TV App Engagement : Beyond Download Counts

Those of us in the TV App space would like to understand the extent and trajectory of user interest in TV apps. A positive trajectory might indicate early excitement maturing into a user habit, upon which an industry can then exist. Unfortunately, app downloads (especially in a free app ecosystem) indicate awareness, but fall short of calibrating involvement. All of us who download apps are familiar with the “use once, forget forever” set in our Apps folders. More nuanced engagement studies around dwell time or biometrics are closely guarded secrets, revealed on an uneven basis across the App Ecosystem. The question is – can we do better than downloads in calibrating App Engagement across the TV App Ecosystem, using marketplace data that is commonly available for most apps?

One simple approach is to compute normalized ratings (i.e. reviews as a fraction of total downloads). The intuition is that people are more persuaded to take the trouble to rate/review an app if it is interesting. And if it is interesting, they probably use it more. Below, I’ve calculated a Figure of Merit (1000*#Reviews/#Downloads) and its associated behaviors.

A summary of the Figure of Merit data  (ignoring ‘tip of tail’ apps with less than 5000 downloads and less than 50 reviews) yields the following : 

    • Average Figure of Merit – 5.25 (i.e on average about 5 reviews per 1000 downloads)
    • Average TV App Rating – 4.1
    • Average App Ratings Count – 1250

The middle 80% of apps get between 2 and 20 reviews per 1000 downloads, with a distribution that looks something like the below.

FOM10to90

As one goes to either end of the distribution, the very popular apps get an order of magnitude more engagement (and conversely on the long tail)

FOM5to95

Overall, the use of this Figure of Merit (normalized ratings) is moderately useful, and generally correlate with intuitive notions of the quality of the Apps. Qualitative observations based on Figure of Merit data include :

  • Global Brand + App Strategy does well as a pair – 50% of apps in the top 25 on the FOM scale (and FOM numbers ranging from 15 to 200) are either global brands or brands with strong local presences (e.g.  media companies of note in Sweden, Vietnam and India).
  • Brand awareness doesn’t save bad apps –  There are a number of well known content brands that have put out apps without a discernable content strategy or user benefit. These apps garner downloads .. and user disappointment. 42  out of the 73  apps with over 250K downloads have below average ratings.  8 (of those 42) are from global media/entertainment companies, have over 250K downloads and a rating of well under 3 (compared to a median rating of 4.1). So, if you are a large and well known brand and put out an app that ‘snookers’ people – people will take the trouble to publicly call you out.
  • Sports has a natural engagement advantage Sports TV Apps score marginally higher on average ratings (4.25 vs 4.1) but about 25% higher in terms of the average Figure of Merit score. Thus people are more vocal (and generally more positive) about Sports Apps.
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