Artificial intelligence in 2025 will penetrate even further into corporate operations, allowing it to automate routines, sort through information, and customize interactions with customers. We deal with businesses of all sizes on a daily basis, so to our thinking, the most fascinating technology in this area is AI personas, i.e., virtual avatars with which you can mimic the behavior, interests, and preferences of the users.
Why is this important for your business? AI-generated personas are already being implemented in automated support systems, AI chatbots, and virtual assistants. McKinsey research shows that personalized customer experience can increase revenue by up to 15%, and 65% of consumers expect brands to tailor communications to their needs. AI personas allow you to do just that — build flexible, intelligent interactions with users, improving retention and conversion.
In this article, we will analyze what AI personas are, how they work, and why you should implement them in your marketing, product, and service strategy. You will also get a step-by-step process for creating AI personas and analyzing examples of their successful use.
What is AI Generated Persona
An AI-generated persona is a digital interpretation of a real user, customer, or expert, created using machine learning and data analysis. It is filled with the same characteristics as the original personas. Unlike static marketing personas, which are built on hypotheses and generalized demographic data, AI personas are formed based on real behavioral patterns, interests, and interaction context.
Why is this important to you?
Traditional segmentation methods no longer work as effectively as they used to. According to Gartner, 80% of marketers who use segmentation admit that their models do not produce the expected results. AI-generated personas are a game changer. They are dynamic, able to adapt to market changes, and automatically update as new data comes in.
AI personas are used in SaaS, marketing, sales, and customer service, and are also becoming a key tool for:
- Personalized interactions: they adapt communications to the user's style and behavior, which increases engagement.
- Marketing and sales automation: AI assistants can qualify leads, personalize content, and improve the customer journey.
- Customer service improvements: Chatbots and virtual assistants can act like human experts, offering up to 40% more relevant responses (according to Salesforce).
Instead of outdated template profiles, you get flexible, adaptive, and self-learning models that help your business increase conversions, reduce customer acquisition costs, and improve user satisfaction.
AI personas are not about abstract segments that a marketer once drew on a whiteboard. They are living, constantly updating digital avatars that analyze millions of signals, adapt to user behavior, and react to changes faster than your marketing team can hold another brainstorming session.
Amazon has long understood that a personal approach is not just an option, but a business necessity. 35% of its sales come from the AI personalization engine. Netflix is experimenting with AI to create custom movie previews: someone will be shown a dynamic action scene, someone a romantic moment - it all depends on your past viewing. Now imagine that your marketing, sales, and even products work the same way.
It all starts with AI personas for personalized marketing. While 80% of marketers admit that their segments do not work (according to Gartner), AI analyzes behavioral data and gives hyper-relevant recommendations. Starbucks uses AI to personalize offers in a mobile app, increasing the average check by 10-15%. If your strategy still includes “women 25-35, interested in fitness,” it’s time to reconsider your approach.
In sales, AI personas are becoming invisible sales assistants. HubSpot, Salesforce, and even LinkedIn are implementing AI that predicts the likelihood of a deal, determines which customers are on the verge of churning, and suggests who should be pressed. A 20-30% reduction in the deal cycle is not magic, but the work of algorithms.
AI personas in customer service have already gone beyond boring script bots. Erica from Bank of America has processed more than a billion requests, and AI chats in Shopify help stores close deals faster than live operators. H&M is testing AI stylists who recommend clothes based on your style, and all this without human intervention.
SaaS companies use AI personas for product solutions. Miro analyzes which features people use most often and rebuilds the interface. Notion trains AI on your notes to suggest relevant tags and categories. This is not just UX tuning - it is a transformation of how we interact with products.
And in content? AI personas write headlines, select images and test texts. M1-Project.com offers Social Media Content Generator, that adapts content to your audience, simplifying the creation of personalized campaigns. Netflix uses AI to adjust trailers for different groups of viewers. All this works because AI sees data that humans will not notice.
