Why this is hard to get right
The Real Cost of Generic Store Copy
Maria is a mobile growth marketer at a mid-size fintech company. Her team ships app updates every three weeks, and every update means rewriting the App Store and Google Play listings. She's done it dozens of times. She knows the drill.
But this release is different. The team rebuilt the onboarding flow, cut account setup time by 40%, and added biometric login. These are real improvements. Users will notice. And yet, when Maria sat down to write the listing update, she spent 90 minutes producing copy that felt exactly like what was already live.
Her first attempt read like a changelog. "Version 4.2 adds biometric login and a streamlined onboarding experience." Technically accurate. Completely unconvincing.
Her second attempt swung the other way. She tried making it conversational, but without character counts in front of her, the iOS subtitle ran 44 characters and got rejected. The release notes hit 220 characters. Another rejection. She rewrote everything from scratch.
The real problem wasn't her writing ability. Maria is a strong communicator. The problem was that writing app store copy requires you to hold six or seven constraints in your head simultaneously: platform character limits, keyword priority, benefit framing, compliance guardrails, brand voice, and conversion goals. Forget any one of them and you're rewriting.
When she finally structured her request properly — defining the audience (first-time investors aged 25-40), the job-to-be-done (manage savings without needing financial expertise), the new features in user-benefit terms, a concrete proof point (40% faster setup), a keyword priority list, and exact deliverable specs — the output changed completely.
The AI returned an iOS subtitle under 30 characters, a short description at 78 characters, a full description with five punchy benefit bullets, and release notes at 148 characters. Everything was on-spec on the first pass. The copy led with the outcome (faster setup, less friction) rather than the feature (new onboarding flow). It embedded her priority keywords naturally. It matched her brand's confident, plain-English voice.
Maria's revision time dropped from 90 minutes to under 15. More importantly, the copy actually differentiated the app instead of describing it. That's the gap a well-structured prompt closes: not just saving time, but producing listing copy that gives someone a real reason to tap "Get."
App store copywriting is a specialized discipline. The best practitioners think like direct-response writers constrained by a billboard. A prompt that captures audience, proof points, keyword intent, and platform specs doesn't just help AI — it forces you to think like an ASO professional before you write a single word.
Common mistakes to avoid
Describing Features Instead of Benefits
Listing what changed ("new biometric login") without framing the user outcome ("sign in 3x faster, no password needed") produces copy that reads like internal release notes. App store visitors decide in seconds. They need to know what the app does for them, not what your engineers built. Always translate features into jobs-to-be-done before writing.
Omitting Platform Character Limits
iOS and Google Play have strict, different character limits for each field. Without specifying them in your prompt, the AI will write to a comfortable length — which is almost always wrong. Rejected submissions cost you resubmission cycles. Always include exact limits: iOS subtitle at 30, short description at 80, full description at 1,700, release notes at 170.
Skipping Keyword Priority Order
Asking for "relevant keywords" gives the AI discretion over which terms appear prominently. But keyword placement in the first 167 characters of your description carries the most weight for ASO. If you don't specify priority order, high-value terms often end up buried. Provide a ranked list so the AI places them where they perform.
Leaving Tone Undefined
"Make it sound good" is not a tone directive. Without clear guidance — friendly, clinical, bold, reassuring — the AI defaults to generic marketing language that fits no brand in particular. Tone consistency across releases builds user recognition. Specify two or three adjectives that match your existing brand voice so every update sounds like you.
Ignoring Compliance Boundaries
Apps in regulated categories — health, finance, legal — risk store rejection or account penalties from unsubstantiated claims. Phrases like "guaranteed results" or "clinically proven" can trigger review flags. Failing to set claim boundaries in your prompt means the AI won't either. Explicitly state what types of claims to avoid to protect your listing.
Treating All Platforms as Identical
iOS App Store and Google Play have different field structures, indexing behaviors, and audience expectations. Google Play indexes the full description for search; Apple relies more on the subtitle and keyword field. Asking for a single generic description for both platforms usually means neither is optimized. Prompt for platform-specific variants with separate character specs.
