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Why I built ASOScan — an Android dev who got tired of ASO tools

I've shipped Android apps for years, and improving store rankings always meant choosing between cheap keyword scrapers I didn't trust and enterprise suites priced for a team of ten. As a solo dev, neither fit and none gave me the data and views that actually drive ASO decisions: which keywords are worth targeting, what a competitor just changed, and whether a metadata edit will gain ranks before I ship it.

I'd spent years sitting between engineering and marketing teams, so I knew what a developer actually needs to see to act. ASOScan is the tool I always wanted: the complete ASO workflow for iOS and Android, at a price a solo dev or small studio can use.

Just went live, I'd really value your feedback: the trial is free for 7 days, no credit card. Take it for a spin with your own app and tell me what feels off, what's missing, or what you'd expect to be there and isn't. That's exactly what I want to fix next. I also open-sourced the ASO skills I use with AI agents: github.com/ASOScan/aso-skills

https://asoscan.com/?utm_source=indiehackers&utm_medium=community&utm_campaign=launch

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ASOScan
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    The distinction between having ASO data and helping someone actually make an ASO decision is interesting.

    I’d be curious which part of the workflow users find hardest right now: finding the signal or deciding what to do with it.

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      Finding the signal is always worth the time, because even with fairly large apps you sometimes find obvious gaps. Relevant keywords with meaningful demand that the app is barely targeting, or not targeting at all. Those can translate into a surprising amount of missed organic traffic. But the harder part is deciding what to actually do with that signal. Seeing that a keyword has volume, or that a competitor moved up, is one thing. The harder questions are: is this keyword actually worth targeting for my app? What should I change? And once I make that change, did it really help? That is the part I am trying to solve with ASOScan. It surfaces keyword opportunities rather than just giving you a big table of keyword data, and then keeps track of your metadata changes alongside your rankings. So if a keyword moves after you change a title, subtitle, description, etc., you can see whether you gained or lost rank around that change instead of noticing the movement weeks later and having no idea what caused it. When the changelog does show a matching edit it names the date and the field; when it does not, it says the cause is not established rather than guessing. That feedback loop is probably the hardest part of ASO in practice: finding an opportunity, acting on it, and then actually understanding whether the decision worked.
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        That feedback loop is the consequential part — especially whether users are actually changing metadata based on the signal and then judging the outcome. If you’re open to it, what’s the best email to reach you on?