Amplitude shows which events users triggered, but event logs do not explain why users took those actions. Importing cohort criteria into Minds lets product managers explore the intent and friction behind behavioural segments.
An Amplitude chart shows you precisely what a group of users did. It shows when they dropped off in an onboarding funnel, how frequently they fired a specific event, and where their path diverged from retained users.
Product teams often look at these behavioural cohorts and assign motivations to them. If a user triggers skip_team_invite, the team assumes the user works alone. If a user stops after completed_step_2, the team assumes step three was too difficult. The cohort definition records the action, but it tells you nothing about the goal the user had in mind when they took it.
A behavioural cohort is an aggregation of actions. It is not an explanation of why those actions occurred. When teams analyse why one cohort retained while another churned, they frequently compare event counts. They notice retained users fired dashboard_filter_applied five times in week one, while churned users fired it zero times.
This comparison usually leads to product changes that try to force the behaviour, such as adding tooltips to the filter bar. It fails to ask what problem the retained users were trying to solve with that filter, or why the churned users found no reason to touch it.
Additionally, Amplitude cohorts rely on internal event taxonomy. Event strings like btn_workspace_cfg_v2_click or modal_dismiss_timeout make sense inside a tracking plan, but they obscure the actual user journey. When teams discuss the cohort solely in these terms, they lose touch with the human problem the customer was trying to solve.
You can use Minds to test hypotheses about the mental models behind your Amplitude segments. Minds does not connect directly to Amplitude. You export or copy your cohort criteria and bring them into the platform as reference documents.
Open your cohort in Amplitude and review the criteria. Copy the behavioural definition, such as the sequence of events, frequency thresholds, time windows, and user properties.
If your event names are technical or abbreviated, add a short sentence next to each event describing what the user saw on screen.
Save this information as a document. Minds accepts PDF, Word, CSV, spreadsheet, and plain text formats.
Upload or paste the document into a Minds project.
Define a simulated audience that matches the profile of the users in that cohort, including their technical skill, job role, and core objective.
Prompt the simulation to explore the decisions, confusion points, or unmet expectations that would lead a user with that profile to follow that exact path.
Once you bring the behavioural attributes into Minds, you can prompt the simulated audience to evaluate your product flows from the perspective of that specific group.
Instead of guessing why users who hit trial_started failed to reach project_created, you can present the onboarding steps to a synthetic audience configured with the constraints of that drop-off segment. You can ask what assumptions they made when seeing the initial setup screen, what friction caused them to exit, and what alternatives they might have considered.
This process gives you clear, testable hypotheses about user intent. It helps you design experiments that address the underlying reasons for behaviour rather than simply treating the symptoms visible in your event charts.
Bring the cohort definition and its behavioural attributes, not user records. The output is a hypothesis about motivation, not a measurement of it.
Minds does not analyse actual customer telemetry, calculate retention probabilities, or predict how metrics will change in your analytics dashboard. Synthetic results describe the simulated audience only. Use these findings to generate better hypotheses for your next product iteration or qualitative interview guide.
Paste a prompt structured like this alongside your exported cohort criteria:
I have pasted the behavioural criteria for our Amplitude drop-off cohort below, along with descriptions of the screens where each event occurs. Assume the mindset of a mid-market operations manager evaluating this workflow for the first time. Review the sequence between event onboarding_step_1_submit and event trial_abandoned. Explain three plausible reasons why someone with this background and intent would stop at this stage, what information they felt was missing, and what they likely attempted to do next outside of our interface.
Frequently asked questions
Is there a direct API connector between Amplitude and Minds?
No. You copy your cohort definitions, event names, and funnel descriptions directly from Amplitude and paste or upload them into Minds as text, spreadsheets, or documents.
Can I upload individual user event streams or user IDs?
No. Do not upload customer personal data, user identifiers, or raw tracking logs. You upload only the aggregate logic and behavioural criteria of the cohort.
How does Minds handle internal event names from our taxonomy?
Minds interprets the event names you supply. If your names are obscure, include a short glossary or paste your tracking plan descriptions alongside the cohort rules.
Does this replace user interviews with churned customers?
No. Synthetic cohorts provide rapid hypotheses about why users might drop off. They do not replace direct qualitative conversations with real people.
Can Minds tell me the future retention rate of a new cohort?
No. Minds simulates cognitive perspective and potential objections for defined profiles. It does not forecast retention curves or statistical conversions.
