Most teams treat app keyword research like a spreadsheet chore — dump a hundred terms into an ASO tool, sort by volume, paste the top ten into the keyword field, ship it. Then installs flatline and nobody can say why. The reason is simple: app keyword research isn’t one discipline, it’s two, and each runs on a completely different indexing engine than the web SEO most marketers already know. Get the mechanism wrong and you optimize for the wrong surface with the wrong data. Get it right and a single well-chosen long-tail term keeps delivering installs for years.
App keyword research is two jobs, not one
There are two places a person can search their way to your app: inside the App Store or Google Play (that’s ASO — App Store Optimization), and out on the open web via Google, where a landing page or blog post captures the query and pushes the download. Apple has said the majority of App Store downloads — roughly two-thirds — begin with a search inside the store, which is why store keywords matter enormously. But store rankings are rented: the moment a better-funded competitor outbids you or reworks their metadata, your position evaporates. A web page ranking for “best budget expense tracker app” compounds instead — it keeps sending installs long after you publish it. Serious app keyword research covers both surfaces deliberately, because they reach different intent at different stages.
The indexing mechanic Apple and Google don’t advertise
Here’s what breaks most beginners: the store search engines don’t work like Google web search, and they don’t work like each other. On iOS, Apple builds your searchable index from a fixed set of fields — the app name (30 characters), the subtitle (30 characters), and a hidden keyword field (100 characters). Repeating a word across those fields wastes space, because Apple indexes each term once. Commas separate terms and spaces after commas are wasted characters. Apple also auto-combines your words into phrases, so “budget” and “tracker” in the field can surface you for “budget tracker” without you spending the phrase.
Google Play works nothing like that. There’s no hidden keyword field. Play runs a full-text index across your title (30 chars), short description (80 chars), and the entire long description (up to 4,000 chars), and — unlike Apple — repetition carries weight. Mentioning your core term three to five times naturally across the long description genuinely helps you rank for it, while over-stuffing triggers a quality demotion. Two stores, two engines, two keyword strategies. Any keyword strategy that produces one flat list for both is leaving installs on the table.
Where store keyword volume data actually comes from
Neither Apple nor Google publishes clean search-volume numbers the way web keyword tools do. So where do the numbers in ASO platforms come from? Mostly triangulation:
- Apple Search Ads popularity scores — Apple exposes a search-popularity signal (roughly 5–99) inside its ad platform, and tools reverse-engineer relative volume from it.
- Store autocomplete — the order suggestions appear in reflects real query frequency; scraping autocomplete at scale reveals demand and phrasing.
- Google Play Console search terms — your own console shows the exact terms people searched before installing your app. This first-party report is the most underused asset in Android ASO.
- Third-party ASO panels — Sensor Tower, AppTweak, and similar estimate volume and difficulty from device-panel and modeled data.
Treat every one of these as directional, not gospel. An ASO “volume 45” is a relative ranking, not 45,000 monthly searches. The moment your app has any install history, your own Play Console search-term report beats all of them — it’s the only source showing terms that actually converted for your specific app.
A scoring framework: relevance × reachable volume × difficulty
Volume alone is a trap. A term with high volume you can never rank for is worth zero; a low-volume term with exact intent that you can dominate is worth a lot. Score every candidate on three axes instead of sorting by one:
- Relevance (0–3): How exactly does this term describe what your app does? A “sleep tracker” ranking for “alarm clock” wastes an impression on someone who bounces. Low relevance kills conversion rate, and conversion rate feeds store ranking.
- Reachable volume (0–3): Not raw volume — volume you can realistically capture given your current rating count and category authority. A brand-new app should weight this toward long-tail terms it can actually reach.
- Difficulty (0–3, inverted): How saturated is the term with entrenched, high-rated incumbents? Score the field, not the leader — you’re competing to displace the tenth result, not the number one.
Multiply the three. Prioritize the top scores, not the highest-volume terms. This is the same weakest-competitor logic that governs good web SEO: you don’t need to beat the market leader, you need to beat the weakest page — or app — currently occupying the ranking you want.
A worked example: a habit-tracker app
Say you’re launching a habit tracker. The lazy approach targets “habit tracker” (high volume, brutally competitive, dominated by apps with hundreds of thousands of ratings). Your relevance is 3, but reachable volume is 0 and difficulty is 0 — score of zero. Useless on day one.
Now score the long tail. “Streak habit tracker” — relevance 3, reachable 2, difficulty 2 = 12. “Daily routine planner app” — relevance 3, reachable 2, difficulty 2 = 12. “Habit tracker no subscription” — relevance 3, reachable 3, difficulty 3 = 27, because it’s low-competition and screams high-intent. You’d anchor your subtitle and keyword field around the mid-tail winners, seed the long-tail terms into your Play long description, and build one web landing page targeting “habit tracker with no subscription” to catch that exact frustration on Google. Three surfaces, one coherent keyword set, every term earned its slot.
