{"id":6944,"date":"2026-05-17T06:17:28","date_gmt":"2026-05-17T06:17:28","guid":{"rendered":"https:\/\/userpilot.com\/blog\/user-persona-examples-saas\/"},"modified":"2026-05-19T06:34:26","modified_gmt":"2026-05-19T06:34:26","slug":"user-persona-examples","status":"publish","type":"post","link":"https:\/\/userpilot.com\/blog\/user-persona-examples\/","title":{"rendered":"User Persona Examples in The LLMs Era: How to Build Them as Good Research Documents"},"content":{"rendered":"

Every guide I searched about user persona examples has the same definition, some interchangeable templates, a Spotify mock-up, and a CTA. None is answering the actual question product managers<\/a> are asking right now, which is whether any<\/em> of this still works.<\/p>\n

You see, the shift around user personas has widened the gap between those who created fictional personas and the teams that used them as validated research documents. On one hand, synthetic users made it possible to quickly create fake personas that look “legit”. On the other hand, 69% of teammates<\/a> are using AI for research projects, reporting faster turnarounds, better team efficiency, and more optimal workflows.<\/p>\n

So I went and read the people who actually study how buyers make decisions: Adele Revella at the Buyer Persona Institute, Noz Urbina at Urbina Consulting<\/a>, and the Market Research Institute International (MRII)<\/a>. Then, combined with our internal data and expertise (shoutout to Katie Kelly, our UX Researcher), I put together this guide on what user persona examples should look like in the era of LLMs and MCPs.<\/p>\n

Why most user personas end up unused<\/h2>\n

The first user persona came from Alan Cooper, a software designer who started writing one-page descriptions of a fictional user to keep engineers from designing for themselves. The idea was to give the team a shared, specific person to think about, so that they stop designing for “everyone.”<\/p>\n

However, three things tend to go wrong about this concept:<\/p>\n

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  1. The user persona stopped being researched and started being decorative:<\/strong>\u00a0Teams often only do the minimum user research and base their personas on initial hypotheses, not actual users.<\/li>\n
  2. The user persona drowned in demographics:<\/strong>\u00a0E.g., age, location, marital status, net worth, etc. None of which tells you why someone will or won’t buy your B2B SaaS product. As Clayton Christensen (author of “Competing Against Luck<\/a>“) says in his book about jobs theory: “I’m sixty-four years old. I’m six feet eight inches tall. My shoe size is sixteen. My wife and I have sent all our children off to college. I live in Boston and drive a Honda minivan. But these characteristics have not yet caused me to go out and buy the New York Times today.”<\/li>\n
  3. The user persona stopped getting updated:<\/strong>\u00a0Once printed and presented on a slide, the persona was set and forgotten. Then, after years of market shifts and behavior changes, the persona keeps describing a customer that no longer exists.<\/li>\n<\/ol>\n

    Now, LLMs are making user research more confusing. A category of synthetic user tools markets itself as “user research without the users.” You feed in a brief and get back a bot that mimics what a real user would do. The Nielsen Norman Group, who actually tested these platforms<\/a>, found that synthetic users “have a tendency to want to please” and “do not always model human behavior well.” Erika Hall, co-founder of Mule Design Studio and author of Just Enough Research<\/em>, has been blunter on LinkedIn<\/a>: “It is unethical, indefensible, and also unnecessary, to create a product or service or policy that affects other people, without having conversations with representatives of those populations.”<\/p>\n

    Despite this, AI is also making real research more<\/em> accessible. According to the MRII AI in Focus 2025 report<\/a>, 62% of market researchers say “most” or “some” of their team is now using AI, up from 39% the year before. The most common applications included literature reviews (53%), questionnaire development (50%), and learning new skills (36%). Plus, 85% report time savings as the biggest benefit.<\/p>\n

    Another change is that AI agents are now users. Anthropic’s MCP and the wave of agentic SaaS callers mean that a real percentage of your product’s traffic comes from models executing tasks on behalf of humans. That type of user has no demographics, nor goals in the human sense. But it has a job to do, success criteria, and failure modes, which means you now have to build for them too.<\/p>\n

    What a useful user persona looks like in 2026<\/h2>\n

    The good news is that the user persona didn’t die. Just like a couple of years ago, good user personas should look more like a research document of your target audience than a slide page. It acts as a compass for the team so they know what pains they’re trying to solve.<\/p>\n

    Here’s what you should still include when creating user personas today:<\/p>\n