A Data Analysis of iTunes’ Top Charts Algorithm

A few days ago I published an in depth analysis of Apple’s iTunes top free chart algorithm, boosting, rank manipulation and algorithmic glitching – on medium.com.

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 Here’s the overview:

On October 29th and December 18th, 2014, something very strange happened to the iTunes top apps chart. Like an earthquake shaking up the region, all app positions in the chart were massively rearranged, some booted off completely. These two extremely volatile days displayed rank changes that are orders of magnitude higher than the norm — lots of apps moving around, lots of uncertainly.

If you build apps for iOS devices, you know that the success of your app is contingent on chart placement. If you use apps on iPhones and iPads, you should realize just how difficult it is for app developers to get you to download their app. Apple deploys an algorithm that identifies the Top Apps across various categories within its iTunes app store. This is effectively a black box. We don’t know exactly how it works, yet many have come to the conclusion that the dominant factor affecting chart placement is the number of downloads within a short period of time.

If a bunch of people all of a sudden download your app, you climb up the charts, and as a results, gain significant visibility, which results in many more downloads. Some estimate that topping the charts may lead to tens of thousands of downloads per day.

Encoded within the iTunes app store algorithm is the power to make or break an app. If you get on its good side, you do really well, and if not, you lose.

If these volatile days are deliberate, shouldn’t we be informed? There are over 9 million registered developers who have shipped 1.2 million apps into iTunes. Algorithmic glitches on wall street can set off hundreds of millions of dollars in losses. What’s the dollar cost to entrepreneurs affected by these iTunes glitches? These are people who pour countless hours and resources into adding value to Apple’s ecosystem. Whether running experiments or A/B tests, shouldn’t Apple show due respect by taking issues like this seriously?


While the app store’s ranking algorithm is opaque, there’s much to be learned by looking at it’s output over time. In his work on Algorithmic Accountability, Nick Diakopoulos highlights ways to investigate the inner-workings of algorithmic systems by tracking inputs and outputs.

Analyzing this type of data gives us a way to hold accountable systems of power, in this case, Apple and its algorithm.

Perhaps Apple is not aware of these glitches? Or maybe my data is flawed? I’ll let you be the judge of that. I did manage to find another person complaining about abnormal chart rank fluctuation around the same time. If you’ve witnessed something similar, please add a note or get in touch.

Read the full piece here.

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