Incipia blog

App Store Algorithm Ranking Tips

Gabe Kwakyi | May 24, 2016

App store algorithm keyword ranking
Today’s study is a small-scale look at:
The ability to attain a high ranking for keywords and variations of those words found in an app’s title or keyword space.
Please note that these results are based on observations from our study and are not meant to be definitive; our findings may not mirror results from marketing your own apps and should be consumed as directional insight. Additionally, we are constantly uncovering new learnings from studies and adjusting through app store ranking algorithm changes, so check back often to stay in the loop as we may update content with new discoveries. Enjoy! Please feel free to email us with questions, comments, inaccuracies or ideas for future studies.

Study setup:

  • App store data collected on 2 apps
  • Data for app 1 collected after its first official update (~1 month after launch)
  • Data for app 2 collected after the 7 day app store boost expired
  • Ranking data from Sensor Tower keyword rankings report
  • No marketing beyond keyword selection was done on either app; but app 1 did seem to experience a small halo effect for app store searches, caused by the launch of a fellow app under the same developer account
  • Study based on a small sample set of search + download data (< 1,000 downloads per app)

Summarized ranking factor findings

  • The simple average of ranks for relevant title keywords was the 8th percentileof total competing apps for that keyword (both apps)
  • The simple average of ranks for relevant keyword space keywords was the 20th percentile of total competing apps for that keyword (both apps)
  • An app’s primary app category does not seem to cause an app to rank for that term (i.e. “utilities” for app 1)
  • The location of a keyword in the title or keyword space (character-wise) did not appear to be correlated with higher rank (both apps)
  • Removing keywords immediately impacts rank for that keyword (app 1)
  • Singular presence helps rank plural variants and vice versa, as well as re-arranged word combinations (across both the title and keywords space, so long as all keywords in the combination are found) (both apps)
    • Tasks caused task to rank
    • Timer caused timers to rank
    • Accomplishment caused accomplishments to rank
    • Task and timer caused timer task and task timer to rank
    • Daily and tasks caused daily tasks and daily task to rank
  • Some common compound words also seemed to rank their spaced versions:countdown caused count down to rank and goal tracker caused goaltracker to rank. Similar trends seem to be found for apps in the broader market, like any time, basket ball and pass port
  • Additionally, base keywords seem to sometimes rank their variants, but the opposite is not true (both apps)
    • Accomplish caused accomplishes, accomplishing and accomplished to rank
    • Remind caused reminds, reminding and reminded to rank
    • But achieve did not cause achieved, achievement, achiever or achieving to rank
    • Planning did not cause planner or plan to rank
    • Daily did not cause day or every day to rank
    • Productivity did not cause productive or productiveness to rank
    • Forget did not cause forgot to rank
  • Repeating keywords across the title or keywords space may possibly boost rank; however the common guidance is not to repeat keywords and most keywords in title scored top 10% rank at any rate. BUT the 2 BEST scoring keywords for app 1 (weekly and tasks) were mentioned in both the title & keywords.
  • Sensor Tower’s difficulty score was not correlated with the ability to rank well or not well; in fact, the data shows a slightly negative correlation, indicating that a higher difficulty score was more often seen for a keyword that achieved a better rank.
App store algorithm keyword ranking
Even when looking at only keywords in the keyword space, the negative correlation still exists.
App store algorithm keyword ranking
For example, get it done had a difficulty score of 2.4 but ranked worse (11th percentile) than done (5th percentile), which had a 5.7 difficulty score.

Topics of interest for a future study:

  • Expanding the study to include more data
  • Which ASO tools most accurately predict the ability to rank highly (upcoming article)
  • A similar analysis of Google Play store ASO
  • How best to determine keyword search volume
  • How many additional words one keyword can pull rank for
Updated 2/13/16 That’s all for today! Thank you for following along. Be sure to sign up for our email list below for future updates from the Incipia Internal App Store Study Series and other company operations, and feel free to reach out with questions, comments, inaccuracies or ideas for future studies to . At Incipia not only do we build and market our own internal mobile apps, but we are also available for hire as a full service app firm to help companies design, develop and market apps. For inquiries, please fill out our inquiry form.