Writing Effective Questions

The quality of your questions determines the quality of insights you'll uncover. Diaform's AI excels at following up on open-ended questions, so your base questions should be broad, conversational, and designed to invite detailed responses.

Open-Ended vs Closed Questions#

Prefer open-ended questions for richer, more actionable data. Closed questions (yes/no, ratings, multiple choice) limit what respondents can tell you. Open-ended questions give the AI room to explore context, motivations, and nuance.

Keep It Conversational#

Write questions as if you're talking to a friend, not conducting an academic survey. Conversational questions feel natural and encourage honest, detailed responses.

Academic: "Please provide feedback regarding your product utilization experience."

Conversational: "What has your experience been like using our product?"

Recommended Question Count#

3-5 questions is ideal for most use cases. More questions mean longer interviews, which can lead to respondent fatigue and drop-off.

• 3 questions: Quick pulse checks, post-transaction feedback (5-10 min)
• 4-5 questions: Customer satisfaction, onboarding feedback (10-15 min)
• 6+ questions: Deep research, product discovery (15-25 min)

Remember: the AI asks multiple follow-ups per question, so even 3 questions can generate substantial depth.

Good vs Bad Examples#

Here are real-world examples that demonstrate the difference between surface-level and insight-generating questions:

Example 1: Product Experience#

Bad: "Rate our product 1-10"

Good: "What has your experience been like using our product?"

Why: The rating gives you a number but no context. The open-ended version invites stories, specific examples, and natural follow-up opportunities (e.g., "Can you tell me more about that frustration you mentioned?").

Example 2: Recommendation Intent#

Bad: "Would you recommend us?"

Good: "If a colleague asked about us, what would you tell them?"

Why: The yes/no version is binary. The alternative reveals what aspects they'd highlight, how they describe your value, and what reservations they might have.

Example 3: General Feedback#

Bad: "Any feedback?"

Good: "What's one thing you wish worked differently?"

Why: "Any feedback?" is too vague—most people will say "no" or give generic answers. Asking for one specific improvement makes it easier to respond and surfaces actionable insights.

Focus on Past Behavior Over Hypotheticals#

Ask about what people have actually done, not what they think they might do in the future. Past behavior is a more reliable indicator of needs, pain points, and decision-making.

Hypothetical: "Would you use a feature that does X?"

Behavior-focused: "Tell me about the last time you tried to do X. What did you end up doing?"

One Topic Per Question#

Don't combine multiple topics into a single question. It confuses respondents and makes it harder for the AI to follow up effectively.

Combined: "What do you like about our product and what would you improve?"

Separated:

• "What's working well for you in our product?"
• "What's one thing you wish worked differently?"

Question Limits Per Plan#

Your plan determines how many questions you can add per conversation:

• Trial (post-trial): Up to 6 questions
• Starter: Up to 10 questions
• Pro: Up to 20 questions
• Business: Up to 20 questions

If you need more questions, consider splitting your research into multiple projects or upgrading your plan.

Next Steps#