BusinessBeginnerPreview
App Store Optimization (ASO)
A hands-on, beginner-friendly path to organic app growth: research the keywords your app can rank for, write metadata that the algorithms and humans both reward, design screenshots that convert browsers into installers, build a ratings engine, and prove what works with real store A/B tests.
App founders, marketers, and ASO beginners who own one iOS or Android app and need more installs from search and browse without paying for every download.
Course content
Workbook & downloads
Put the course into practice — a printable workbook plus editable templates you can fill in and reuse.
Preview the workbook
This workbook turns the course into an ASO project for one real app. Work through each section as you build: baseline your listing and read the competition, research and prioritize keywords, write metadata and design converting creatives, then stand up a ratings engine and a disciplined A/B testing loop. Fill every worksheet and template with your own data, and leave all totals, averages, rates, and scores blank until you calculate them yourself.
How App Store Search Actually Ranks
Baseline your current listing, decide whether your problem is visibility or conversion, and read the competitors already winning your terms.
Worksheet: Listing baseline (your before picture)
Pull these from App Store Connect (App Analytics) and Google Play Console (store listing acquisition) and record them with today's date. Leave conversion rate blank until you calculate downloads divided by impressions yourself.
- Date of baseline
- Store (App Store / Google Play / both)
- Impressions (last 30 days)
- Product page views / store listing visitors (last 30 days)
- Downloads / store listing acquisitions (last 30 days)
- Conversion rate (downloads / impressions) — calculate yourself
- Share of downloads from search vs browse vs referral
- Current average rating and total review count
- Current category rank
Exercise: Diagnose visibility vs conversion
Decide which of the two ASO jobs is your real constraint so you fix the right thing first. Answer using your baseline numbers.
- Are your impressions low (a visibility problem) or high with few installs (a conversion problem)?
- How does your conversion rate compare to the typical 2 to 5 percent range and to your visible competitors?
- If visibility is weak, which fields (title, subtitle, keyword field, long description) are underusing keywords?
- Write your single biggest gap in one sentence (e.g. 'page-two rank for our category term and a 3% conversion vs ~6%').
Worksheet: Competitor listing teardown
Pick three to five apps that consistently outrank you for your core terms and record exactly what their listing does. Fill one row per competitor in the linked template.
- Competitor app name
- Exact title (and the keyword inside it)
- Exact subtitle / short description wording
- First screenshot: the one benefit it leads with
- Creative format (portrait / landscape, captioned / raw, video Y/N)
- Average rating and total review count
- Update frequency (how often they ship)
Checklist: Baseline confirmed before any changes
- Impressions, page views, downloads, and conversion rate recorded with a date
- Average rating, review count, and category rank recorded
- Rankings for 10 to 20 target terms captured in an ASO tool or by manual search
- You have decided whether visibility or conversion is your bigger constraint
- Your single biggest gap is written in one clear sentence
ASO Keyword Research
Build a broad keyword universe, score every term on volume, difficulty, and relevance, and allocate the winners to the right metadata field.
Exercise: Build your keyword universe
Gather far more terms than you will use, from real sources, before filtering. Work through each source and add everything you find to the keyword research template.
- List the jobs-to-be-done and outcomes a user wants — in their words, not your feature names.
- Type each seed into App Store and Google Play autocomplete and record every suggestion.
- Harvest terms from competitor titles, subtitles, and reviews, and from your own reviews and support tickets.
- Pair modifiers (free, offline, for kids, daily) with your core nouns to generate long-tail phrases.
Worksheet: Keyword scoring and decision
Score each candidate on the three numbers that decide whether to target it, then assign a decision. Leave any blended opportunity score blank unless your tool provides it — do not invent one.
- Keyword
- Source (autocomplete / competitor / review / tool)
- Search volume or popularity (0-100)
- Difficulty or competition (0-100)
- Relevance (high / medium / low)
- Decision (target now / build toward / skip)
- Reason for the decision
Worksheet: Metadata allocation map
Give every targeted keyword a home in a specific field, never repeating a word across iOS fields. Fill in your actual planned values within each character limit.
- iOS title (<=30 chars): brand + top keyword
- iOS subtitle (<=30 chars): 1-2 keywords as a benefit
- iOS keyword field (<=100 chars): remaining single words, comma-separated, no spaces, no repeats
- Android title (<=30 chars): brand + top keyword
- Android short description (<=80 chars): benefit-led hook with 1-2 terms
- Android long description: priority terms to weave in (and roughly how many times)
- Active target keyword list for this cycle (8-12 terms)
Checklist: Keyword plan ready to ship
- Universe contains 100+ candidate terms grouped into branded vs generic and by theme
- Every candidate is scored on volume, difficulty, and relevance
- At least a few low-difficulty, high-relevance long-tail terms are in the 'target now' set
- No keyword is repeated across the iOS title, subtitle, and keyword field
- The 8 to 12 active target keywords are written down with the field each one lives in
Metadata and Creative That Convert
Write metadata that ranks and reads as a clear promise, then design icon, screenshots, and preview video that win the install in seconds.
