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Mobile App Satisfaction & Feedback Survey

Measures how satisfied users are with your app, where they hit friction, and which improvements matter most — for product and mobile teams tracking release health. An AI follow-up interview digs into the story behind each user's satisfaction score, surfacing the specific moment or feature that shaped it.

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Sample questions

A preview of what’s in the template. Every question is editable before you launch.

12 questions · ~7 min
Q01
Message

Thanks for taking a moment to share feedback on the app! This will take about 4-5 minutes and helps us decide what to fix and build next.

Q02
Opinion ScaleRequired

How likely are you to recommend this app to a friend or colleague?

Scale: 0 – 10
Min:Not at all likelyMax:Extremely likely
Q03
Rating ScaleRequired

Overall, how satisfied are you with the app based on your experience in the last 30 days?

Range: 1 – 5
Min:Very dissatisfiedMax:Very satisfied
Q04
Multiple ChoiceRequired

In the last 30 days, how often have you used the app?

  • Multiple times a day
  • About once a day
  • A few times a week
  • About once a week
  • Less than once a week
  • This is my first time using it
Q05
MatrixRequired

How would you rate the app on each of the following?

5 rows × 5 columns
  • Ease of use
  • Speed and performance
  • Design and look and feel
  • Reliability (no crashes or bugs)
  • Value for the price
Columns: Poor · Fair · Good · Very good · Excellent
Q06
Multiple Choice

In the last 30 days, have you experienced any crashes, freezes, or error messages while using the app?

  • Yes, frequently
  • Yes, occasionally
  • Yes, once or twice
  • No
  • Not sure
Q07
Best–Worst Trade-off (MaxDiff)Required

Which of these areas should we prioritize improving? (Template note: replace the placeholder items below with your app's actual feature or improvement list before launching.)

  • (Replace with Feature A - e.g., Search)
  • (Replace with Feature B - e.g., Notifications)
  • (Replace with Feature C - e.g., Checkout flow)
  • App loading speed
  • Visual design and layout
  • Fewer bugs and crashes
  • (Replace with Feature D - e.g., Offline mode)
  • Customer support within the app
Pick best & worst per setBest:Most important to improveWorst:Least important to improve
Q08
AI Interview

Reconstruct the specific experience behind the respondent's satisfaction and recommendation scores: ask what happened the last time they used the app that made them feel that way, and anchor on a concrete moment rather than a general impression. If they flagged crashes/bugs or a low priority area, probe exactly what broke, when, and what they did next (retried, gave up, contacted support). If scores were high, probe what single feature or moment they'd protect if the team could only keep one thing.

Q09
Long Text

Is there anything else about your experience with the app you'd like us to know?

Q10
Multiple Choice

Which age range do you fall into?

  • Under 18
  • 18-24
  • 25-34
  • 35-44
  • 45-54
  • 55-64
  • 65 or older
  • Prefer not to say
Q11
Multiple Choice

How do you identify?

  • Woman
  • Man
  • Non-binary
  • Prefer to self-describe
  • Prefer not to say
Q12
Message

That's everything — thank you for the feedback! Your responses go directly into our product roadmap review to help us fix what's broken and build what matters most to you.

What’s included

  • AI follow-ups

    Adaptive probes on open-ended answers that pull out detail a static form would miss.

  • Attention checks

    Built-in safeguards against rushed answers and low-quality respondents.

  • AI-drafted copy

    Wording, ordering, and branching written by the AI — tuned to your research goal.

  • Auto report

    Themes, quotes, and a plain-English summary write themselves once responses come in.

How it compares

We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.

Why this template

  • Includes an AI follow-up interview that reconstructs the specific experience behind each respondent's satisfaction and recommendation scores, rather than stopping at a static rating.
  • Pairs quantitative measures (recommend likelihood, satisfaction rating, usage frequency, feature-level matrix ratings, crash/error incidence, MaxDiff prioritization) with open-ended probing, so teams get both the 'what' and the 'why' in one flow.
  • Closing long-text and chat-message steps give respondents a natural way to add anything the structured questions missed, which the AI interview can then build on.
  • Runs on QuestionPunk's free tier or $50/mo Business plan with transparent prompts and automated per-response quality scoring — no academic pricing tier, just straightforward access to adaptive interviewing.

SurveyMonkey

Mobile App Survey Template & Questions

A ready-to-field static template covering standard mobile app feedback questions (satisfaction, usage, feature ratings). It's backed by SurveyMonkey's mature survey logic and reporting tools, but the question set itself is fixed once deployed. Good for quick baseline measurement, less suited to uncovering the story behind a given score.

What it does well

  • Well-established survey platform with broad question-type support and analytics
  • Template is purpose-built for mobile app feedback, so it maps closely to this use case
  • Likely integrates with SurveyMonkey's existing reporting and benchmarking features

Where it falls short

  • No adaptive AI follow-up interview — every respondent sees the same fixed question set regardless of their answers
  • No voice AI interview or guided screen-share task option for observing friction directly
  • No published methodology for how responses are scored or synthesized into insights

SurveySparrow

Mobile App Feedback Survey Questionnaire Template

A conversational-style template aimed at collecting mobile app feedback, leveraging SurveySparrow's chat-like survey format for a friendlier respondent experience. It's still a predetermined question flow rather than a dynamically probing interview. Useful for quick, engaging feedback collection but not for deep, respondent-specific follow-up.

What it does well

  • Conversational UI style may improve completion rates compared to traditional grid-style forms
  • Positioned specifically for mobile app feedback within a marketing template category
  • Part of a platform with broader survey distribution and reporting features

Where it falls short

  • Conversational tone does not equal adaptive intelligence — follow-up questions are pre-scripted, not generated from each individual's response
  • No option for AI-moderated voice interviews or guided tasks with screen share
  • No automated per-response quality scoring or transparent prompt visibility

Ready to launch?

Open this template in the editor. Every part is yours to change before the first respondent sees it.

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