QWE AI Academy Two ways people use AI to write App Store descriptions:
Approach A: Paste your app idea into ChatGPT, ask for a description with keywords, copy the output into App Store Connect and Play Console. Done in 5 minutes.
Approach B: Feed the AI the actual character limits, the indexed-vs-not-indexed rules per store, your keyword list, and competitor descriptions – then produce two different outputs, one tuned for Apple and one for Google.
Approach B wins. Not because the AI is smarter in scenario B. Because the App Store and Play Store don’t agree on what a description even does – and a single generic prompt produces text that fights its own ranking on at least one platform.
Why generic AI prompts fail at ASO
The App Store description is not indexed. Not partially indexed. Not indexed with caveats. Apple’s product page documentation confirms the only fields that influence organic search ranking on iOS are the app name (30 chars), subtitle (30 chars), and keyword field (100 chars). The description – all 4,000 characters of it – is a conversion tool, not a ranking tool. So when you ask ChatGPT to “stuff keywords naturally into the description,” you’re optimizing iOS for an algorithm that isn’t reading it.
Google Play is the opposite. Turn out: you should repeat keywords in the long description so Google understands they’re central to your app, with a rule of thumb around 2% density (App Radar academy). Apple’s developer docs, by contrast, explicitly recommend not repeating keywords across fields.
So one AI output can’t serve both. If it reads natural for iOS, it under-indexes on Android. If it’s keyword-dense for Android, it misses the point entirely on iOS – where only the title, subtitle, and that 100-character keyword field matter for search.
Here’s a question worth sitting with before you open any AI tool: if barely 2-3% of App Store visitors even tap “Read more” on the description (per SplitMetrics A/B testing data), and the average store visit runs under 10 seconds with half that time spent on screenshots – what are you actually writing the description for on iOS? Conversion, not search. That reframe changes every prompt you write.
The constraint-first prompt structure
Don’t ask AI to “write a description.” Ask it to fit specific text into specific fields under specific rules. The fields and limits are non-negotiable – so they go into the prompt as hard constraints.
Per Apple’s product page documentation and Google’s Play Console Help (check current docs – these limits have changed before and may again):
| Field | App Store | Play Store | Indexed for search? |
|---|---|---|---|
| App name / title | 30 chars | 30 chars | Yes (highest weight) |
| Subtitle | 30 chars | – | Yes (Apple) |
| Short description | – | 80 chars | Yes (Google) |
| Keyword field | 100 chars | – | Yes (Apple only) |
| Description / long description | 4,000 chars | 4,000 chars | No (Apple) / Yes (Google) |
| Promotional text | 170 chars | – | No |
That promotional text field is worth a separate mention. Apple allows up to 170 characters at the top of the description – designed for timely updates like new features or events – and it can be updated without a new app submission. That’s a tactical field, not a keyword field. One detail most generic prompts never account for.
The actual workflow (copy this)
Run two passes. One per store. Don’t merge them.
Pass 1 – App Store
- Give the AI: your app’s core feature, target user, tone, and 8-12 candidate keywords (with monthly volume if you have it).
- Tell it explicitly: “The description is NOT indexed for search. Do not stuff keywords. Write for conversion.”
- Ask for three components separately: a 30-char subtitle (clear value prop, not the app name), a 170-char promotional text (newsy hook), and a 4,000-char description where the first 200 characters carry the load.
- Separately, ask the AI to pack the 100-char keyword field as a comma-separated list – no keyword repeated, no spaces wasted.
That keyword field is where ranking actually happens on iOS. It’s the prompt that earns its keep on Apple’s platform.
Pass 2 – Play Store
- Same app brief, different rule set: “The long description IS indexed. Target ~2% keyword density for these 3-4 priority keywords. Do not repeat the short description verbatim in the long description.” (Google’s own Play Console Help flags this as a quality issue.)
- Add the banned-words filter – see the next section.
- Ask for an 80-char short description focused on user benefits, and a 4,000-char long description with priority keywords spread throughout the body – including the middle.
