> ## Documentation Index
> Fetch the complete documentation index at: https://docs.userintuition.ai/llms.txt
> Use this file to discover all available pages before exploring further.
> Maximize the value of your customer research with these proven best practices for study design, participant recruitment, and insight activation.
# Best Practices
Maximize the value of your customer research with these proven best practices. These recommendations come from extensive experience conducting thousands of AI-moderated interviews.
***
## Study Design
### Start with Clear Objectives
Before creating a study, articulate:
* **The core question:** What must this research answer?
* **The decisions:** What will you do differently based on what you learn?
* **The stakeholders:** Who needs to act on these insights?
If you can't articulate what decision will change based on the research, consider whether you need the study at all.
### Focus on Depth, Not Breadth
**Don't try to cover everything.** Studies that go deep on 4-6 topics deliver more actionable insights than broad studies that skim 15 topics.
| ❌ Too Broad | ✅ Focused |
| -------------------------------------- | --------------------------------------- |
| "Tell us about your entire experience" | "Walk me through your checkout process" |
| 15 topics, 2 questions each | 5 topics, 6 questions each |
| Surface-level across everything | Deep understanding of key areas |
### Write for Your Participants
* Use language your customers understand
* Avoid internal jargon and acronyms
* Frame questions from their perspective
* Test your wording with a few participants
### Trust the AI to Probe
You don't need to script every follow-up question. The AI interviewer naturally:
* Asks "tell me more" when responses are brief
* Probes deeper when participants mention something interesting
* Requests specific examples to ground abstract statements
* Follows unexpected threads that may reveal insights
***
## Participant Recruitment
### Prioritize Real Customers
Whenever possible, interview your actual customers rather than panel participants. Real customers provide:
* Genuine experiences with your product
* Specific, contextualized feedback
* More relevant and actionable insights
### Set Clear Expectations
In your invitation, communicate:
* How long the interview will take (be accurate)
* What topics you'll cover (high level)
* Why their feedback matters
* Any incentives offered
### Time Your Invitations
| Context | Best Timing |
| ------------------- | -------------------------- |
| Post-purchase | Within 24-48 hours |
| Churn research | Shortly after cancellation |
| Onboarding feedback | End of first week |
| General feedback | Avoid Mondays and Fridays |
| B2B research | Mid-week, business hours |
### Send Reminders
A single reminder 3-5 days after the initial invitation can significantly improve response rates. Keep it brief and friendly.
***
## During Data Collection
### Monitor Early Responses
Listen to your first 3-5 interviews to:
* Confirm questions are understood correctly
* Verify the conversation flows naturally
* Catch any issues before scaling recruitment
* Validate your research hypotheses (or adjust them)
### Don't Edit Mid-Study
Once participants have started completing interviews:
* **Avoid changing questions** (compromises comparability)
* **Don't adjust the flow** (earlier and later responses won't match)
* **Note issues for next time** instead of fixing mid-stream
If changes are truly necessary, document when they occurred and consider separating analysis into pre/post change periods.
### Check Quality Distribution
Monitor your High Quality count relative to total responses. If quality is low:
* Review if questions are confusing
* Check if you're reaching the right participants
* Consider whether the topic engages participants
***
## Analysis and Reporting
### Look for Patterns, Not Just Quotes
Individual quotes are powerful, but patterns matter more:
* What do multiple participants mention?
* Where do responses contradict each other?
* What's notably absent from conversations?
### Consider Sample Size
| Sample Size | Appropriate Conclusions |
| ----------- | ---------------------------------------- |
| 2-5 | Directional hypotheses to validate |
| 10-20 | Emerging patterns (handle with care) |
| 30+ | Higher confidence in consistent findings |
Always note sample size when sharing findings.
### Connect Insights to Actions
Every insight should connect to potential action:
| Insight | Action |
| ------------------------------ | ---------------------------------------------- |
| "Checkout feels slow" | Investigate performance; A/B test improvements |
| "Confused about pricing tiers" | Revise pricing page; test clearer copy |
| "Love the mobile app" | Double down on mobile investment |
If an insight doesn't connect to a potential action, consider whether it was worth learning.
### Share Widely, But Appropriately
| Audience | What to Share |
| ------------- | --------------------------------------------- |
| Executives | Executive Summary + Top Insights |
| Product teams | Detailed findings + specific quotes |
| Marketing | Customer language + perception insights |
| Sales | Objection patterns + competitive intelligence |
***
## Building a Research Practice
### Create Recurring Studies
For ongoing intelligence, establish:
* **Quarterly brand health tracking**
* **Monthly churn analysis**
* **Continuous onboarding feedback** (via widget)
* **Post-launch research** for each major release
### Build Institutional Knowledge
User Intuition's Intelligence Hub becomes more valuable over time:
* Query across historical studies
* Identify long-term trends
* Preserve knowledge through team changes
* Accelerate onboarding for new team members
### Close the Loop
After each study:
1. Share findings with stakeholders
2. Identify 2-3 concrete actions
3. Track whether actions were taken
4. Measure impact where possible
5. Document learnings for future studies
***
## Common Mistakes to Avoid
**❌** "Don't you think our checkout is confusing?"\
**✅** "Walk me through your experience with checkout."
**❌** 20 topics in a 15-minute interview\
**✅** 5-6 topics explored deeply
Low-quality responses often reveal confusion or disengagement—which is itself a finding worth investigating.
One passionate participant doesn't make a pattern. Wait for consistent themes across multiple interviews.
Research that doesn't lead to action wastes resources and erodes organizational trust in research value.
Resist the urge to tweak questions once interviews have begun. Note improvements for next time instead.
***
## Quick Reference
### Study Setup Checklist
* [ ] Clear research objective defined
* [ ] 4-6 focused topics identified
* [ ] Questions written in participant language
* [ ] Decision/action identified for insights
* [ ] Study tested before launch
### Recruitment Checklist
* [ ] Target participants identified
* [ ] Invitation includes time estimate
* [ ] Incentive communicated (if applicable)
* [ ] Reminder plan in place
* [ ] Early responses monitored
### Analysis Checklist
* [ ] Listened to sample of interviews (not just read transcripts)
* [ ] Patterns identified across multiple participants
* [ ] Sample size noted with findings
* [ ] Insights connected to actions
* [ ] Appropriate sharing with stakeholders