential leads, ultimately leading to conversions, and mastering their creation and use takes deliberateness and practice.

A skillfully designed AI prompt translates your business goals into actionable tasks for your AI. Learning how to develop clear and effective prompts leads to better results from your AI tools. There are a number of key points to keep in mind when creating prompts for AI sales prospecting.

Be Clear and Concise

Ensure your prompt is straightforward and easy to understand, avoiding ambiguous language to make sure that the AI can quickly understand and act on your request without confusion.

• Bad Prompt: “Analyze sales data.”
• Good Prompt: “Analyze monthly sales data for the past year to identify seasonal trends.”

Specify the Context

Provide context to help the AI filter and find the most relevant information, making the results more accurate.

• Bad Prompt: “Find marketing managers.”
• Good Prompt: “List marketing managers who attended our 2024 digital marketing conference.”

Define Your Desired Outcome

Clearly state what you want to achieve with the prompt to get specific results, saving time and effort in the AI sales prospecting process.

• Bad Prompt: “Provide leads interested in cloud technology.”
• Good Prompt: “Identify 50 potential leads who are interested in cloud-based software solutions.”

Include Relevant Details

Include relevant details to refine the AI’s search and get results that are pertinent to your needs.

• Bad Prompt: “Find small business owners in retail.”
• Good Prompt: “Get contact details of small business owners in the retail sector interested in e-commerce platforms.”

Focus on a Single Task

Overloaded prompts can confuse the AI; concentrate on one task at a time for better efficiency and effectiveness.

• Bad Prompt: “Find IT managers and generate a list of potential cybersecurity clients.”
• Good Prompt: “Generate a list of IT managers looking for cybersecurity solutions.”

Set Parameters For Analysis

Define the parameters for the AI to focus on, narrowing down the search criteria and leading to more targeted insights.

• Bad Prompt: “Find companies interested in data analytics.”
• Good Prompt: “Identify companies with annual revenues over $10 million that are interested in data analytics.”

Indicate Your Preferred Output Format

Be specific on how you want the information to be presented, making it easier to integrate into your workflows.

• Bad Prompt: “Generate some information about countries and their GDPs.”
• Good Prompt: “Provide the top five countries by GDP in a table format.”

7 Ways To Use AI For Sales Prospecting

AI sales tools assist with a variety of sales prospecting tasks, from finding potential leads to predicting customer behavior. Relying on AI lets you optimize your time, focus on high-value activities, and grow conversion rates.

Automated Discovery and Research

AI tools can accelerate the process of identifying potential customers by scouring a variety of online sources, databases, and social media platforms for leads. This automation saves valuable time and ensures a comprehensive collection of relevant data. You can gather detailed profiles of prospects, uncovering insights that manual research might miss and laying a solid foundation for effective sales strategies.

Intelligent Targeting

AI algorithms can analyze vast amounts of data to pinpoint the most promising prospects. These algorithms consider demographics, past behaviors, and purchase history to find leads with the highest conversion potential. This intelligent targeting allows you to focus your sales efforts on prospects who are more likely to respond positively, boosting the effectiveness of your outreach.

Lead Scoring and Qualification

AI can refine lead-scoring by evaluating and ranking leads based on their likelihood to convert. By analyzing patterns and key data points, AI tools prioritize leads that exhibit behaviors and characteristics indicative of high-potential prospects. Through this targeted approach, you can spend time and resources on leads that are more likely to result in successful conversions, raising overall sales productivity.

Social Media Monitoring

You can monitor social media platforms for mentions of your brand, industry keywords, and competitor activities with AI. Identifying these mentions brings valuable insights into your potential prospects’ interests and needs. Additionally, integrating AI into your CRM lets you engage with prospects at the right moment with the most relevant information, increasing your chances of building meaningful connections.

Personalized Content Creation

AI can analyze your prospects’ online behavior, social media activity, and other digital footprints, guiding you in crafting highly personalized outreach strategies. With these insights, AI can generate tailored, compelling messages that resonate with individual prospects. Personalized content in the form of emails, social media posts, and other communications drives engagement and fosters stronger relationships with potential customers.

Customer Behavior Prediction

AI-powered predictive analytics equips you to anticipate future customer actions by examining historical data, trends, and patterns. As a result, you can make informed decisions and proactively address customer needs. By understanding and predicting customer behavior, you can tailor your sales strategies to meet evolving demands, driving higher conversion rates and customer satisfaction.

Sales Forecasting

You can use AI to analyze historical sales data and forecast future sales trends with greater precision, enabling you to strategize more effectively. This forward-looking approach will fine-tune your resource allocation and set realistic targets that align with anticipated market conditions for sustained growth and success.

5 Benefits of Using AI For Sales Prospecting

Incorporating AI in sales prospecting elevates how your business approaches lead generation and customer engagement. By using AI’s data analysis, machine learning (ML), and automation capabilities, you can gain a wide range of benefits and grow revenue. Here are five of the most common benefits:

• Saving Time and Increasing Efficiency: AI can automate tedious tasks like data collection and lead searching, giving you more time to focus on captivating potential customers and successfully closing deals.
• Reducing Costs: By automating data analysis and lead qualification, AI can lower the costs associated with these processes, letting you allocate more resources to activities that directly drive sales and growth.
• Prioritizing the Best Leads: Scoring and ranking leads become simpler, letting you concentrate on the most promising prospects and ensuring that you’re always targeting the right people and maximizing your chances of success.
• Crafting Personalized Messages: With the deep insights into customer behavior and interests from AI, you can write personalized messages that will allow you to connect with your audience and boost engagement rates.
• Targeting The Right Audience: Predictive analytics from AI can pinpoint companies and individuals that match your ideal customer profile, refining your targeting efforts and improving your chances of reaching the right audience.

