QuestionPunkQuestionPunk
Start free
All templates
Product & UX

Video Game Difficulty, Progression & Monetization Feedback

Captures how players actually experience difficulty tuning, progression pacing, monetization fairness, and moment-to-moment session enjoyment. Built for game designers and live-ops teams tracking post-launch sentiment, with an AI follow-up that digs into the specific moment a player felt cheated by difficulty or monetization instead of a generic complaint.

Use this templateBrowse more templates

Sample questions

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

13 questions · ~7 min
Q01
Message

Thanks for taking a few minutes to tell us about your experience with the game! We want to understand what's working and what's frustrating — honest answers help us tune things. Your responses are completely confidential and anonymized. About 5 minutes.

Q02
Multiple ChoiceRequired

In the last 30 days, how often have you played this game?

  • Not at all
  • A few times
  • A few times a week
  • Almost every day
  • Multiple times a day
Q03
Multiple Choice

Which platform do you play this game on most?

  • PC
  • PlayStation
  • Xbox
  • Nintendo Switch
  • Mobile
  • Other
Q04
Rating ScaleRequired

Thinking about a typical play session, how enjoyable is it?

Range: 1 – 5
Min:Not enjoyable at allMax:Extremely enjoyable
Q05
Opinion ScaleRequired

How would you rate the game's overall difficulty balance right now?

Scale: 1 – 7
Min:Far too easyMax:Far too difficult
Q06
MatrixRequired

How much do you agree with each statement about your progression through the game?

4 rows × 5 columns
  • The pace at which I level up or unlock new abilities feels right
  • The rewards I earn feel meaningful
  • I always have a clear sense of what to work toward next
  • My skills feel like they're genuinely improving over time
Columns: Strongly disagree · Disagree · Neutral · Agree · Strongly agree
Q07
Opinion ScaleRequired

How fair does the game's monetization feel relative to what it costs?

Scale: 1 – 7
Min:Very unfair, feels pay-to-winMax:Very fair, doesn't affect gameplay
Q08
Multiple Choice

In the last 30 days, have you spent real money in this game?

  • No, and I don't plan to
  • No, but I've considered it
  • Yes, on cosmetic items only
  • Yes, on items that affect gameplay or progression
  • Yes, on both cosmetic and gameplay-affecting items
Q09
Best–Worst Trade-off (MaxDiff)Required

Which of these changes would matter most to your enjoyment of the game?

  • Reduce the grind or time needed to progress
  • Make monetization less intrusive or pressuring
  • Add more difficulty options or accessibility settings
  • Add more story or level content
  • Improve matchmaking or multiplayer balance
  • Fix bugs and technical issues
  • Improve clarity of goals and tutorials
  • Add more customization options
Pick best & worst per setBest:Most important to improveWorst:Least important to improve
Q10
AI Interview

Probe the specific moment behind the respondent's difficulty and monetization ratings rather than their general opinion. If they flagged the game as too easy or too hard, ask for a concrete example — a boss, level, or mechanic — and whether they quit, looked up a guide, or pushed through. If they rated monetization as unfair or mentioned pay-to-win concerns, ask which specific purchase or mechanic triggered that reaction and whether it changed how they play or spend. Compare in their own words whether difficulty frustration or monetization frustration is more likely to make them stop playing.

Q11
Long Text

Is there anything about difficulty, progression, monetization, or overall enjoyment that we haven't asked about but that matters to you?

Q12
Multiple Choice

What's your age range?

  • Under 18
  • 18-24
  • 25-34
  • 35-44
  • 45-54
  • 55+
  • Prefer not to say
Q13
Message

That's everything — thank you! Your feedback goes directly into how we tune difficulty, pacing, and monetization in future updates.

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

  • Goes beyond a single satisfaction rating by pairing opinion-scale questions on difficulty balance and monetization fairness with a matrix on progression agreement, then an AI follow-up that probes the specific moment a player felt cheated instead of accepting a generic complaint.
  • Includes a max-diff exercise so live-ops teams get a ranked priority list of which changes would actually move enjoyment, not just open-ended wishlist text.
  • Automated per-response quality scoring and an auto-generated report mean design and live-ops teams get synthesized findings, not just raw response exports to manually theme.
  • Structured to separate play frequency, platform, and spend behavior (multiple-choice) from subjective sentiment (rating/rating-scale), so segment-level cuts (spenders vs. non-spenders, platform) are possible without extra setup.

SurveySparrow

Sample Video Game Survey Template

A genuinely on-topic, ready-to-field video game survey template covering general player feedback. It appears aimed at broad satisfaction capture rather than the specific difficulty-tuning and monetization-fairness angle live-ops teams need. Being a static form template, it relies entirely on pre-written questions with no mechanism to dig deeper when a player rates something poorly.

What it does well

  • Quick to deploy as a conversational-style survey template
  • Part of a broader templates library, so it's easy to duplicate and lightly customize
  • Positioned for general audience feedback, which lowers setup friction for simple use cases

Where it falls short

  • No adaptive AI follow-up, so a low difficulty or monetization rating can't be automatically probed for the specific moment behind it — only whatever generic open-text question was pre-written
  • No published per-response quality scoring or automated analysis report tied to game-specific dimensions like progression pacing or monetization fairness
  • No voice AI interview or guided screen-share task option for capturing in-session moments

Ready to launch?

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

Use this templateStart free

Related templates

More studies from the same category.

See all
Product & UX

Pricing Plan Naming and Tier Structure Comprehension Study

Tests whether prospects can correctly interpret your plan names, pick the tier that actually fits them, and understand what changes when they upgrade. Built for pricing and product teams evaluating a new plan lineup before launch, with an AI follow-up that digs into exactly which name or feature line caused hesitation or a wrong guess.

View template
Product & UX

Design & Creative Feedback Review

Structured stakeholder or customer feedback on a design, mockup, or creative asset: first impressions, a click on what draws attention, ratings against the brief, and file upload for marked-up versions. The AI interviewer converts 'I just don't like it' into usable direction.

View template
Product & UX

Unmoderated Usability Test with Screen Share & Voice

A self-serve usability session: participants share their screen, complete guided tasks on your website or prototype while thinking aloud, and the AI moderator watches, prompts, and probes — then debriefs them. You get recordings, transcripts, and task-level analysis without scheduling a single session.

View template
Product & UX

Importance vs. Satisfaction Gap Analysis

Find your biggest opportunities by measuring the same attributes twice — how much each matters, and how well you deliver it today. The gaps become your priority list, and slider matrices keep it fast enough that people actually finish. AI follow-ups dig into the biggest gap each respondent reports.

View template
Product & UX

MaxDiff Feature Prioritization Survey

Force real trade-offs with best-worst scaling: respondents pick the most and least valuable feature in rotating sets, then an AI interviewer probes the reasoning behind their top pick. Produces a true preference ranking instead of everything-is-important rating inflation.

View template
Product & UX

SaaS Plan Change Intent & Migration Blockers Survey

Measures plan-change intent, upgrade/downgrade drivers, and migration friction among active SaaS users. Use with account holders and team leads to identify churn risk, prioritize feature investments, and reduce plan-change barriers.

View template