How Appfigures Estimates Downloads and Revenue for iOS and Android Apps
Every day, Appfigures estimates data for millions iOS and Android apps to provide app makers, marketers, investors, and analysts unparalleled visibility into the mobile market.
When estimating, we have two critical focuses: accuracy and privacy:
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Accuracy is essential because we know our members rely on our Intelligence data to make real-world decisions. Whether it's spending on ads to beat a competitor, investing in a new game developer, or choosing an app idea to focus on, the data you use will make (or break) your potential for success.
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Privacy is important to us because we know that we can produce accurate estimates without using any data that can identify its owner or give a competitor any information they can't have otherwise.
We're obsessed with both, and that why so many app and game developers, marketers, analysts, investors, and journalists rely on our app intelligence every day.
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High Accuracy
Appfigures uses sophisticated AI models that turn information which can be observed in the store into download and revenue estimates. We do that by training our models with real downloads and revenue data from hundreds of thousands of apps that share that data with us.
Modeling means making assumptions. Because we're estimating, we have to make assumptions, but the fewer assumptions we make, the more accurate our estimates are.
Our training set contains billions of data points which minimizes the number of assumptions we need to make and allows us to build models that understand the entire store including all categories and countries, which makes them even more accurate.
This in turn enables us to estimate downloads and revenue for most apps and games across all categories, by country, with daily updates.
Extra Privacy
When estimating, we apply a double-opt-out process, which ensures every estimate we produce is actually an estimate.
This makes it impossible for any of the data we used for training to "leak" out as an estimate, which is why many popular app developers are included in our training pool, enabling us to have high accuracy.
Adapting to Trends
In addition to all of the above, our team constantly updates our models to fit trends that are going on in the store. For example, 2020 was full of megatrend shifts due to COVID, working from home, and lockdowns. In 2023 it was AI.
We've made more than 100 major updates to our models to ensure our accuracy remains high, and continue to do so.