Our team doesn’t recommend trying to play by the old rules when the market has already changed. AI personas are a tool that makes marketing and products not only smarter but also faster. Use them, or in a couple of years, you will catch up with those who have already built them into their strategy.
Want to learn how to create such an AI persona? Let's break down the step-by-step process.
How to Create AI generated Persona: A Step-by-Step Process
Creating AI personas is not about copying and pasting classic buyer personas with age and position. It is about a living model that is updated based on real user behavior, not marketers' assumptions. This approach gives businesses a competitive advantage. McKinsey confirms that companies using AI for personalization increase revenue by 10-30%
Step 1: Collecting data and creating a foundation
AI does not build personalized models on guesswork. It needs data. The more information you have about user behavior, the more accurate the model will be. Three key sources are used: behavioral, transactional, and contextual data
Google Analytics and Amplitude record how users move around the site, which pages they visit, and where they spend more time. CRM (HubSpot, Salesforce) shows how the lead status changes, which leads to a sale. Social networks provide information on engagement, interests, and activity. ICP Generator from M1-Project.com combines this data to help create the basis of an AI persona
Step 2: Finding patterns and segmenting the audience
An AI persona is not just a digital profile, but a dynamic model that identifies patterns in behavior. It is important not to try to artificially create segments but to let the data speak for itself
Cluster analysis helps to identify groups of users with similar interaction patterns. Cohort analysis provides an understanding of how the behavior of different segments changes over time. It is important to monitor changes. Airbnb uses AI to adapt recommendations for tourists depending on seasonality and past bookings
Step 3: Forming an AI persona
Unlike static buyer personas, an AI persona is constantly updated. It is based on three key components: a digital footprint, a behavioral model, and predicted actions
Facebook Ads analyzes which ads attract attention, how many seconds a user watches a video, and which headlines catch their attention. Spotify takes into account the time of day, preferences, reactions to playlists, and adjusting recommendations to a specific context. If AI sees that a user tends to return to certain products or topics, it will offer more similar content, increasing the likelihood of conversion
Step 4: Testing and adjusting the model
AI does not work perfectly from day one. Each AI persona must be tested and adjusted. Netflix tests AI models on thousands of segments before a large-scale launch, checking how much personalization increases engagement
The best way to test is to run A/B experiments, checking how much the predicted actions match real behavior. If AI predicts that a user should click on a CTA, but this does not happen, then the model needs to be adjusted. Marketing Strategy Builder from M1-Project.com helps to adapt the strategy based on test results
Step 5: Integrate the AI persona into marketing, sales and product
AI personas are useless if they remain in analytical reports. They must work at all levels. In marketing campaigns, in sales scenarios, in product solutions
Amazon uses AI personas for dynamic pricing and personalized offers, increasing the average check. In B2B, AI algorithms in HubSpot predict the likelihood of a deal and recommend optimal steps for sales managers. In SaaS products, AI adapts onboarding, offering features that are most relevant to a particular user
Prompt Formula for Creating an AI Persona in ChatGPT
One of the fastest ways to get a detailed AI persona is to use ChatGPT. To achieve accuracy, we have developed a universal query formula that allows you to get a clear, structured and practically applicable profile of the output. This formula helps us and our clients in B2B, SaaS, e-commerce, and other industries to quickly adapt marketing, sales, and product strategy to real market needs.
Here is the structure of the request that we use in our work:
"You are [an AI role, for example, a marketing analyst, a sales expert]. Create an AI persona for [type of business or product, for example, a B2B SaaS product, an e-commerce store, a fintech startup]. Describe the target client, including the following parameters:
Name and position: [a typical client, for example, a marketing director, CEO, a freelancer]
Demographics: [age, gender, income level, lifestyle]
Major pain points: [key problems that the product solves]
Major purchase triggers: [what makes the client look for a new product or service]
Behavioral patterns: [how the client makes decisions, what they study before buying]
Where they look for information: [what resources, social networks, forums they use]
Objections before purchase: [what fears and doubts interfere with conversion]
Best methods of persuasion: [what arguments and offers work better total]
Preferred communication channels: [email, social media, webinars, calls]
Create a detailed and comprehensive profile with an emphasis on real behavior patterns, motivations, and decision points. Indicate which marketing strategies are suitable for working with this AI persona"
This formula can be adapted to any niche, you should just insert the necessary parameters.
