How do I ask good questions to Pilea?

Welcome to Pilea

The difference between getting useful insights and generic fluff from AI comes down to how you ask questions. This guide shows you how to ask Pilea specific questions that lead to actionable insights, when to trust AI patterns versus digging deeper yourself, and how to avoid going down rabbit holes that waste time without improving decisions.

The short version

  • Ask specific questions, not "What do customers want?"
  • Use your review time to find blind spots, not confirm what you already know
  • Trust clear patterns with multiple examples, investigate surprises
  • Share actual customer language, not your interpretation
  • The difference between good and terrible questions for AI

    Ask Pilea "What do customers want?" and you'll get a generic list that doesn't help anyone. Ask "What specific onboarding problems are new users mentioning?" and you'll get actionable insights.

    The difference is specificity. Pilea works best when you give it a clear target, not when you ask it to read your mind.

    Start with "what themes am I missing?" not "tell me everything"

    Your weekly summary already shows the obvious patterns. Use your review time to dig into blind spots.

    Try questions like:

    • "What are customers saying about our competitors?"
    • "What problems do customers mention that we haven't prioritized?"
    • "What workflows do users struggle with that we think are simple?"

    These questions help you discover gaps between customer reality and team assumptions.

    Screenshot of asking questions in Pilea

    When to trust AI insights vs. when to dig deeper yourself

    Trust Pilea when it shows clear patterns with multiple examples. Three different customers mentioning the same specific problem? That's worth paying attention to.

    Dig deeper when something surprises you or contradicts what you expected. If Pilea says customers love a feature you think is problematic, read a few actual examples to understand why.

    The AI is great at spotting patterns you'd miss. You're great at understanding context the AI might not catch.

    Following up without going down rabbit holes

    Found an interesting theme? Ask one specific follow-up question, then stop. "What exactly are customers saying about mobile performance?" is a good follow-up. Then asking "What about Android specifically?" then "What about Samsung devices?" will pull you away from other priorities.

    Set a timer. One main question, one follow-up, then move on. Save deeper investigation for themes that directly impact current decisions.

    Making insights shareable with people who weren't there

    When you find something worth sharing, include the specific customer language, not just your interpretation.

    Instead of: "Customers want better search"Try: "Three customers this week mentioned 'can't find what I'm looking for' and 'search results don't make sense'"

    Raw customer language is more convincing than your summary, and it helps your team understand the real problem.

    Common question patterns that actually work

    • "What are customers saying about [specific feature you're considering]?"
    • "What problems do [specific user type] mention most often?"
    • "What positive feedback are we getting about [recent change]?"
    • "What complaints have we not addressed yet?"

    These questions give Pilea clear boundaries and give you actionable answers you can actually use in planning conversations.

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