The transformation
Write new app store description and release notes for my app update. Make it sound good and include keywords.
You’re a mobile growth copywriter. Create updated App Store + Google Play listing copy for **[App Name]**, a **[category]** app. 1) Audience: **[who]**. Main job-to-be-done: **[goal]**. 2) What’s new: **[feature 1]**, **[feature 2]**, **[fixes]**. 3) Proof: **[metric like “cuts setup time by 30%”]**. 4) Keywords to include (priority order): **[k1, k2, k3]**. Deliver: - **iOS subtitle (≤30 chars)** - **Short description (≤80 chars)** - **Full description (max 1,700 chars)** with 5 benefit bullets - **Release notes (120–170 chars)** Use a **clear, friendly, confident** tone. Don’t make medical or financial claims.
Why this works
Role Assignment Primes Output
The After Prompt opens with "You're a mobile growth copywriter." This isn't decoration. Assigning a specialist role shifts the AI's register toward conversion-focused, ASO-aware language instead of generic marketing copy. It sets expectations for what a competent output looks like before a single deliverable is specified.
Structured Inputs Eliminate Guessing
The numbered input format — audience, what's new, proof, keywords — mirrors how a professional ASO brief is structured. Each field removes one variable the AI would otherwise guess. Without the audience definition and job-to-be-done, the AI can't write benefit-led copy. Without the proof point, it can't write outcome-driven bullets.
Explicit Deliverables with Specs
The After Prompt requests each output field by name with its character limit: iOS subtitle at 30 chars, short description at 80 chars, full description at 1,700 chars, release notes at 120-170 chars. Naming deliverables with hard constraints eliminates the most common failure mode — copy that reads well but gets rejected at submission.
Keyword Priority Order Controls Placement
The prompt asks for keywords "in priority order," which signals to the AI that the first keyword should appear earliest in the description. This mirrors how ASO indexing actually works — earlier placement carries more weight. Without the priority instruction, the AI distributes keywords based on sentence flow, not search performance.
Compliance Guardrail Reduces Risk
The final line — "Don't make medical or financial claims" — acts as a hard constraint. This single instruction prevents a whole class of output errors that could trigger store rejection or legal review. It's domain-specific risk reduction that a vague prompt like "make it sound good" can never provide.
The framework behind the prompt
The Theory Behind App Store Copywriting
App store optimization (ASO) sits at the intersection of search engine optimization, direct-response copywriting, and conversion rate optimization. Understanding why each element matters helps you build prompts that actually move the needle.
Keyword indexing works differently by platform. Google Play indexes the full description, so keyword placement and density within the body copy directly affects search ranking. Apple's App Store indexes the app name, subtitle, and a separate keyword field — the description itself is not indexed. This means the same copy goal (rank for a search term) requires a different strategy on each platform.
The "above the fold" problem is real. On iOS, only the first 167 characters of your description appear before the "more" link. On Google Play, users see the first 80 characters of the short description. These opening lines function like a headline and subheadline in direct-response advertising — they either earn the click or lose the visitor. The AIDA framework (Attention, Interest, Desire, Action) applies here: your opening must grab attention and create interest before the user decides whether to read on.
Jobs-to-be-done theory (developed by Clayton Christensen) is especially relevant for app store copy. Users don't download apps — they hire apps to accomplish a specific job. Copy that names the job ("manage 10 clients without missing a follow-up") outperforms copy that describes the tool ("a client management app"). The After Prompt on this page builds this in by requiring the "main job-to-be-done" as a structured input.
Proof points outperform feature lists. Behavioral economics research on persuasion consistently shows that specific, credible evidence (a metric, a user count, a rating) converts better than descriptive language. "4.8 stars from 200,000 users" outperforms "the highest-rated app in its category."
Structuring your AI prompt to capture all of these elements — platform, audience, job, proof, keywords, and constraints — is the difference between copy that fills a character limit and copy that earns an install.
Prompt variations
You're an app store copywriter for a productivity SaaS tool used by operations teams at mid-size companies.
Write release notes for version 3.7, targeting users who value workflow speed and reliability.