How AI Personas Work in Practice: Real-World Examples
1. AI persona in e-commerce: how Amazon personalizes purchases
Amazon has long been using AI to create personalized recommendations. This is not just a selection of similar products, but a complex system that analyzes purchase history, views, clicks, frequency of returns, and time of interaction with content. AI understands which product the client is more likely to buy, even if he himself does not yet realize his need
Example: a client is looking for a camping tent, but does not buy it right away. AI analyzes his previous orders, viewed pages, and reviews left on other products. A couple of days later, the user is shown not only a tent but also a list of related products - a lantern, a thermos, a gas stove. This approach increases the average check and conversion rate. According to a McKinsey study, personalized recommendations bring Amazon up to 35% of all revenue
2. AI persona in SaaS: how Notion adapts the product to each user
Notion is not just a notepad with the ability to insert tables and tasks. It is a product that understands how each specific user uses it. If a person often creates to-do lists, AI offers templates for task management. If he works with tables, it suggests how to link databases
But the most interesting thing begins when Notion analyzes team interaction. If several employees of the company actively use the same space, AI recommends them to create common rules, offers automation, and simplify navigation. This approach retains users, makes the product more convenient and reduces churn. According to the company, an AI-optimized interface increased user engagement by 20%
3. AI persona in the financial sector: how Bank of America improved service quality with Erica
Bank customers expect a quick answer to their questions, but call centers are overloaded, and standard chatbots cannot handle complex requests. Bank of America solved this problem by implementing Erica, an AI-powered virtual assistant. Erica does not just answer customer questions, but analyzes their financial habits, offers personalized advice, and warns about possible problems
If a customer often forgets to pay bills, AI offers to set up automatic debits. If it sees that a person is spending more than usual, Erica sends a notification and suggests how to reduce expenses. Since its launch, Erica has processed over 1 billion requests, and customer satisfaction has increased by 90%
4. AI persona in B2B marketing: how M1-Project.com helps companies build strategies
B2B products are more difficult to sell than goods in e-commerce. Marketers spend weeks analyzing the audience, creating ICP, and developing a strategy. AI allows you to automate this process and work with real data instead of assumptions
M1-Project.com offers an ICP Generator that analyzes the market, identifies key customers, and segments the audience by behavioral patterns. Instead of hypothetical “marketing directors from SaaS companies,” AI creates accurate profiles: who these people are, what tools they use, and what triggers influence their decisions. This speeds up the process of creating marketing campaigns and increases conversions
5. AI persona in streaming services: how Netflix retains users
Netflix knows more about users than it seems. It analyzes not only what movies and TV shows people watch, but also at what point they pause, what genres they prefer at different times of day, how they react to trailers. All this helps create AI personas that predict what content is best suited for each viewer
If the AI sees that a user watches thrillers on weekdays and comedies on weekends, the recommendations will adapt to this rhythm. If someone likes Scandinavian detectives but has never watched French ones, Netflix will offer a similar style, but in a new location. This kind of personalization helps retain the audience and reduce subscriber churn.
Conclusion
AI personas are changing the approach to marketing, sales, and product strategy. Companies that implement them receive accurate predictions of customer behavior, personalize interactions, and automate key processes.
Amazon personalizes recommendations, increasing the average bill. Netflix adapts content for each user. Bank of America improves the quality of service with virtual AI assistants. These examples show that AI personas are becoming the standard for working with audiences.
At M1-Project, we use ChatGPT and our own tools, such as ICP Generator and Marketing Strategy Builder, to create AI personas based on real data. This approach helps businesses better understand customers and effectively adapt strategies.
If your marketing and sales are still based on static segments, it's time to change your approach. AI personas provide not just analytics, but ready-made solutions that work.
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