Customer analysis sample: great questions for customer interviews that uncover actionable insights

If you’re searching for a customer analysis sample or want to discover great questions for customer interviews, you’re in the right place. Customer interviews are critical for understanding what drives user behavior, shapes satisfaction, and influences business outcomes.

The right questions unveil what makes your product compelling (or not), clarifying product-market fit, key features, and growth levers. AI-powered conversational surveys now make customer analysis scalable—without sacrificing the nuanced insights that traditional interviews deliver. You can try creating one with an AI survey builder to see how natural and effective this approach can be.

25 essential questions for customer analysis interviews

The core of effective customer analysis is asking the right questions—and following up naturally, as a great interviewer would. I’ve organized these 25 questions into five objectives. Each question comes with AI-powered follow-up examples Specific might use, so you’ll collect focused, actionable feedback without extra effort. According to a Forrester study, customer interviews can increase new feature adoption by as much as 40% when paired with targeted follow-up probing [1]. Here’s how to do it right:

• Understanding Customer Needs

Uncover what truly matters to your users and their pain points—with specifics that drive roadmap decisions.

1. What problem does our product solve for you?
   AI follow-up examples:

   • Can you describe a specific situation where our product solved this problem?

   • How did you handle it before using our product?

2. What features do you find most valuable?
   AI follow-up examples:

   • What makes those features stand out to you?

   • Are there features you rarely use? Why?

3. What challenges do you face when using our product?
   AI follow-up examples:

   • Can you share a recent challenge you faced?

   • How did that impact your experience?

4. How does our product fit into your daily workflow?
   AI follow-up examples:

   • What tasks do you use it for most often?

   • Are there tasks you wish it could help with?

5. What other solutions did you consider before choosing ours?
   AI follow-up examples:

   • What made you choose us over those alternatives?

   • How do you compare our product to them now?

• Product Experience & Satisfaction

Gauge not just satisfaction, but what drives positive—or negative—experiences, so you know what to double down on.

6. How satisfied are you with our product’s performance?
   AI follow-up examples:

   • Which aspects contribute most to your satisfaction?

   • Are there areas where you think we could improve?

7. Have you run into any bugs or technical issues?
   AI follow-up examples:

   • Can you walk me through the most recent issue?

   • What was the impact on your workflow?

8. How intuitive is our product's interface?
   AI follow-up examples:

   • Are there features or menus you find confusing?

   • What would make it more user-friendly?

9. How responsive is our customer support?
   AI follow-up examples:

   • Could you share an example of a recent support interaction?

   • What would have improved your support experience?

10. How likely are you to recommend us to others?
    AI follow-up examples:

    • What would you highlight when recommending our product?

    • Do you have any hesitations or concerns?

• Decision-Making Process

Get insight into buying motivations and objections, to improve positioning—vital for both sales and retention.

11. What factors influenced your purchasing decision?
    AI follow-up examples:

    • Which of these was most important?

    • Was it a particular feature, benefit, or something else?

12. Who else was involved in the decision?
    AI follow-up examples:

    • What were their main concerns or priorities?

    • How did you address any disagreements?

13. What was your biggest hesitation before buying?
    AI follow-up examples:

    • How did you overcome it?

    • Could we have addressed it more effectively?

14. How did you first discover our product?
    AI follow-up examples:

    • What sources of information influenced you most?

    • Did any messaging or materials stand out?

15. What criteria did you use to evaluate solutions?
    AI follow-up examples:

    • Which criterion mattered most?

    • How does our product measure up?

• Value Perception

Learn what customers value—and what convinces them your product is worth the price (or not).

16. Do you feel you get good value for the price?
    AI follow-up examples:

    • Which features or factors drive this?

    • Is anything missing at your current price point?

17. How has our product impacted your productivity?
    AI follow-up examples:

    • Can you estimate time or cost savings?

    • On which tasks have you seen the biggest gains?

18. What real benefits have you seen since using our product?
    AI follow-up examples:

    • Could you share an example or story?

    • How has it affected your broader goals?

19. Compared to competitors, how do we rate in value?
    AI follow-up examples:

    • Are there areas where we stand out or fall short?

    • What tips the balance in our favor?

20. Did you experience any unexpected benefits?
    AI follow-up examples:

    • What surprised you most?

    • How did that influence your satisfaction?

• Future Expectations

Reveal where you can grow with your customers—and safeguard against churn before it starts.

21. What additional features or improvements would you like to see?
    AI follow-up examples:

    • How would those change your experience?

    • Are any current limitations holding you back?

22. How do you see your needs changing next year?
    AI follow-up examples:

    • How can our product adapt to keep up?

    • Any trends or challenges we should know about?

23. Are you interested in beta testing new features?
    AI follow-up examples:

    • What would motivate you to participate?

    • Any specific areas you’d want to test?

24. How can we better support your long-term goals?
    AI follow-up examples:

    • What resources would be most helpful?

    • How could we align more closely with your objectives?

25. What might make you discontinue using our product?
    AI follow-up examples:

    • Are there specific concerns that could drive that decision?

    • How can we prevent this from happening?

AI-driven, contextual follow-ups—like those enabled by Specific’s automatic AI follow-up questions—let you explore customer answers with organic, relevant probing. That’s how breakthrough insights surface, even at scale.

Choosing between in-product and landing page delivery

Deciding whether to deliver a customer analysis interview inside your product or via a landing page depends on your goals and audience. Here’s a quick breakdown:

Timing is important: in-product surveys (embedded conversational surveys) are best for immediate, contextual feedback—think onboarding, quick NPS checks, or feature usage moments. Landing page surveys (survey on a landing page) excel in scheduled projects, research beyond your active user base, or referrals from email/social channels.

Both support dynamic, AI-driven interviews and conversation—choose based on whether you need in-the-moment feedback or a wider, scheduled reach. Mix and match as your needs evolve.

Analyzing customer responses with AI

Analyzing responses from 50, 100, or hundreds of conversations can feel overwhelming. AI-powered tools surface common themes and patterns instantly—freeing you to drive action instead of wrangling spreadsheets. Research by McKinsey shows that teams using AI for open-ended survey analysis gain “insight-to-action speed 2-3x faster than with manual coding” [2].

With Specific’s AI survey response analysis, I can just type a prompt and get powerful, conversational insights:

What are the top feature requests mentioned across all customer interviews?

What are the most common reasons customers consider churning?

Segment feedback by user persona: What needs do enterprise users raise that SMB users don’t?

What are the strongest signals of product-market fit emerging from recent interviews?

Analysis chats let different teams drill into what matters for them—retention, bugs, pricing, onboarding, and more. AI-generated summaries distill even long, messy answers so product managers and execs can scan what matters. This replaces tedious manual tagging, categorization, or spreadsheet work, making high-volume feedback truly actionable.

Best practices for customer interview surveys

If you want the best insights, don’t just fire off random questions. Here’s how I approach crafting high-impact surveys:

• Define your objective so every question