Worksheet: Metadata draft (ranks and reads)
Draft the human-facing copy for each field, checking it both ranks and reads as a promise. Stay within each character limit and remember the iOS description is not indexed.
- Title (Brand + one descriptive keyword, <=30 chars)
- Subtitle / short description (benefit + 1-2 keywords)
- First two description lines (the hook that earns the More tap)
- Android long description body (benefit-led, priority terms a few times)
- iOS description body (human-only: value, features, social proof — no stuffing)
- Self-test: would a stranger reading only title + subtitle know what the app does and who it is for? (Y/N)
Exercise: Plan a converting screenshot set
Treat screenshots as your sales page and plan them as a narrative. Decide the message of each frame before any design happens.
- Screenshot 1: what single strongest benefit headline leads, and which screen sits behind it?
- Screenshots 2 to 4: which next benefits, one idea per frame, in what story order?
- Which later frame carries social proof (rating, user count, press) or a call to action?
- Is each headline legible as a small thumbnail in search results (large type, high contrast, one idea)?
Checklist: Creative assets ready and spec-correct
- Icon is simple, distinctive, and legible at small sizes against light and dark backgrounds
- First screenshot leads with the single most important value proposition
- Screenshots are captioned with benefit headlines, not raw unlabeled UI
- Android feature graphic (1024x500) is designed and reinforces the core promise
- App preview video shows real use in the first 3 seconds and works muted
Exercise: Plan your top localization markets
Localization multiplies reach, but only where you do it deliberately. Choose markets and plan real adaptation, not machine translation.
- Which 2 to 3 markets already send you traffic or do you most want to grow?
- For each, will you re-run keyword research natively rather than translating English keywords?
- On iOS, how will you use English (U.S.) and English (U.K.) with different keywords to double English coverage?
- Which screenshot captions, imagery, or colors need cultural adaptation per market?
Ratings, Testing, and Iteration
Stand up a compliant ratings engine, run real store A/B tests one variable at a time, and turn ASO into a measured monthly loop.
Exercise: Design your ratings and reviews engine
Lift rating and volume with a well-timed native prompt and structured responses. Design the trigger and the flow for your app.
- At which success moment will you trigger the prompt (completed action, streak, Nth session) — never first launch?
- Which native API will you use (SKStoreReviewController on iOS, In-App Review on Android), respecting Apple's 3-per-year limit?
- How will a soft pre-prompt route unhappy users to a feedback form while staying compliant (no sentiment gating, no incentives)?
- What is your standard for replying to reviews, and how fast will you respond to negative ones?
Worksheet: A/B test plan and result
Run one disciplined test at a time using the native tools and record it. Leave the lift and significance cells blank until the tool reports them — do not estimate.
- Tool (Google Play store listing experiment / iOS Product Page Optimization)
- Element tested (first screenshot / icon / order / video / subtitle)
- Hypothesis (what you believe will change and why)
- Control conversion rate — record from tool
- Variant conversion rate — record from tool
- Relative lift (%) — calculate yourself
- Reached significance? (Y/N) and visitors per variant
- Decision (ship winner / keep control / inconclusive)
Checklist: Testing discipline upheld
- Only one element is changed per test so the result is attributable
- A written hypothesis exists before the test starts
- The test ran long enough to reach the tool's confidence threshold (often 1 to 2 weeks)
- Highest-leverage assets (first screenshot, then icon) were tested before minor copy
- The winner was applied as the new baseline before the next experiment began
Checklist: Monthly ASO loop
- Reviewed rankings for active target terms, impressions, and category rank
- Reviewed impression-to-page-view and page-view-to-install conversion rates
- Named the single biggest constraint and one hypothesis to address it
- Shipped one metadata edit OR ran one A/B test (not ten at once) and allowed time to re-index
- Measured against the dated baseline, kept the winner, and logged what changed and what happened
Your Action Plan
- Baseline your listing in App Store Connect and Google Play Console, with a date, and decide whether visibility or conversion is your bigger constraint
- Tear down 3 to 5 competitor listings and write your single biggest gap in one sentence
- Build a keyword universe of 100+ terms from autocomplete, competitors, and reviews, grouped branded vs generic and by theme
- Score every term on volume, difficulty, and relevance, and sort into target now, build toward, and skip
- Allocate winners to fields with no word repeated across the iOS title, subtitle, and keyword field; lock an 8 to 12 keyword active set
- Write metadata that ranks and reads — iOS description for humans only, Android long description keyword-rich and readable
- Design a captioned screenshot set led by your strongest benefit, plus a spec-correct icon, feature graphic, and muted-friendly preview video
- Localize the 2 to 3 markets that matter most with native keyword research, including the English U.S./U.K. double-coverage trick on iOS
- Stand up a compliant ratings engine: native prompt at a success moment, feedback path for unhappy users, and fast review replies
- Run native A/B tests one variable at a time, ship each winner as the new baseline, and repeat the measured loop every month
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