To get meaningful insights and enable our Interview Agent to ask intelligent follow-ups, Task Questions need to be formulated with both qualitative research rigor and AI interpretability in mind.
Activity Goal
Writing a Clear and Effective Activity Goal
Why it matters: The Activity Goal tells the AI the purpose and scope of your research activity. This keeps it focused and prevents irrelevant follow-ups.
Best practices:
- State the research topic clearly – Use explicit product, brand, feature, or behavior.
- Include the research purpose – Clarify the insight you’re seeking.
- Define scope and boundaries – Add constraints or exclusions to prevent tangents.
- Use plain language – Keep it clear and direct. If you have a short summary, aim for 1–2 sentences. If you already have a project brief, you can paste a few paragraphs, but make sure the key topic and purpose appear at the very top so the AI immediately knows the focus.
- Write for both humans and AI – Clear, precise, and easy to understand.
Formula: Action Verb + Research Focus + Purpose + (Optional Scope)
Short Example: “Explore how customers discover new meal delivery services and what factors influence their first purchase decision, excluding price-based considerations.”
Sample Goals by Research Type:
- Concept Testing: “Evaluate how target customers perceive the appeal and clarity of our new product concept for a portable air purifier.”
- Usability: “Identify areas of confusion in the mobile app’s onboarding process for first-time users.”
- Brand Perception: “Understand how Gen Z consumers view Brand X’s sustainability efforts and whether these efforts influence purchase intent.”
- Customer Journey Mapping: “Explore the steps small business owners take from initial awareness to purchase when choosing accounting software.”
- Ad or Message Testing: “Gather reactions to the tone, clarity, and persuasiveness of the new social media campaign targeting college students.”
Longer Example:
We are conducting a study to understand the perceptions, motivations, and concerns of frequent air travelers regarding eco-friendly airline initiatives. Our focus is on travelers who fly at least once a month for business or leisure. The research will explore awareness of current airline sustainability programs, perceived credibility of these programs, and whether these efforts influence booking decisions. We will also investigate which communication channels and messages are most effective in promoting sustainable travel behavior. Insights from this study will guide the development of targeted marketing campaigns and potential program improvements.
Task Questions
1. Ask One Thing at a Time
Why it matters: Questions that focus on a single topic are easier to answer and easier for AI to build on. When a question packs in multiple ideas or instructions, it creates confusion and makes it harder to generate useful follow-ups.
Best practices:
- Stick to one clear idea per question.
- Avoid combining multiple topics, like pricing and usability.
- Keep wording simple and free of unnecessary detail.
Examples:
- ❌ “What are your thoughts on the pricing and the usability of the app?”
- ✅ “What do you think about the app’s pricing?”
- ✅ “How would you describe the app’s usability?”
When Needed, Add Context with Brief Setups
Why it matters: A short setup before your main question can help ground the participant and frame their thinking. This is especially helpful when asking about past experiences or specific scenarios.
Best practices:
- Use a short, natural lead-in that focuses the participant without overloading them.
- Make sure your setup and question are clearly linked.
- Keep the entire prompt concise and free of nested clauses.
Examples:
- ❌ “Tell me what you think about the app, and whether or not you think it's something you would continue using, if the features get better, which they may in the next version.”
- ✅ “Think back to your recent shopping trip. What did you notice about the store entrance?”
- ✅ “Imagine you just opened the app for the first time. What stood out to you?”
Pro tip: If your prompt includes multiple instructions or conditions, re-read it aloud. If it feels like two questions or sounds overly complex, split it up.
2. Avoid Leading or Biased Wording
Why it matters: Leading questions nudge participants toward a specific answer, and AI may reinforce that bias in follow-ups.
Best practices:
- Don’t imply a value judgment or expected response.
- Avoid emotionally loaded or assumptive language.
- Replace “Do you like...” or “How good is...” with neutral alternatives.
Example:
- ❌ “Why do you love this brand’s customer service so much?”
- ✅ “How would you describe this brand’s customer service?”
3. Ask True Open-Ended Questions
Why it matters: Follow-up generation is strongest when initial questions encourage storytelling, not yes/no answers.
Best practices:
- Start with what, how, or tell me about.
- Avoid closed questions (especially starting with did, do, is, are, was).
- Don’t frame questions as binary choices.
Example:
- ❌ “Do you like using this app?”
- ✅ “What has your experience been using this app?”
4. Write Clearly for the AI to Follow
Why it matters: The AI follows logic based on what's stated. If a question is vague or inconsistent, it can lead the AI to ask confusing or irrelevant follow-ups. Clear and specific questions make it easier for the AI to stay on topic and extract meaningful insights.
Best practices:
- Refer explicitly to the thing you want to ask about (avoid words like "this" or "that" alone).
- Use the same term consistently (don’t switch from "plan" to "strategy" midstream unless they mean different things).
- Keep the structure of your questions simple and predictable.
Examples:
- ❌ “How did this make you feel?” (What is “this”?)
- ✅ “How did the sign-up process make you feel?”
Bonus Tips
| Tip | Why It Matters |
|---|---|
| Use present or recent-past tense | Helps ground responses in experiences participants can recall clearly |
| Consider natural language | AI performs best when prompts sound like real human speech |
| Test your questions aloud | If it sounds awkward or unclear when spoken, it will likely confuse both the AI and the participant |
Examples of Well-Written Task Questions
| Poor Example | Improved Version |
|---|---|
| “Do you think the checkout was easy and intuitive?” | “What was your experience using the checkout process?” |
| “What do you think about the brand’s new logo and advertising campaign?” | “What do you think about the brand’s new logo?” + “What’s your impression of their recent ad campaign?” |
| “Why do you love using this app?” | “How would you describe your experience using the app?” |
Custom Follow-Up Question Instructions
Why it matters: In addition to the Activity Goal, you can guide how the AI asks follow-ups. Clear instructions here help the Interview Agent probe in the style and direction you want, while staying within system limits.
Best practices:
- Keep it focused: Choose one or two main priorities for follow-ups (e.g., "ask for examples" or "probe for emotions").
- Stay simple: If you need a complex branching path, break it into multiple Task Questions instead of complex multi-step instructions.
- Encourage depth, not breadth: Ask the bot to go deeper on one angle, rather than skimming multiple unrelated points.
Examples:
- ✅ “Encourage participants to share detailed stories and probe for emotional reactions.”
- ✅ “Ask for specific examples if participants give general answers.”
- ❌ “Explore every possible reason someone might switch brands, covering price, quality, trust, packaging, ads, and word of mouth.” (Too broad—better handled by multiple questions.)