3 Best AI Tools For Sales Prospecting

The market is saturated with AI tools to help with sales prospecting, some of which specialize in finding and prioritizing high-value leads while others focus on automating tedious tasks such as data entry and lead research. Finding the right tool depends upon your specific needs and budget, but generally speaking, we recommend three that meet a wide range of needs in this area.

Apollo.io

Apollo.io is an all-in-one sales platform with built-in AI features for effective sales prospecting. It generates rich buyer data, with access to over 275 million verified contacts and more than 65 filters, including buyer intent, job postings, and headcount growth.

The platform stands out for its AI-powered writing assistant that lets you create hyper-personalized emails for every stage of your sales pipeline. It also has lead-scoring, contact database management, and email outreach solutions.

Apollo.io can occasionally generate incorrect contact information in its vast database, making some of the emails bounce. But this AI tool remains a top choice despite this drawback due to its solid automation capabilities and personalized outreach features.

Wiza

Wiza is an AI sales prospecting and engagement platform that extracts verified email addresses and phone numbers from LinkedIn profiles, making it a valuable resource for sales professionals and marketers.

The platform can turn LinkedIn search or saved lists into valid email lists, scrape leads in bulk, and produce a clean spreadsheet with the contact info. It also has real-time prospecting and email verification with a high deliverability rate.

Wiza lacks the extensive integrations offered by some competitors, but its ease of use and ability to quickly and efficiently provide high-quality leads compensates for its shortcomings.

Seamless.AI

Seamless.AI is a sales prospecting tool that applies AI to streamline the process of finding and connecting with potential customers. It empowers you to build a sales pipeline, shorten your sales cycle, and close more deals.

This AI tool comes with a search engine for B2B sales leads, firmographic filters, and business insights that aid in building leads lists. It also has AI recommendations that continuously find prospective buyers as well as a Chrome extension for searching contact information anywhere on the web.

It’s worth noting that some users have reported issues with the quality of data and limited data source from Seamless.AI. However, its sophisticated AI sales prospecting features—like automated list-building and real-time data verification feature—ensure that your contact database is error-free, making it a worthy investment.

AI Ethics and Best Practices in Sales Prospecting

AI continues to revolutionize sales prospecting by enabling businesses to more efficiently discover and engage potential customers. However, using this technology requires a strong commitment to ethical practices to ensure transparency, fairness, and respect for privacy. It’s important to keep ethical considerations in mind and follow best practices for using AI in sales prospecting.

Data Privacy and Management

To ensure your business complies with data protection laws like the European Union’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), collect and process data transparently and strictly within the bounds of prospect consent. Implement robust data anonymization techniques and encryption protocols to safeguard personal information. High-quality data management is paramount—make sure your AI training data is accurate, relevant, and up-to-date, as low-quality data can produce inaccurate predictions and insights.

Bias, Fairness, and Personalization

To promote fairness, audit your AI models regularly for biases that could cause unfair treatment of certain groups. Using diverse datasets and fairness-aware algorithms helps you mitigate biases and prevent AI hallucinations. Make sure you obtain explicit consent from prospects before making use of their data for personalized outreach, respecting their preferences and privacy choices.

Transparency and Monitoring

Your AI-driven decisions should be interpretable so that stakeholders can understand how AI models operate. To build trust and align with ethical standards, inform your prospects when AI is being used in the engagement process and keep an eye on AI models to make sure they perform as expected and do not drift from ethical standards.

Accountability and Training

Maintaining human oversight in AI-driven processes is of utmost importance to uphold ethical standards. AI tools should assist human judgment rather than replacing it. Establish clear accountability for AI outcomes and put protocols in place to address any negative impacts caused by AI decisions for responsible AI use. Conduct regular training sessions for your sales teams on ethical AI use and best practices to make sure that all team members understand their significance.

Frequently Asked Questions (FAQs)

How is AI Used to Forecast Sales?

AI forecasts sales using ML algorithms. These algorithms analyze historical data and external factors like seasonality and market trends and give accurate future sales predictions by detecting patterns and relationships in the data.

Can I Use AI for Marketing Strategy?

Yes, AI tools can enhance marketing strategies. They analyze customer data to identify patterns and preferences, segment audiences for targeted campaigns, and predict customer behavior. AI can also automate personalized content delivery, optimize ad placements, and accurately measure campaign effectiveness.

Bottom Line: AI Sales Prospecting Can Unlock New Opportunities

By using AI for sales prospecting, you can improve your workflows, find high-value leads, and personalize outreach efforts—but you must craft effective prompts that guide the AI’s decision-making process. When developing your own prompts, keep them specific, relevant, and well-defined to ensure precise and actionable insights. Mastering basic prompts for AI sales prospecting lets you uncover new opportunities, elevate your sales performance, and stay ahead of the competition.

AI is a powerful tool for prospecting and other sales-related efforts. It simplifies pinpointing and engaging potential customers for various businesses, including retail organizations. Read our comprehensive guide on top AI retail solutions to discover the best AI tools for retailers today.

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