What changed:
- Fixed a sync delay that caused tasks to appear out of order
- Added bulk-assign feature for team leads
- Improved load time on project dashboards by 25%
Tone: Direct, confident, and brief — no marketing language.
Deliverable:
- iOS release notes (120–170 characters)
- Google Play release notes (under 500 characters with a short header line)
Lead with the most user-visible improvement. Don't start with "Bug fixes and improvements."
You're a mobile ASO specialist.
Write a full app store listing for a new iOS and Android app called DayStack — a daily planning app for freelancers who manage 3-10 clients at once.
Audience: Independent consultants and freelancers, aged 28-45, who lose time switching between tools and miss follow-ups.
Core value: One daily view that surfaces your most urgent client tasks and unpaid invoices.
Proof point: Beta users reduced missed follow-ups by 60% in the first month.
Keywords (priority order): freelancer planner, client task manager, daily schedule app, invoice tracker.
Deliver:
- iOS app name (≤30 chars)
- iOS subtitle (≤30 chars)
- Short description (≤80 chars)
- Full description (≤1,700 chars) with 5 benefit bullets
- Release notes for v1.0 (120–170 chars)
Tone: Energetic but grounded. Avoid startup clichés.
You're a mobile growth copywriter specializing in English-language app store localization.
Adapt the existing US English listing for a meditation app called ClearMind for the UK market.
App category: Wellness and mental health Audience in UK: Adults 30-55 managing work stress, familiar with NHS mental health framing.
Localization requirements:
- Use British English spelling (favour, recognise, licence)
- Replace references to "therapy" with "mental wellness support" to stay within UK advertising standards
- Swap any US-specific idioms for neutral or UK-appropriate equivalents
Keywords for UK store (priority order): stress relief app, mindfulness UK, mental wellness app, breathing exercises.
Deliver:
- iOS subtitle (≤30 chars)
- Short description (≤80 chars)
- Full description (≤1,700 chars) with 5 benefit bullets
- Release notes (120–170 chars)
Maintain a calm, reassuring tone throughout. Avoid clinical language.
You're a conversion-focused app store copywriter running an A/B test.
Create two distinct variants of the short description and first 167 characters of the full description for a home workout app called BurnForm.
Audience: Adults 25-40 who have tried and abandoned gym memberships. Primary keyword: home workout app Proof point: 4.8 stars, 200,000 active users.
Variant A: Lead with social proof and community angle. Variant B: Lead with time efficiency and no-equipment angle.
Constraints:
- Short description ≤80 chars per variant
- Opening 167 chars of full description ≤167 chars per variant
- Both variants must include the primary keyword in the first sentence
Label each variant clearly. Note the core psychological trigger each one targets.
When to use this prompt
Mobile Growth Marketers
Refresh store copy before a paid campaign to improve conversion rate from view to install.
Product Managers
Translate release changes into user-facing benefits for each version update.
Customer Success Teams
Align store messaging with top support wins and common customer objections.
Engineers Shipping Weekly Releases
Generate consistent, accurate release notes that stay within platform limits.
Founders of Early-Stage Apps
Test positioning fast by creating multiple store copy variants from one prompt.
Pro tips
- 1
Replace feature lists with outcomes so the copy explains why users should care.
- 2
Provide your top 3 competitor phrases so you can differentiate without copying.
- 3
Set your primary conversion goal, like installs, trials, or sign-ups, so the CTA fits.
- 4
Add localization details, like region and spelling rules, so the copy matches your market.
Once you've mastered the core prompt structure, these techniques push results further:
Front-load your primary keyword in the first 167 characters. Apple and Google both weight the opening section of your description more heavily for indexing. Structure your prompt to explicitly place Keyword 1 in the opening sentence.
Use the "3-3-3 rule" for benefit bullets. Each bullet should be: 3 words for the feature, 3 words for the benefit, and 3 words for the outcome. Example: "Biometric login — instant access — no password needed." This keeps bullets scannable and outcome-oriented.
Request multiple subtitle variants. The iOS subtitle is only 30 characters, but it carries significant keyword weight. Ask for 3 subtitle options targeting different keyword angles (use case, audience, or outcome) so you can test which drives more views-to-taps.
