Every analytics tool groups users by what they bought. Free, Plus, Team, Enterprise. This tells you nothing about what they actually do with the product — and the people who do the same thing never share a tier.
The groups in your BI are demographic
Plan tier. Country. Signup source. These are facts about the user, not about the use. They're easy to store in a row, easy to filter on, and easy to chart. They are also almost useless for product decisions.
Two Plus users can behave nothing alike. One is a writer drafting emails. The other is an analyst running SQL through natural language. Grouping them by plan reveals nothing about either.
The groups that matter are behavioural
The groups that predict retention, satisfaction, and churn are behavioural. A behavioural group is defined by what the user does — the shape of their conversations, the tools they call, the use cases they return to.
- Writers — prose drafting, often paired with creative brainstorming.
- Code-first — mostly code, with a learning tail.
- Researchers — summaries, explanations, citations.
- Analysts — spreadsheets, SQL, numeric work.
- Generalists — broadly spread across four or more use cases.
- Advice-seekers — help with decisions.
These groups emerge from the conversations themselves. They cut across every plan tier, every country, every signup source. And they're the groups whose drift actually tells you something about the product.
Why this is hard
Behavioural segmentation is hard for the same reason reading conversations is hard: free text. A SQL query can slice by plan tier in a second. It cannot slice by what the user was trying to do — because that's not a column anywhere.
Locus reads the free text and produces those groups automatically. See six of them in a live sample or bring your own traces.