Cross-Platform Mobile App Case Study

A Comprehensive Analysis of Marketing and Financial Data

Summer 2013, I was unemployed and spent learning Java, my first high level programming language, as well as developing my first mobile app for the Android platform. Booble Level was intended as a joke app, something to pull out at family gatherings to make everyone laugh, which unfortunately would get me in some hot water with Google in the future, as we’ll see later. My second app was Studfinder, which is the subject of this cross-platform mobile app case study.

Android Paid Version

I first released Studfinder (Android, Paid) to the Google Play Store in August 2013 and to date have been meticulously collecting and organizing marketing, sales, and financial data on it and it’s successors: StudFinder Tool (iOS, Paid), Stud Detector (Android, Free), and Stud Detector (iOS, Free). Recently, I’ve received requests to participate in others’ market research studies, and I’ve decided to publish a cross-platform mobile app case study based on a comprehensive spread of data I’ve collected over the past three years of developing and marketing paid and free versions of Studfinder on Google Play and iTunes. I also released Studfinder on for Kindle devices; however, due to the relative insignificance of this version’s sales, I’ve not included that data here. For confidentiality, absolute financial data has not been disclosed in this mobile app case study, but much useful information can still be gleaned from the relative comparison of the various versions, platforms, and monetization strategies employed.

cross-platform mobile app case study, 2013-2016Combined plot marketing financial annotated data
Figure 1. Combined plot of financial data gathered from various releases and monitization strategies over a three year period of marketing Studfinder app on Google Play and iTunes

iOS Paid Version

Summer 2014, I again chose to remain unemployed in order to learn Object-C (Swift is a dream compared to that shit language eh!) in order to port Studfinder over to Apple’s iOS. Sidenote: it is indeed possible to compile iTunes acceptable code on a PC running the latest version of OSX inside a virtual machine – no need to buy a mac – shhh, don’t tell Apple. Booble Level had been on the store for $0.99 with no action for the past year so I decided to make it free with in-app-payments (IAPs). Within a few weeks it was ranking in the top 100s in the US, Canada, Russia, and India and making me a few bucks [Fig. 1-1], before it was removed from the Play Store – strike one. January 2015, I released the first free, ad-supported version of Studfinder for Android as an experiment, but decided to remove it in March [Fig. 1-2] because I had decided it was eroding my Android paid sales. Then in August, after a couple more apparent strikes against me, my account was unceremoniously terminated [Fig. 1-3] with one email.  This was brought on from what I can only surmise was semantics/wordings contained in Studfinder’s store description that apparently violated some copyright policy somewhere (emails from Goo-bots are notoriously vague and meaningless, and there’s no way you’re talking to a real person). So went through a VPN and paid the $20 to start up a new developer account, and Studfinder was back in the top 3 search results again in a matter of days – shhh, don’t tell the Goo-bots. Across all app versions and platforms, Studfinder has consistently ranked in the top 3 search results for “stud finder,” “studfinder,” and “stud detector” over the period covered in this mobile app case study.

Android, iOS Free Versions

2016 monthly stud finder google keyword searches
Figure 2. Monthly “stud finder” google keyword searches, 2015-2016

In an effort to increase revenues and to maintain market share despite numerous upstart competitors, I released free ad-supported versions of Studfinder for Android in November and for iOS in December, 2015. The effect in the Play Store was, again, to erode my paid sales; conversely, on iTunes the free version gave a massive (though apparently short-lived) boost to paid sales [Fig. 1-4]. This spike could have also been influenced by an increase trend in Google keyword searches for “stud finder” [Fig. 2] typical during the Christmas season. Currently I’m in the process of switching out my banner ads for incentivized interstitials, because my analytics data suggests this will be more lucrative. Unfortunately, I’ve only recently integrated Google Analytics into a number of my apps, and so do not have enough data yet to properly present it in this mobile app case study – check back later or subscribe below if you’d like to be email spammed whenever I post.


stud finder global sales 2013-2014 cross-platform mobile app case study
Figure 3. Studfinder global sales 2013-2014

Over its lifetime, one problem that has plagued Studfinder is bad reviews, particularly on iTunes. Now, I’ll admit that many of those reviews were warranted in earlier releases, but over the years I’ve continually improved its algorithms and UI to the point where I realistically can little improve its functionality any further, given the sensor limitations of modern devices. I know it works, thousands of returning users use it every day, but still the bad reviews. I’ve tried various review and support notification strategies, which haven’t worked; so, it is what it is.


ios stud detector app free download rankings plot app annie 2016 first quarter
Figure 4. Stud Detector (iOS, free) download rankings plot, App Annie 2016

Sales are predominantly in English speaking countries – US, Canada, UK, Australia – and US users are responsible for >80% of revenue [Fig. 3] – Texas ~ 13%, California ~12%, Florida ~5%, each remaining ~1-4%.  I had translated earlier releases into Spanish, Korean, Japanese, Hindi, and Russian, but this had zero affect on encouraging increased downloads any of the languages’ respective countries.


ios stud detector app paid download rankings plot app annie 2016 first quarter
Figure 5. Stud Detector (iOS, paid) downloads rankings plot – App Annie, first quarter, 2016

Most Studfinder versions have consistently ranked between the top 200s-1000s, depending on country, in their app categories (Tools on Play Store and Utilities on iTunes) in download rankings [Fig. 4, Fig. 5] and, where applicable, grossing rankings [Fig. 6] according to App Annie analytics data. The periodic bumpiness in Figures 4-6 is primarily caused by a consistent weekly trend of significantly higher downloads during the weekend than the rest of the week.


ios stud detector app paid grossing rankings plot app annie 2016 first quarter
Figure 6. Stud Detector (iOS, paid) grossing rankings plot – App Annie, first quarter, 2016

So learning to develop and market Studfinder by trial and error has been a very interesting exercise for me over the past few years. Although frustrating at times, overall its been extremely rewarding for me as a creative outlet, learning challenge, and entrepreneurial venture.

TL;DR – lessons learned:

  • diversification == increased profits && revenue stability && piece of mind
  • iOS monetization: paid > interstitials > banners
  • Android monetization: ad-supported > interstitials > banners > IAPs
  • incorporate app analytics early
  • take user reviews seriously right from the start
  • unlearn Obj-C asap
  • never trust a Goo-bot!

Thanks for reading, and I hope this cross-platform mobile app case study proves useful to some of you current or aspiring developers conducting your own market research. If you’re interested, check out this AMA I did recently and these 9 steps to create your own app to generate passive income.

Posted in Dev, Science
Share Subscribe

Leave a Reply

Your email address will not be published. Required fields are marked *