Add a "voice consistency" anchor. Include one sentence from your existing listing in the prompt and add: "Match the tone and reading level of this sentence." This anchors new copy to your established brand voice rather than defaulting to generic app store language.
Separate keyword stuffing from natural flow. Prompt the AI to embed keywords naturally first, then as a second pass, confirm keyword placement without repeating any keyword more than twice. Over-repetition triggers spam filters and reads badly to human reviewers.
Use this reference when building your prompts. Exact limits prevent rejections.
Apple App Store:
- App Name: 30 characters
- Subtitle: 30 characters
- Short Description (promotional text): 170 characters (not indexed)
- Full Description: 4,000 characters (not indexed by Apple — keywords go in separate keyword field)
- Release Notes: 4,000 characters
- Keyword Field (separate): 100 characters total
Google Play:
- App Name: 50 characters
- Short Description: 80 characters (indexed)
- Full Description: 4,000 characters (indexed — keyword placement matters)
- Release Notes ("What's New"): 500 characters
Key differences to address in prompts:
- Apple indexes keywords from the dedicated keyword field, not the description. Google Play indexes the full description. This means keyword density matters far more for Google Play copy.
- Apple's promotional text (170 chars) is not indexed but shows above the fold — treat it as ad copy, not SEO copy.
- Always specify which platform each deliverable targets so the AI applies the right constraints and optimization logic.
Generating good copy is step one. Knowing whether it's working is step two.
Use Apple's Product Page Optimization (PPO) and Google Play Store Listing Experiments to run controlled tests. Each platform allows you to test alternate copy variants against your default listing with real traffic splits.
What to test first:
- Subtitle vs. subtitle: Test a use-case framing ("Task Manager for Teams") against an outcome framing ("Hit Deadlines Together")
- First 167 characters: The content visible without tapping "more" — test benefit-led vs. social-proof-led openings
- Release notes: Test action-oriented language vs. conversational updates to measure repeat-opener rates
Prompt-based iteration: After your first test, take the winning variant back to your prompt. Add: "Here is our current top-performing short description: [paste text]. Write 3 new variants that keep the same keyword placement but test a different primary benefit."
Minimum test duration: Run listing experiments for at least 7 days to account for day-of-week traffic variation. Aim for 1,000+ impressions per variant before drawing conclusions.
Track conversion rate (views to installs), not just installs. Copy quality shows up in conversion rate. If installs rise but views rise proportionally, the gain came from traffic — not copy.
When not to use this prompt
Avoid this prompt pattern in these situations:
-
Your app has no differentiated value yet. If you can't complete the "proof point" or "job-to-be-done" fields with real specifics, the listing copy will be hollow regardless of how well it's structured. Fix the positioning first, then write the copy.
-
You're in an active App Store review dispute. During a compliance review or rejection appeal, copy decisions should go through legal or compliance review, not AI generation. The prompt includes guardrails, but it's not a substitute for legal counsel in regulated categories.
-
You need deep localization, not translation. This prompt structure handles English-language copy well and can adapt for UK vs. US English. But true localization for non-English markets — where cultural idioms, search behavior, and platform norms differ significantly — requires native-speaker review that the prompt alone can't replace.
-
You're replicating an existing competitor listing. Using this prompt to reverse-engineer a competitor's copy structure is a misuse that risks both legal exposure and ASO penalties. Use competitor research for differentiation context only, not as copy input.
Troubleshooting
AI output consistently exceeds character limits despite specifying them
Add a self-verification step to your prompt: "After writing each field, count the characters and state the count in brackets." This forces the model to audit its own output. Also reframe limits as hard rules: "The iOS subtitle must be 30 characters or fewer — do not exceed this under any circumstances."
Copy sounds generic and reads like every other app in the category
Add differentiation anchors to your prompt. Include: "Here are 3 phrases my top competitors use that I want to avoid: [list them]. Position the copy to claim territory they don't." Also add your brand's one-sentence positioning statement so the AI has a specific angle to write from, not just a category to describe.
