The task
You’re submitting a new app or refreshing an existing listing. The store page has roughly six surfaces that matter: app name, subtitle (30 chars on iOS), promotional text (170 chars), description (4,000 chars but only the first 2-3 lines show), keywords field, and screenshot copy. Writing all of these from scratch eats half a day and is full of fiddly character limits.
A focused AI workflow gets you a first-draft listing in 20 minutes, leaving time for A/B testing variations of the subtitle and first description line — where most of your conversion lift actually lives.
When AI is the right tool
Use AI when you have a clear sense of who the app is for and what the top three features deliver. Models are excellent at compressing benefit language to fit character caps, generating keyword expansions, and producing 3-5 subtitle variants for A/B tests.
It’s also useful for localizing copy: keep your English source clean, then generate per-market variants with cultural nuance hints.
When not to rely on AI alone
Don’t trust AI to know current ASO best practices for your specific category — those shift quarterly. Pair AI drafts with a manual review of three competitors who currently rank well for your target keywords.
Also avoid AI-generated keyword fields for regulated categories (finance, health) without a compliance review.
What to feed the AI
- App name + tagline
- Top 3 features, each with the user benefit, not the technical feature
- Target audience (specific: “freelance designers tracking invoices,” not “small businesses”)
- 5 competitors and one thing each does well
- Two adjectives for tone (e.g., “calm + capable,” not “innovative”)
Copy-ready prompt
You are an App Store optimization writer. Produce a full English listing.
App: {name}, {tagline}
Top 3 features (feature → benefit):
- {feature_1}: {benefit_1}
- {feature_2}: {benefit_2}
- {feature_3}: {benefit_3}
Audience: {specific_audience}
Competitors I respect: {comp_list}
Tone: {two_adjectives}
Output:
1. Subtitle: 5 variants, each under 30 characters, leading with a benefit verb.
2. Promotional text: 3 variants, each under 170 characters.
3. Description:
- First 2 lines: punchy, benefit-first, no "Welcome to..."
- 3 short paragraphs covering the three features
- 4-6 bullet list of additional features
- Closing CTA (one line)
4. Keywords field: 100 characters, comma-separated, no spaces, no repeats of words from the app name.
5. Screenshot caption ideas: 5 lines, each under 60 characters.
Avoid: superlatives without proof, "revolutionary," "next-generation," any feature without a benefit.Recommended output structure
Each surface labeled clearly with character counts. Three to five variants per critical surface (subtitle, promo text, first description line) so you can A/B test.
The bullet list of features should not be a wall of icons in prose form — it should look scannable.
How to check the output
Manually count characters on the subtitle and promotional text variants (models miscount). Check that every feature in the description is paired with a user benefit. Search the App Store for your top 3 keywords and confirm at least one competitor in the top 10 uses similar phrasing.
Read the first two description lines on a phone — that’s the only part most users see before tapping “more.”
Common mistakes
- Listing features without benefits (“Cloud sync” instead of “Pick up where you left off on any device”)
- Keyword stuffing in the description (Apple ignores it; users find it spammy)
- Subtitles that are taglines, not benefits (“The future of notes” doesn’t help)
- Same description for iOS and Android — they reward different copy patterns
- Skipping screenshot captions, which are often more read than the description
Next steps to keep improving
A/B test one element at a time — usually subtitle first. Apple Connect now lets you run native experiments; treat each test as a 2-week commitment with a single hypothesis. Re-prompt the model with the winning subtitle to align the rest of the listing.
Practical depth notes
For How to Write App Store Copy With AI That Converts Page Visitors, the difference between a usable AI result and a generic one is the input packet. Give the model the audience, the current draft or raw material, the desired format, the decision you need to make, and two examples of what good and bad output look like. Ask it to preserve facts first, then improve structure or wording second.
After the first response, do a separate review pass. Look for missing constraints, invented details, weak calls to action, and language that sounds plausible but does not match the real situation. The best final output should be easy to use immediately: clear owner, clear next step, and no hidden assumption that someone else has to untangle.
FAQ
- How long should a description actually be? Most users tap “more” rarely. Make the first 2-3 lines and bullets do the heavy lifting; the rest is for the curious and for keyword surface.
- Does AI help with iOS keyword field strategy? It can expand and dedupe candidates, but use a real ASO tool to validate search volume.
- What about localization? Localize copy per top 5 markets with native-fluent review, not just machine translation.
Related
For Apple-specific patterns, see app store listing prompts, boost on-page conversion with app store screenshot copy prompts, and align the strategic story using product positioning prompts.