Guide · 8 min read
ASO Keyword Research Without Paid Tools: The Free Method That Actually Works (2026)
Sensor Tower starts at roughly $450 a month. AppTweak is in the same tier. For an indie developer with a new app and no revenue yet, paying enterprise ASO tool pricing to figure out whether anyone searches for your keyword is a trap — you're spending the marketing budget before you know if you have a product worth marketing. The free method below gives you everything you need to build a solid initial keyword strategy: real volume signal, competitive gap analysis, and a ranked shortlist of 10–15 keywords you can deploy in your metadata today.
Apple Search Ads is the only free keyword volume signal Apple actually publishes
Apple's Search Ads platform exposes a keyword popularity score — an integer from 1 to 100 — for any keyword you type into the campaign setup flow. You do not need to spend a dollar on advertising to access it. Create a free Apple Ads account at ads.apple.com, start a new campaign, navigate to the keyword step, and type any keyword. The score appears inline. This is the same underlying signal that every paid ASO tool uses: Sensor Tower, AppTweak, and Astro all surface derivatives of this same Apple-sourced data.
The scale is logarithmic, not linear. A keyword scoring 70 does not have twice the search volume of a keyword scoring 35 — it has significantly more, likely an order of magnitude. Apple does not publish conversion rates or absolute search volume, only the relative popularity bucket. That is enough to build a tiered keyword list and identify where you have a realistic chance to rank. What it cannot tell you is how hard specific keywords are to rank for — that requires competitor analysis, which is covered in the next section.
One workflow tip: use the Apple Ads Keyword Suggestions tab (available inside any ad group setup screen) to generate related keywords from your app's category and app name. This surfaces terms you would not have thought to type yourself. The suggestions are seeded from actual search behavior in the App Store, not keyword databases. Paste every suggestion with a score between 20 and 60 into a spreadsheet — that range is your starting shortlist.
Autocomplete mining: the App Store search bar as a free keyword generator
Open the App Store on an iPhone and start typing your primary keyword, but do not finish it. Watch the autocomplete suggestions. Each autocomplete term is a real query that real users have searched recently enough to make it into Apple's suggestion model. These are not algorithmic guesses — they reflect actual search intent, weighted toward recency. For any keyword concept you want to target, type the first three letters and record every suggestion. Then type the first four letters. Then five. Each prefix reveals a new tier of completions.
Run this exercise for your product category name, your primary feature verb, and the problem your app solves. A task manager app would mine 'task', 'to-do', 'remind', 'plan', and the names of two or three competitor apps. At the end of this exercise, which takes about 20 minutes, you will have 30–60 real keyword phrases, all confirmed to exist in App Store search behavior, with zero spend. The limit of autocomplete is that it gives you no volume ranking — you cannot tell from the autocomplete list whether 'task manager for teams' or 'team task list' is searched more. That is where the Search Ads scorer from the previous section closes the gap.
One nuance: autocomplete suggestions vary slightly by App Store region. If you are targeting non-English markets, run the same exercise on a device with the App Store set to that region and language. The autocomplete behavior reflects local search patterns, and keyword phrases that work in en-US often have structurally different equivalents in de, ja, or pt-BR. See the description framework guide for how regional targeting flows through to the full metadata strategy.
Competitor metadata autopsy: reading what your rivals already figured out
Every app in the App Store has a 100-character keyword field, a 30-character title, and a 30-character subtitle — all of which Apple indexes for search. The title and subtitle are publicly visible on any product page. The keyword field is not visible in the App Store UI, but you can read it through two free surfaces. First, open the app's product page in a desktop browser and view the page source — the keyword metadata tag often contains the raw keyword string. Second, use App Store Connect's "Search" tab for your own app to see which keywords you rank for, which reveals the competitive overlap.
For competitor keyword fields that are not exposed in page source, the proxy is ranking footprint. Search each term from your autocomplete list and note which apps appear in the top five results. If the same three apps appear across 15 different keyword searches, their keyword field almost certainly contains those exact terms. You have reverse-engineered their strategy at zero cost. The actionable output: a list of keywords where competitors are absent or weakly ranked — those are your entry points.
One observable pattern across top-ranked apps: apps that rank broadly tend to use their 30-character subtitle for a secondary keyword phrase that would not fit naturally in the title. The title carries the brand and primary keyword; the subtitle carries the category modifier ('for teams', 'with AI', 'daily planner'). Indie developers who leave the subtitle as a tagline ('Your life, organized') are surrendering 30 characters of indexed real estate to copy that Apple cannot rank.
The 20–55 popularity sweet spot — why chasing high-volume keywords kills indie apps
The instinct is to target the highest-volume keyword in your category. 'Meditation' beats 'meditation timer' in raw search volume, so go after 'meditation.' This logic is correct about volume and wrong about outcomes. High-volume keywords (popularity 65+) on the App Store are dominated by apps with thousands of ratings, multi-year ranking histories, and enterprise marketing budgets. A new app with 50 reviews cannot rank on page one for 'meditation' regardless of how well its metadata is written — Apple's algorithm weights historical download velocity and engagement signals too heavily.
The 20–55 range is where indie apps win. A keyword with popularity 35 has real search volume — real users typing it, real installs available — but thin competition from large players who don't bother targeting niche modifiers. 'Meditation timer with bells' (hypothetically SP 28) has users searching it and few apps optimized for that exact phrase. You can rank in the top three within weeks of launch. That ranking builds your rating count and engagement signals, which eventually support broader keyword expansion.
The practical framework: start with 3–5 keywords in the 20–40 range (high chance of quick ranking), 3–5 in the 40–55 range (medium competition, meaningful volume), and 1–2 stretch keywords at 55–65 (aspirational, will take months). Track ranking weekly using App Store Connect's built-in Search tab or the free tier of any tool that pulls from the same Apple data. Adjust the stretch keywords as your review count grows.