Release notes start with 'Bug fixes and performance improvements'
Add an explicit instruction: "Never write 'bug fixes and performance improvements' or any equivalent phrase." Then instruct: "For every fix or improvement, describe the user-visible outcome, not the technical change. Start with the most user-noticeable improvement." Providing 2-3 example release notes in your preferred style also calibrates the output fast.
Keywords appear awkwardly forced into sentences
Separate keyword placement from copywriting in two passes. First prompt: "Write the full description naturally without worrying about keywords." Second prompt: "Now revise this description to include these keywords in priority order, ensuring each appears in a grammatically natural sentence: [list]." Two-pass prompting produces more fluent keyword integration than single-pass.
Output doesn't match the brand's existing voice
Paste your two best-performing existing sentences into the prompt and add: "Match the reading level, sentence length, and tone of these examples exactly." If you have a brand voice guide, include its 3-5 core principles directly. Avoid adjectives like 'professional' or 'friendly' alone — they're too broad. Use examples instead.
How to measure success
How to Evaluate Your App Store Copy Output
Before publishing, run your AI output through this checklist:
Compliance checks:
- iOS subtitle is 30 characters or fewer (count manually — don't trust the AI's count)
- Short description is 80 characters or fewer
- Full description is under 1,700 characters for safe rendering across devices
- Release notes are between 120 and 170 characters
Quality signals:
- The first sentence names the user's job-to-be-done, not a feature
- At least one proof point appears in the first 167 characters or the first benefit bullet
- Primary keyword appears in the opening 167 characters of the full description
- Every benefit bullet states an outcome, not a feature name
- No claims require substantiation you can't currently support
Brand fit:
- Read the copy aloud — it should sound like your brand, not a generic SaaS company
- Compare tone against your existing best-performing listing
- Check that no competitor's distinctive phrases appear verbatim
Now try it on something of your own
Reading about the framework is one thing. Watching it sharpen your own prompt is another — takes 90 seconds, no signup.
Turn your release notes and feature list into conversion-ready store copy that fits every character limit.
Try one of these
Frequently asked questions
Update your full description and subtitle with every significant release — major features, UX overhauls, or new use cases. Update release notes with every version push. For ASO purposes, testing new copy variants every 60-90 days is a reasonable cadence. Stale listings signal low activity to stores and fail to match evolving search behavior.
Not directly. Google Play indexes the full description for keyword ranking; Apple relies more on the subtitle and a separate keyword field. Character limits also differ. Use the same prompt structure but request platform-specific outputs. The After Prompt on this page already does this — it requests both iOS subtitle and short description as separate deliverables with their own specs.
Add a compliance constraint line to the prompt. Be explicit:
- For health apps: "Avoid any claims of diagnosis, treatment, or medical efficacy."
- For finance apps: "Do not imply guaranteed returns or personalized financial advice."
- For both: "Flag any sentence that could require substantiation before publishing." This forces the AI to flag risky language rather than bury it in polished copy.
This is a common issue. First, verify you stated the limit as a hard maximum, not a suggestion. Reframe as: "The iOS subtitle must be exactly 30 characters or fewer — count carefully." If it still fails, add: "After writing each field, count the characters and state the count." This self-verification step dramatically improves compliance with length constraints.
Yes, with a specific instruction. Include 2-3 competitor names and add: "Do not copy their phrasing, but note where our positioning should differentiate." This gives the AI contrast context without copying. Alternatively, include 2-3 phrases your competitors use that you want to avoid, so your copy actively claims different territory.
Never write "Bug fixes and performance improvements" — it wastes the release notes field entirely. Translate every fix into a user-visible outcome:
- "Fixed sync delay that caused tasks to appear out of order" beats "Fixed sync bug"
- "Faster load times on the dashboard" beats "Performance improvements" If there are truly no user-facing changes, describe the reliability win: "Smoother experience with fewer interruptions."
Yes. The core structure transfers — audience, features as benefits, proof points, keywords, character limits. You'll need to adjust the deliverable specs for each platform. Amazon Appstore uses a short description (170 chars) and long description (4,000 chars). Samsung Galaxy Store follows Google Play conventions. Add the platform name and its specific limits to your prompt.