This is the seventh entry of my ASO series; although I concede that it could certainly be the first one.
Catching up with the ASO series.
Over this ASO series, I’ve already shared posts on how to retrieve data on app Keyword Rankings and app profiles on Google Play, track and visualize keywords and rankings, automate and schedule its reporting, and build tools and workflows to improve a given app organic positioning in Google Play.
All that using Rstudio and several scripts written in R.
However, I’ve yet not shared much about why ASO is relevant for any app.
What is ASO
ASO stands for App Store Optimization and it has a direct influence on how any app positions when a related term is searched in the app stores (in this case, I will refer to the Google Play only).
You may think of ASO as the equivalent of SEO (search engine optimization) for apps.
Websites with content ranking at the top of web search engines will have more chances to be visited by internet visitors using those web search engines; and therefore, more chances for those web owners to create value out of these “non-paid” visitors.
Why is ASO important
The same stands for ASO;
The higher the app rankings for some search terms in the app store,
The more “non-paid” users, and
More value for its owners (subscription revenue, e-commerce sales, branding… )
Thinking about the search engine
One could think that all it’s needed is just to decipher how the search engine works to rank #1 in the app store.
However, that is not the case. Or, to say the least, the case is not that simple.
Think for a second about the raison d'etre for an independent app search engine.
A reasonable scope might be to provide the maximum match between the input search term and the app results listed by the search engine.
In order to find and sort the matches between the search input term and the available app inventory, the search engine will calculate some app matching scorings based on different inputs, such as but not limited to:
Some relevant input for an app search engine
Public data available at the app profile
Number of text matches between the the input search term and the text contained in the app title, app short description, app long description, app developer name, app reviews´ text, text written as an image in the app screenshots, etc. (not necessarily with the same weight!)
Reviews.
Score.
Localization / Country - Language.
Number of downloads.
Time of the day, day of the week, and day of the year.
Non-disclosed private data owned by the search engine.
App performance.
User retention and engagement.
Technical performance (crashes and ANR errors)
First-party, personal data of the user making the search.
Demographics (user language, location, gender)
Behavioural (user apps used, habits, mobile usage,…)
App profile page performance
Traffic records
Conversion records
Links between the app profile page and other websites pointing to it.
Therefore, it is certainly complicated to fully emulate or reverse engineer the work of a search engine. Especially, because only the search engine has data available about the the app performance, and the personal records of the user searching in the app store.
In addition to that, there are not (and should not be) easy ways to increase the User’s Reviews and Scores in case they were relevant for the search engine.
There is still hope
Be as it may, there is still room to play around and improve the chances to position better in the Google Play with the information available.
In particular, someone could retrieve much of the information present in the app profiles and use it to her advantage to increase a given app positioning (ignoring the non-disclosed private data).
A Keyword scoring proposal
Along the following lines, I´ll propose a search term (Keyword) scoring algorithm to improve any app positioning in Google Play
In line the above, the approach might be synthesized in the following steps.
Select a 100-500 bag of search terms relevant for the app to be positioned (tracked Keywords).
Select a 20-30 pocket of search tearms the app is trying to ranking for or ranking already (used Keywords*)
Run daily searches on the app store (search engine) to track the rankings of the apps listed for each tracked Keywords and used Keywords.
Retrieve the public profile data available for each of the apps ranked, for each of the tracked Keywords and used Keywords.
Calculate a score for each tracked Keywords and used Keywords based on its estimated app store traffic, and the app authority and competition values out of the analysis of the profiles of all the apps ranking for each search.
Track and replace low-scoring keywords with high-scoring ones based on hands-on rules.
(*) Used Keywords will be present in the app title, short and/or long description depending on their priority for the ASO manager, and with a Keyword density between 2 and 4%. The Keyword density is defined as the number of times a keyword appears on the weigthed app title, short and/or long description as a percentage of the overall word count in that piece of text.
If you have liked this content, I reccomend you following along from my first entry.
You should be able to cover all the steps with enough ground and code insights to deploy (and aslo, improve) your own ASO scripts and workflows to reach the top of Google Play with your apps!
Why not using a third-party tool for ASO?
That´s a fully respectable position. In fact, the vast majority of the ASO managers work with several third-party tools.
However, I do like building my own ASO scripts for several reasons. The first one is that it makes me think what I need and why I need it.
The second reason is that it doesn´t cost me money but rathre time that I´ve put into learning a key topic for my business.
The third reason is that, after getting into the ASO rabbit hole retrieving data from Google itself, I genuinely wonder where this third-party tools are getting the data from and how reliable that data is.
Fourth reason is the most powerful one, and it is that I can do it.
What´s next?
Likely, I will soon share some further pieces on how to maintain healthy your bag of keywords by exploring competition.
If you would like to stay tuned with more of this content just subscribe!
Should you have any comment or request, do not hesitate to get in contact with me by email at datadventures@substack.com