What the Evidence-led audience–market fit analysis across US, UK, Germany and Türkiye prompt does

Act as a cross-market game audience researcher and risk analyst who tests market-fit hypotheses without stereotyping players.

The prompt will, at minimum:

  • Build a comparable evidence base for US, UK, DE and TR from supplied research, store data, reviews, community feedback and current public sources, recording date, sample, platform and confidence
  • Separate observed behaviour, cultural context, product-stage limitation, platform mix and monetization effect; never convert nationality into a behavioural fact
  • Define audience hypotheses by player job, motivation, genre literacy, access, social context and purchase barrier rather than broad demographic labels alone
  • Assess localization, store positioning, pricing, community, age-rating, child-safety, monetization and platform-policy risks market by market and flag mandatory specialist review
  • Produce fit scores only from explicit dimensions and evidence weights, show uncertainty and counter-evidence, and recommend low-cost validation experiments before major investment

Who it is for

Gökhan Güzel's games prompt for ChatGPT users: marketers, founders, agencies and consultants who need an auditable, evidence-based deliverable instead of generic advice.

What you get

  • Cross-market evidence and comparability report
  • Audience hypothesis and anti-stereotype framework
  • US, UK, DE and TR fit scorecards
  • Risk, compliance and localization matrix
  • Validation experiments and investment decision register

Variables

PlaceholderPurpose
{{age_rating}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{audience_hypotheses}}Audience research, hypotheses, signals or settings
{{community_feedback}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{cultural_constraints}}Approved rule, policy or constraint; state owner, version, scope, jurisdiction and effective date
{{decision_goal}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{game_genre}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{game_name}}Verified identifier or text value; state exact spelling, source, status and validity scope
{{gameplay_summary}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{localization_assets}}Media or asset input; state filename, page/frame/time segment, source, usage rights and review date
{{monetization_model}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{platform_mix}}Numeric value or table; state formula, numerator, denominator, unit, currency, tax treatment, period and source
{{player_research}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{product_stage}}Verified identifier or text value; state exact spelling, source, status and validity scope
{{store_data}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance
{{target_markets}}Target markets

How to use

Copy the prompt with the button above, replace every {{placeholder}} with your verified data, and paste it as the first message in a new ChatGPT conversation. The prompt runs a short question gate first; answer it, then the deliverable is produced.

Run Evidence-led audience–market fit analysis across US, UK, Germany and Türkiye in ChatGPT

Open a new ChatGPT chat, paste the filled-in Evidence-led audience–market fit analysis across US, UK, Germany and Türkiye prompt and answer the short question gate. ChatGPT then returns the executive decision, the evidence ledger and the task-specific tables in one reply.

Source

Original file in the multilingual prompt library on GitHub: