40 AI prompts for ASO, Apple Ads and app growth from MobileAction

Compare [APP] with [COMP A], [COMP B] and [COMP C] in the [COUNTRY] App Store to identify additional non-brand search opportunities.

Find relevant keywords where competitors currently rank in the top 10 and [APP] has room to expand its organic coverage.

Prioritize the 10 strongest opportunities using MobileAction search volume, [APP]'s current rank, and available chance scores.

Group the opportunities into meaningful search themes and show which competitors currently have the strongest visibility.

Then recommend metadata opportunities that are justified by the evidence.

Do not force title or subtitle changes for marginal opportunities; use the keyword field or other metadata directions when more appropriate.

Analyze [APP]'s organic search visibility in the [COUNTRY] App Store over the latest complete 30-day period.

Identify the most important non-brand keywords where the app currently ranks well, has made recent ranking gains, or has a realistic opportunity to improve further.

Prioritize up to 10 keywords using current rank, recent rank movement, MobileAction search volume and competitor positioning.

For the strongest opportunities, show which competitors currently rank well and whether they made relevant metadata, screenshot, or app-version changes during the same period.

Also summarize any positive or notable themes visible in recent ratings and reviews.

Finish with three specific ASO actions or tests the team should consider next.

Separate observed MobileAction data from strategic interpretation and do not claim causality.

I manage both [APP A] and [APP B] in the [COUNTRY] App Store.

Use MobileAction MCP to find non-brand keywords where both apps currently rank in the top 50.

Highlight terms where their rankings are within 10 positions of one another.

For each overlapping keyword, compare:
- both organic ranks
- MobileAction search volume
- ratings
- available predicted conversion or max-reach signals
- how closely each app's current positioning matches the search intent

Classify each keyword as:
1. useful portfolio overlap,
2. worth differentiating,
3. unclear from available data.

Do not assume that two rankings automatically mean cannibalization.

For the terms worth differentiating, recommend which app should emphasize each keyword and draft revised metadata directions for both apps.

Do not estimate traffic or visibility gains.

Compare [APP] on the Apple App Store and Google Play in [COUNTRY].

Compare major non-brand keyword rankings, category position, ratings and reviews, current listing copy and recent review themes.

Identify the strongest search themes on each store and the most meaningful store-specific opportunities to expand organic reach.

Use listing copy, verified keyword coverage, competitive positioning and review themes to evaluate plausible explanations, but do not claim they caused ranking differences.

Keep App Store and Google Play metrics separate where definitions or scope may differ.

Finish with up to five store-specific ASO changes [APP] should test, including revised metadata or description copy where justified by the evidence.

Analyze the Google Play long description for [APP] in [COUNTRY] against these priority keywords: [KEYWORD 1], [KEYWORD 2], [KEYWORD 3], [KEYWORD 4].

Retrieve [APP]'s description and the descriptions of [COMP A], [COMP B], and [COMP C] through MobileAction MCP.

Calculate how often each priority term appears in each listing and where it appears.

Treat this as a textual comparison, not as proof of a Google Play ranking factor.

Combine that analysis with the current keyword rankings and search-volume data.

Identify important search themes that [APP]'s listing barely addresses while competitors address them more clearly.

Then draft revised sections of [APP]'s long description that cover those themes naturally.

Show a before/after term-frequency table and explain the rationale.

Find the strongest organic keyword opportunities for [APP] in [COUNTRY].

Start with non-brand keywords where [APP] currently ranks between positions 6 and 50.

For each candidate, retrieve the available MobileAction search volume, chance score, and max-reach, predicted-install, or predicted-conversion estimations where supported.

Create an opportunity score using only those available variables.

Explain the formula clearly and do not present it as an official MobileAction metric.

Rank the top 15 terms and classify them as:
- quick-win candidate
- high-value but competitive
- low priority

Then recommend the five keywords [APP] should prioritize in its next ASO iteration and explain which observable signals drove each recommendation.

[APP] is launching or expanding [FEATURE].

Evaluate the App Store ASO opportunity for this feature in [COUNTRY].

Start with these seed terms: [KEYWORD 1], [KEYWORD 2], [KEYWORD 3], [KEYWORD 4], [KEYWORD 5].

Use MobileAction MCP to expand the research using relevant organic keywords from apps ranking for those searches and major competitors where relevant.

Identify the 10 strongest keywords for the actual feature using MobileAction search volume, chance score, leading ranking apps and [APP]'s current rank.

Prioritize semantic relevance over volume alone.

Then recommend one App Store subtitle direction, one keyword-field direction and three screenshot headlines.

Clearly separate MobileAction evidence from the copy recommendations.

Find [APP]'s most recent meaningful App Store metadata or storefront change in [COUNTRY] that has enough before-and-after data to evaluate.

Identify exactly what changed and when.

Then compare the 14 days before the change with the 14 days after it for the most relevant affected keywords.

Show the metadata change, keyword, pre-change rank, post-change rank, rank movement and search volume.

Use visibility history only if the returned series is usable.

Highlight the keywords with the clearest positive momentum and those that remained broadly stable.

If results are mixed, describe them neutrally rather than forcing a positive or negative conclusion.

Finish with what the team should keep, build on or test next.

Do not claim causality.