Best Practices

Get the most out of your AI interviews with these proven approaches.

Match the interview type to your goal. Use Discovery Interviews for early-stage research, Churn Interviews inside cancellation flows, and Post-Release Feedback after major feature launches.
Keep your interview outline focused. 4–6 core topics produce better conversations than exhaustive question lists. The AI will probe deeper on its own.
Share the link in context. A link placed at the point of action (e.g., after a user cancels, right after onboarding, or in a tooltip near a feature) gets higher completion rates than cold email blasts.
Run at least 20 interviews before drawing conclusions. Thematic patterns become statistically meaningful at volume. Aim for 20–50 for early signal; 100+ for confident decisions.
Use Reals to align your team. Short audio clips are faster to share and easier to absorb than full transcripts. Use them in team standups or stakeholder reviews.
Review sentiment alongside themes. A theme that appears frequently but carries negative sentiment is a friction point. A theme with high positive sentiment is a strength to double down on.
Iterate your outline. After your first batch of interviews, review the themes and refine your questions to go deeper on what emerged.

How to Interpret Results

High-frequency themes: Topics that appear across many interviews signal broad patterns, not just individual opinions.
Negative sentiment on specific themes: This is where your product has friction or unmet expectations.
Unexpected language: Pay attention to the words customers use. They often reveal how to write your copy, name features, or position your product.
Emotional signals: Frustration, enthusiasm, and hesitation show up in how customers talk, not just what they say. Reals are especially useful for capturing this.

Stopping at 5 - 10 interviews. Small samples create false confidence. Themes shift as more voices are added.
Reading transcripts instead of themes. Start with Thematic Analysis for the big picture, then drill into specific transcripts to add texture.
Ignoring the AI Analytics Chat. This is your fastest path from raw data to actionable insight. Ask it direct questions like "What's the top reason users mention churning?"

Save high-signal quotes to your Notes for use in roadmap discussions or stakeholder decks.
Share Reals with your team to build shared understanding quickly.
Use recurring interview projects (e.g., monthly churn interviews) to track how sentiment shifts over time.