That last detail matters more than it sounds. A yellowHEAD study on Google Play indexing (published on their blog; exact date not confirmed – treat as a directional benchmark) found keywords placed in the middle of the long description had a 91% chance of ranking. Keywords from the short description or first line of the description came in at roughly 87%. Most AI prompts dump everything into the opening paragraph. Tell the model to spread keywords across the body.
Three traps AI walks straight into
Banned words. Google Play no longer accepts terms like “free”, “top”, “best”, and “#1” in titles and short descriptions, per AppTweak’s metadata policy analysis. The catch: community reports from the ASO Stack Slack document warnings for words like “first”, “hot”, “bonus”, and “new” regardless of context. ChatGPT will write “the best fitness tracker” without hesitation. You have to explicitly forbid these terms in the prompt – the model has no idea they’re policy violations.
Performance claims. Google’s policy (per Play Console Help, as of 2024) prohibits text indicating store performance or ranking – “App of the year”, “#1”, award references – and also bars promotional pricing language in descriptions. AI generates this kind of copy by default. Strip it out.
Length inflation. AI fills space because you asked it to. Appbot’s 2024 analysis found the average App Store description runs around 2,100 characters; only about 10% of apps use close to the full 4,000-character limit. Set a hard cap in your prompt: “Maximum 2,200 characters. Cut, don’t pad.”
Prompt addition that helps: “Reject any sentence that doesn’t either (a) state a feature, (b) state a user benefit, or (c) include a target keyword. No superlatives, no comparisons to other apps.” It removes most policy-violating phrases automatically – and the output gets noticeably shorter.
A real example: the meditation app
Say you’re shipping a meditation app. Target keywords: meditation, sleep sounds, anxiety relief, breathing exercises.
App Store keyword field (100 chars, no repeats, comma-separated):
meditation,sleep,sounds,anxiety,relief,breathing,calm,mindfulness,stress,focus,guided,timerThat’s 95 characters. No keyword repeats – the title and subtitle hold separate terms. The description doesn’t touch these keywords at all on iOS, because it doesn’t need to.
Play Store long description: the AI distributes “meditation” 4-5 times across ~2,200 characters, not bunched at the top. “Sleep sounds” appears 2-3 times. Middle paragraphs carry their share. The short description (80 chars) is benefit-first – because the yellowHEAD data suggests it has less keyword ranking impact than the body, so it should be written for humans who read it, not for indexing.
Same app, two completely different texts.
Custom Product Pages: where AI actually scales
Apple’s Custom Product Pages and Google Play’s Custom Store Listings let you create multiple versions of your app’s store listing – different screenshots, different text – for different audiences or campaigns. Per Apple’s documentation (as of 2024), these variants can have distinct promotional text and are updatable without a new submission.
This is where AI use in ASO stops being a one-time drafting aid. Generating 5 variants of promotional text for 5 different ad campaigns – “new parents”, “shift workers”, “students before exams” – is a 10-minute job for a model. Route ad traffic to the matching Custom Product Page. The constraint-first prompt structure scales directly here: same rules, different audience brief per run.
That’s the actual use of AI in ASO. Not the first description. The fiftieth.
FAQ
Should I use a specialized ASO AI tool or just ChatGPT?
ChatGPT works fine with the constraints described above. Specialized tools like AppTweak or App Radar add real keyword volume data and competitor scoring – useful once you’re past the first draft, not before.
Does AI-generated text get penalized by app stores?
No store currently detects or penalizes AI-generated text as a category. What gets flagged is the content: banned words, performance claims, keyword stuffing. AI produces all three by default unless you instruct it otherwise. The risk is in the output, not the origin. A human writing “the best meditation app” has the same problem.
How often should I update my description?
No fixed rule exists – community practice varies and neither Apple nor Google publishes a cadence recommendation. For Google Play, small description tweaks let Google re-index, which some ASO practitioners do every few weeks when testing new keyword targets. For Apple, the description isn’t a ranking signal, so update it when features change or when you launch a new Custom Product Page for a campaign. Ratings and download velocity move the needle more than text revisions on either platform.
Next step: open your current Play Store long description, count how many times your top keyword appears in the middle 50% of the text. If it’s zero, that’s your first AI rewrite job today.