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App Store Optimization (ASO) Content Generator

Generate optimized App Store and Play Store listings: titles, descriptions, keywords, screenshot text, and A/B test variants.

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What this prompt does

This prompt generates optimized store listings for your [app_name] app in the [app_category] category, for both the App Store and Google Play. It produces a 30-character title with the primary keyword, subtitle and short description, a full description at [keyword_density]% keyword density, the 100-character App Store keyword field, [screenshot_count] screenshot caption texts, What's New copy for version [version], promotional text, [ab_variants] A/B test variants for the title and first three lines, and localized versions for [languages]. It targets your [target_keywords], considers [competitors], and includes keyword-research methodology and a ranking strategy.

The structure works because App Store ranking is driven heavily by where keywords sit in the title, subtitle, and keyword field, while installs are driven by screenshots and the first lines users actually read. Treating the listing as a testable surface — with [ab_variants] for the highest-impact elements — moves installs in ways code changes never will, which is why the prompt frames the listing as something to iterate on rather than a form to fill once.

When to use it

  • You're launching [app_name] and need both store listings written from scratch.
  • Your install rate from store impressions is low and the listing may be the cause.
  • You're targeting specific [target_keywords] and need them placed correctly for ranking.
  • You're localizing into [languages] and want consistent, optimized copy per market.
  • You want A/B test variants for the title and opening lines, not a single guess.
  • You're shipping version [version] and need fresh What's New and promotional text.

Example output

Expect a complete listing pack per store: title, subtitle/short description, full description hitting the [keyword_density]% target, the App Store keyword field, [screenshot_count] caption lines, What's New, promotional text, and [ab_variants] variants for the title and opening lines — all translated for [languages]. A short keyword-research methodology and ranking strategy explain why the keywords were placed where they were.

Pro tips

  • Put your strongest term in the title; [target_keywords] ranking weight drops sharply outside the title and subtitle, so don't waste those characters on branding alone.
  • Keep [keyword_density] in a natural range — overstuffing reads as spam to users and can hurt conversion even if it helps a crawler.
  • Write [screenshot_count] captions that sell benefits, not features; the first two or three screenshots do most of the conversion work.
  • Use the [ab_variants] to test the title and first three lines specifically, since those are the elements users see before tapping "more."
  • Localize for [languages] with real translation, not just keyword swaps — install rates suffer when copy reads as machine-translated.
  • Study [competitors] for keyword gaps you can own rather than fighting head-on for terms they already dominate.

Frequently Asked Questions

Does this prompt write listings for both the App Store and Google Play?
Yes. It generates copy for both stores, respecting their different limits — like the App Store's separate 100-character keyword field — so each listing is optimized for its own ranking and character constraints rather than reused verbatim.
How does it use my target keywords?
It places your `[target_keywords]` where ranking weight is highest — primarily the title and subtitle — and works them into the description at a `[keyword_density]`% target. It also outputs a keyword-research methodology explaining the placement choices.
Can it create A/B test variants?
Yes. It produces `[ab_variants]` variations of the title and first three lines, the elements users see before expanding the description, so you can test the highest-impact copy rather than guessing which wording converts best.
Will the localized versions be properly translated?
It generates copy for each of your `[languages]`, but you should have a native speaker review the output. Machine-quality localization can read awkwardly and hurt conversion, so treat the generated translations as a strong draft, not final.
Engr Mejba Ahmed

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Engr Mejba Ahmed

AI Developer · Software Engineer

I'm Mejba — I design and ship production AI systems, automations, and full-stack apps. If you want this turned into a working solution for your team, let's talk.

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Engr Mejba Ahmed

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