The iOS vs Android split most guides gloss over
Because the indexes differ, your tactics must diverge. On iOS: never repeat a word across name, subtitle, and keyword field; drop spaces after commas; use singulars (Apple loosely stems plurals); and don’t waste field space on your brand name or category name — Apple already indexes those. On Android: write the long description for humans first, then weave your two or three priority terms in three to five times each, front-loading them in the first 160 characters that appear before “read more.” Google Play also weights the short description heavily, so that 80-character line is prime keyword real estate, not a throwaway tagline. Running identical metadata on both stores is the single most common ASO mistake.
The localization trick that expands your keyword field
Here’s an advanced Apple move worth knowing: the US App Store indexes keywords from several English locales at once — English (US), English (UK), and English (Australia) among them. By adding those localizations and filling each keyword field with different terms, you effectively multiply your 100-character keyword budget for the same US audience, without translating anything. It’s a legitimate, Apple-supported feature, not a loophole that gets penalized. If you genuinely serve other languages, real localization compounds further — but even monolingual US apps can use the English-locale stack to index more terms.
Web keyword research: the compounding channel app teams ignore
Store keywords capture people already shopping for an app. Web keywords capture the far larger audience with the underlying problem — “how to stop procrastinating,” “budget when you have irregular income,” “track water intake reminder.” These problem and how-to queries are where most install growth hides, and they never expire. This is where standard web keyword research applies: pull 100–150 ideas per seed term with real volume, difficulty, and CPC, segmented by country. This is exactly what SEO Rocket does — AI keyword research running on live Ahrefs index data, so you’re prioritizing terms with actual demand instead of guessing, then feeding the winners into landing pages and blog posts that funnel to your store listing. Its competitor gap analysis surfaces the queries rival apps rank for that you don’t — often the fastest route to reachable terms.
Measuring what the research produced
Rankings jitter daily, so measure trends, not single days. For the store, track your position for each target term over weeks and — crucially — watch conversion rate to install, because ranking for terms that don’t convert actively hurts you (Apple and Google both factor tap-through and install rate into store ranking). For the web side, cross-check against Google Search Console and your attribution reports as ground truth; ASO panel estimates are directional. SEO Rocket’s rank tracking uses top-100 snapshots rather than spot checks, and its AI-visibility tracking shows when your content gets cited in AI answers — an increasingly real install path as people ask assistants “what’s the best app for X.” Measure the full funnel from query to install, not just the ranking.
Frequently asked questions
What’s the difference between ASO and app keyword research?
ASO (App Store Optimization) is the broader practice of improving your store listing — icon, screenshots, ratings, and keywords — to rank and convert. Keyword research is the slice of that work covering which terms to target, plus the web-SEO keywords that drive installs from Google. Keyword research feeds ASO; ASO is bigger than keywords alone.
How many keywords should an app target?
Focus, don’t spray. Pick two or three priority terms that define what your app is and rank hard for those, then let long-tail combinations accumulate naturally. Apple’s 100-character field forces discipline; Google Play rewards a handful of terms mentioned naturally over dozens stuffed in. Fewer terms ranked well beats many terms ranked nowhere.
How long does app keyword research take to show results?
Store metadata changes can move rankings within days to a couple of weeks because the index updates fast. Web keyword content is slower — expect three to six months for a new page to reach page one — but it compounds and outlasts store positions. Run both timelines in parallel.
Are free ASO keyword tools good enough?
For an early-stage app, store autocomplete plus your own Google Play Console search-term report will get you surprisingly far for free. Paid ASO panels help once you’re scaling and need difficulty and volume estimates across many terms. For the web side, use a research tool built on a real backlink and keyword index rather than free scrapers.
A sequence that works for a new app
Put it together in order. First, list the two or three terms that define your app and score every candidate on relevance, reachable volume, and difficulty — target the winners, not the highest volume. Second, build separate metadata for iOS and Android that respects each store’s index, and stack English locales on Apple to expand your keyword budget. Third, run web keyword research to find the problem and how-to queries your buyers search on Google, and build landing pages for the reachable ones. Fourth, track rankings and conversion as trends over weeks, correcting from your own console data. This is the same playbook that’s held up across 1,000,000+ ranking pages: research by intent, build to beat the weakest competitor, validate before you ship, and measure the trend — not the daily noise. Do app keyword research this way and you stop renting installs and start compounding them.
