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Not all keyword tools are equal, and understanding what data points matter helps you evaluate which free tools are worth your time and which are too limited to be useful. The core functionality you need is search volume estimation, keyword difficulty scoring, and keyword suggestions based on seed terms.

Search volume tells you how many people search for a given term each month within the app store. Unlike web SEO where Google provides exact search volume data, app store search volume is estimated by third-party tools through indirect signals. No free tool provides perfectly accurate volume numbers, but relative comparisons (keyword A has higher volume than keyword B) are generally reliable across tools. Look for tools that provide at least a relative volume score on a 1-100 scale rather than just a high/medium/low label.

Keyword difficulty indicates how hard it would be to rank in the top results for a given keyword. Difficulty is determined by the strength and quantity of apps already ranking for that term. A keyword with high volume but extreme difficulty is not useful for a new app because you will never rank high enough to benefit from that volume. Free tools that provide difficulty scores help you find the sweet spot: keywords with moderate volume and low-to-medium difficulty where you can realistically reach the first page of results.

Keyword suggestions expand your research beyond the obvious terms you already know. Good tools suggest related keywords, long-tail variations, and competitor keywords that you might not have considered. For example, if you enter "expense tracker," the tool might suggest "receipt scanner app," "budget planner free," or "money manager for couples." These suggestions often reveal high-value keywords with less competition than the broad terms you started with.

Several tools offer genuinely useful free tiers for ASO keyword research. Here is an honest comparison of what each provides, their limitations, and which situations they are best suited for.

Apple Search Ads is arguably the most underrated free keyword research source. Even if you never run a paid campaign, the Search Ads keyword planner shows you Apple's own data on keyword popularity (a 5-100 scale), suggested related keywords, and competitor keyword insights. This data comes directly from Apple, making it the most authoritative source for App Store keyword volume. The limitation is that it only covers the App Store (not Google Play) and does not provide a difficulty score. To access it, you need an Apple Search Ads account, which is free to create.

Google Play Console provides keyword data through its "Store listing experiments" and "Search Analysis" features. The Search Analysis section shows which keywords are driving impressions and installs for your app, along with conversion rates for each keyword. This is real performance data rather than estimates, making it extremely valuable for optimizing existing listings. The limitation is that you can only see data for keywords where your app already appears in results, so it is less useful for discovering entirely new keyword opportunities.

AppFollow offers a free tier that includes keyword search volume, difficulty scores, and keyword suggestions for both App Store and Google Play. The free plan limits the number of keywords you can track and the frequency of data updates, but it provides enough functionality to conduct initial research and monitor your most important keywords. The interface is clean and beginner-friendly, making it a good starting point for developers new to ASO.

Appfigures has a limited free plan that provides keyword rankings, search volume estimates, and competitor keyword analysis. The data quality is solid, particularly for the US App Store. The free tier restricts the number of apps you can track and keywords you can research per day, but working within these limits is manageable for a single app. MobileAction and ASOdesk also offer free trials or limited free tiers worth exploring, though their free functionality has become more restricted in recent years.

Effective keyword research follows a structured process. Going through these steps systematically produces better results than random keyword searching, even with free tools that have data limitations.

Start by brainstorming a seed list of 20-30 keywords. Think about what a potential user would type into the app store search bar to find an app like yours. Include obvious category terms ("photo editor," "task manager"), specific use cases ("remove background from photo," "shared grocery list"), and problem statements ("how to track expenses," "better sleep"). Ask friends, family, or early users what they would search for. Check competitor listings and note the keywords they use in their titles and subtitles.

Run each seed keyword through your chosen free ASO tool and record the search volume and difficulty scores. Expand your list by exploring the keyword suggestions each tool provides. For every seed keyword, you should discover 5-10 related terms worth evaluating. After this expansion phase, you should have a list of 100-200 candidate keywords with volume and difficulty data.

Filter and prioritize your expanded list using a simple scoring framework. Multiply the volume score by the inverse of the difficulty score to create a rough "opportunity score." High volume and low difficulty produce the highest opportunity scores. Then add a relevance filter: remove any keyword that does not accurately describe your app, regardless of its opportunity score. Ranking for an irrelevant keyword brings traffic that will not convert. Final priority should go to keywords where you have a realistic chance of reaching the top 10 results within 2-3 months.

Assign your top keywords to specific metadata fields. Your most important keyword belongs in the app title (highest ranking weight). The second and third most important keywords go in the subtitle (iOS) or short description (Android). Remaining keywords fill the iOS keyword field (100 characters) or are naturally incorporated into the Android long description. Do not stuff keywords unnaturally. Apple's algorithm penalizes keyword stuffing, and Google's algorithm uses natural language processing to understand contextual relevance.

Keyword research does not stop at metadata. Your screenshots are an opportunity to reinforce your keyword strategy visually, and this connection between keywords and screenshots is where many developers miss a significant optimization opportunity.

The text overlays on your screenshots should incorporate your target keywords naturally. When a user searches for "budget tracker" and sees your listing, a screenshot with the headline "Track your budget in seconds" reinforces the relevance signal both for the user and for the algorithm. Apple and Google both index text that appears in screenshots (through OCR and metadata), so keyword-aligned screenshot text can contribute to your ranking for those terms.

ScreenMagic makes this connection between keyword research and screenshot creation practical. After completing your keyword research, you can use the tool to generate screenshots with text overlays that incorporate your priority keywords. Because the tool uses AI to handle layout, typography, and device framing, you can quickly iterate on different headline variations to find the combination that integrates your keywords most naturally.

This approach is especially powerful for localized keywords. If your keyword research reveals that the highest-volume term in German is different from the direct translation of your English keyword, you need localized screenshots with the German-specific keyword in the text overlay. Manually creating localized screenshots for 10+ languages with language-specific keyword targeting is prohibitively time-consuming. ScreenMagic generates localized variants from translated text input, letting you align every language version of your screenshots with the optimal keywords for that market.