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Ask users why

Give an AI agent the ability to ask real users why a product behavior is still unexplained.

When to ask users

Use this page when an analytics tool has already shown what happened, and the remaining question is why those people did it. Funnel drop-off, churn, a stalled activation, a spike in regenerations, and a guide that people dismiss are signals. They become a UserCall investigation when the chart cannot name the cause.

Connect once at https://mcp.usercall.co, sign in, and start with create_study. Setup for the connector lives in the MCP docs. Read the page that matches the tool that produced the signal before you write the study.

The pattern

  1. Signal. Record the metric, the time window, and who was affected. Keep the numbers the analytics tool returned.
  2. Unknown. Write the question those numbers cannot answer, in one sentence a person can respond to.
  3. Interview affected users. Call create_study. Put the question in key_research_goal and the signal in business_context. Share the returned interview_link with the people in that cohort.
  4. Evidence. Poll get_study_status until status is complete. Then call get_study_results with format summary. Place the themes next to the original signal.

Start with create_study

create_study is the entry. key_research_goal is the question the interviewer must learn. business_context is the product, the signal, the window, and who to talk to. target_interviews is how many conversations you need before you will trust a pattern. duration_minutes defaults to 12.

create_study({
  key_research_goal: "Why did these users leave at this step? Ask what they expected, what stopped them, and what they did instead.",
  business_context: "Name the product, the analytics tool, the metric, the dates, the counts, and the cohort to interview.",
  target_interviews: 8,
  duration_minutes: 12
})

The call returns study_id and interview_link. One active agent study is allowed per account. If credits are short, the tool returns checkout_url. Hand that URL to a person.

After interviews finish, get_study_results with format: "summary" returns themes, insights, and risks. Ask for format: "full" only when you need a quote. A summary is the evidence. A transcript is the backup.

Investigation pages

  • PostHog — a funnel, path, or replay shows the drop and still cannot say why.
  • Amplitude — a cohort or retention curve names who left and still cannot say why.
  • Pendo — adoption, a guide, or a thin poll shows the stall and still cannot say why.
  • AI products — regenerate, thumbs-down, or abandon shows the failure and still cannot say why.

Skill

The investigate-user-behavior skill runs this same loop beside a PostHog, Amplitude, or Pendo MCP. It lives in this repository at skills/investigate-user-behavior/SKILL.md. An agent that can read this page can follow the loop without the skill installed.