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A user model is an AI representation of a specific group of people. It’s built from real human data and predicts how that group would answer questions they’ve never been asked. Think of it as a research panel that responds in seconds.
50+ user models and growing. UK and US adults, 16 UK Consumer Finance segments (from Growing Families to Just About Managing), tech industry segments (developers, designers, data scientists), and B2B software buyers. Ready-made user models are free to use.
Custom user models are built from your data: survey responses specific to your market, your customers, your users. They’re private to your account and tested for accuracy using cross-validation.
Survey data with questions, answer options, and response distributions is the foundation. Minimum 4 questions, ideally 20+. The more relevant and varied the seed data, the better the model generalises to new questions. We’re also beginning to work with other types of data like qualitative interviews, product analytics and user feedback. Get in touch → if you’d like to find out more.
Segments are separate user models representing subgroups within a broader category. For example, our UK Consumer Finance collection has 16 segments, each with different demographics, financial behaviours, and attitudes. You can ask the same question to multiple segments and compare how they respond.
Yes. Adding more seed data improves coverage and accuracy. More questions give the model more context to draw on when predicting new ones. Accuracy is re-evaluated automatically after each update.
Every prediction comes with an accuracy score. If the model has low confidence for a particular type of question, the score reflects that. You can see accuracy scores for every user model in the dashboard.