ChatGPT for ASO is useful — but only with live store data (summary)
A credited summary of ConsultMyApp’s argument: LLMs help with ideation and drafting, but ASO decisions still require live rankings, search demand signals, and competitive context.
Original article (source): ConsultMyApp — “Chat GPT For App Store Optimization (ASO) - How to REALLY use it!”
This post is a summary with attribution + a backlink.
What ChatGPT is genuinely good for in ASO
The article’s main “yes” is straightforward: LLMs are great at speeding up the messy first draft, like:
- brainstorming keyword themes and angles
- drafting / tightening descriptions
- generating screenshot messaging ideas
Where LLM-only workflows break (the missing inputs)
Their core claim: without live App Store / Play Store signals, you can’t answer the questions ASO work actually depends on:
- Which keywords have meaningful demand now?
- How competitive are they (and who’s winning)?
- Where do you rank today — and how is it changing over time?
- What does the current creative landscape look like in the category?
So you can generate “relevant” ideas, but you can’t reliably prioritize.
A practical workflow that doesn’t overcomplicate things
The useful mental model:
- Use AI to ideate fast (copy, themes, keyword lists).
- Validate with real data (rankings, demand proxies, competitive screenshots).
- Ship the smallest listing change you can measure.
Why it matters
If you skip validation, you can waste weeks optimizing around terms that:
- don’t drive impressions
- are too competitive to move
- don’t match user intent (so conversion tanks even if rankings rise)
Read the original: https://www.consultmyapp.com/blog/how-to-really-use-chatgpt-for-aso-why-you-cant-ignore-live-app-store-data
Want help with ASO?
If you want this implemented for your app, check out our services — or run your workflow in APPlyzer.