Screenshot captions index for App Store search — use the extra keyword surface
Apple confirmed in mid-2025 that App Store search now indexes text extracted from screenshot images via optical character recognition. This means the marketing copy overlaid on your screenshots — the headline text, the feature caption — is now a keyword ranking surface, not just a conversion surface. An indie developer with a to-do app who writes 'Daily Task Manager' as their first screenshot headline is now ranking for that phrase, not just selling it.
The implication is significant: your 100-character keyword field is not your only indexed text. Every screenshot caption contributes. The practical move is to ensure that at least your first two screenshots contain the exact keyword phrases you are targeting in your keyword field — written naturally as headlines, not stuffed awkwardly. You can see the screenshot editor for adding headline text to screenshots with device frames, and the screenshot formula guide for how to structure caption copy for conversion. The conversion and ranking goals align here: a specific feature headline converts better than a generic one and ranks for a more targeted keyword.
The limit of this surface is that Apple's OCR favors text that is legible at display size — high contrast, large font weight, short phrase. Cramming 40 words of keyword text into a screenshot in small gray type will not rank. The same formatting principles that make screenshot captions convert well are the ones that make OCR work correctly.
Google Trends: using it as a relative validator, not an absolute volume source
Google Trends does not measure App Store search volume. It measures Google web search, which is a different intent graph. The mistake is using Trends as a volume proxy — pulling up 'meditation app' and concluding that because search interest peaked in January, that is when to target the keyword. That may or may not be true on the App Store, and the time lag and demographic differences between web search and App Store search are large enough that direct translation is unreliable.
What Trends is genuinely useful for: comparing two keyword variants head-to-head over time to determine relative interest. If you cannot decide between 'habit tracker' and 'habit builder' as a subtitle keyword, Trends will show you that one phrase has consistently more search activity than the other — and the directional gap is likely to hold on the App Store too, even if the absolute numbers don't. It also surfaces seasonality patterns (tax prep apps in February, fitness apps in January) that you can exploit with promotional text updates in App Store Connect, which can be changed without a new build review.
When to upgrade from free: the one signal that tells you paid tools pay off
Free tools have one structural limitation: they show you your own ranking position and keyword popularity, but they do not show you the full competitive landscape at scale — how many apps are chasing the same keyword, what their estimated download velocity is, or what the trending upward keywords in your category are before they become competitive. Paid tools like GrowASO ($49/year), Astro ($9/month), and Komori ($19.99/month) address this gap at prices that make sense once an app is generating revenue.
The signal that paid tools pay off: when you have exhausted the 20–55 popularity range — you are ranking in the top five for every keyword in your shortlist and those rankings are driving downloads — and you need to identify the next tier of expansion keywords. At that point, the keyword intelligence in even a $9/month tool will reveal competitive gaps you cannot find manually. Until then, the free method above gives you more keyword candidates than most indie developers ever actually deploy. The constraint is almost never keyword data; it is execution — writing the metadata, testing variants, and iterating on the results.
Start with the Apple Search Ads scorer, the autocomplete list, and a competitor metadata audit. Build your initial keyword field from that research. Deploy it. Check your ranking positions in App Store Connect after four weeks. Adjust two or three keywords based on what ranked and what did not. Repeat this cycle before spending anything on keyword intelligence tools.
Build your keyword list, then build screenshots that rank for them
The free research workflow covers keyword discovery, volume validation, and competitive gap analysis. What it does not cover is the screenshot layer — because once your metadata keywords are set, your screenshots are now both a conversion asset and a ranking signal. Those two jobs require the same well-written headline.
Write screenshot captions that contain your target keyword phrases naturally, export at the required dimensions, and you have covered every indexed surface the App Store exposes to indie developers at zero tool cost.
Add keyword-rich captions to your screenshots →
Frequently asked questions
Does the App Store index the long description for search?
No. Apple does not index the long description for App Store search on iOS. The indexed fields are the app title (30 characters), subtitle (30 characters), keyword field (100 characters), and — confirmed since mid-2025 — text that Apple's OCR extracts from your screenshot captions. Keywords that appear only in your description have zero impact on search ranking.
How do I access Apple Search Ads keyword popularity scores for free?
Create a free Apple Ads account at ads.apple.com. Start setting up a new campaign, navigate to the keyword targeting step, and type any keyword. Apple displays a popularity score from 1 to 100 inline. You do not need to fund the account or run any ads to use this feature — the keyword research tool is available at the campaign setup stage regardless of spend.
How many keywords should I target in my App Store keyword field?
Apple's keyword field is 100 characters including separating commas. The standard practice is to use comma-separated single words and short phrases without spaces between commas (e.g., 'task,planner,reminder,daily') to maximize the number of terms that fit. Avoid repeating words already in your title and subtitle, which Apple indexes separately. Aim for 8–12 unique keyword concepts in the 100 characters, prioritizing your 20–55 popularity range terms.
Can I see a competitor app's keyword field?
Not directly — the keyword field is not displayed in the App Store UI. The proxy method is to search each term you are considering and note which competitor apps rank for it. If the same app ranks consistently across 15 related keyword searches, those terms are almost certainly in their keyword field. For your own app, App Store Connect's Analytics > Sources > App Store Search tab shows which keywords are driving impressions and installs.
What's the difference between ASO keyword research for iOS and Google Play?
On iOS, the indexed fields are title, subtitle, keyword field, and screenshot OCR text — the long description is not indexed. On Google Play, the full long description is indexed and keyword density within it affects ranking. Play Store keyword research should therefore focus on natural keyword placement throughout the description text, not just a hidden metadata field. The same keyword phrase may also have different relative popularity on each platform, so research each store separately.