How to increase traffic using similar apps?
We’ve learned new things about app recommendation patterns on App Store and Google Play—and now we can’t wait to share them with you! How do store algorithms recommend apps? What factors are crucial? Can a user base overlap impact app recommendations? Spoiler alert: yes, it can. Feel free to read this article for more details.
Similar apps as a traffic source
Similar apps is a block with the store’s selection of apps that’s found at the bottom of an app page. That’s one of the traffic sources for Explore/Browse channels.
App stores are actively promoting their advertising tools (like Google Ads or Search Ads) and options for apps to get featured (like tops, selections, or articles.) It turns out more costly to promote apps based on search traffic, which requires a large investment in paid tools. That’s why an option to get some traffic from app recommendations for free may be quite tempting.
How are similar apps selected?
Algorithms can rate by category, text metadata, app stability, tags, average rating, videos, if any, and graphics metadata. The hypothesis is the last factor. Many people say that algorithms are graphics-oriented. But there’s no direct evidence for that. There are some experiments showing that Google Play algorithms can read the text in icons and screenshots. Even if it’s true, it’s not clear to what extent that might affect app recommendations.
On App Store, app recommendations appear in the You Might Like section. Now attention—here’s an insight! App Store can recommend apps with user base overlap.
App Store recommends apps with user overlap?
That’s news for sure. And here’s how we came to this discovery: one of our projects, the Pushapp agency, has been promoting apps for many years, in particular using motivated traffic. We were promoting two different apps at the same time. After a few months, they began to appear in our app recommendations. The apps weren’t connected in any way since categories and topics were different. Well, user overlap was exactly the point. The same user base installed both apps, and the App Store algorithms began to suggest them to us. We have other cases too where that pattern worked. The apps were small, and they could hardly have overlaps other than a motivated user base.
What factors are most significant for algorithms?
Okay, you want more traffic from app recommendations. How do you get there? To understand which factors are most significant, we did a little research.
- United States;
- 2 stores;
- 89 categories (except for children’s);
- 17,957 free games;
- 35,572 free apps.
We analyzed 500 popular apps in each category. The focus of the research was on the top 1-15 recommended apps. Lower positions are unlikely to be a significant source of traffic.
The data below is a comparison of apps recommended by the store with the ones on whose page they appeared. Let’s look first at apps, then at games.
Apps on App Store
- The category is the same for 88.9% of apps.
- In 73.8% of cases, the number of ratings is higher.
- In 59.9% of cases, the average rating is higher.
- In 71.6% of cases, ASOindex is higher.
- In 86.2% of cases, the apps have, or don’t have, a video.
- Keyword overlap makes up 11.4%.
Apps on Google Play
- The category is the same for 38.9% of apps.
- In 82.2% of cases, the number of installs is higher.
- In 86.4% of cases, the number of ratings is higher.
- In 71.1% of cases, the average rating is higher.
- In 86.3% of cases, ASOindex is higher.
- In 68.6% of cases, the apps have, or don’t have, a video.
- Keyword overlap makes up 19.2%.
We did this research as part of developing our new Performance section. It can help you find out how efficiently you—and your competitors—are acquiring organic traffic in different countries. We’ve described it in detail here.
Games on App Store
- The category is the same for 22.9% of apps.
- In 73.4% of cases, the number of ratings is higher.
- In 59.3% of cases, the average rating is higher.
- In 73.2% of cases, ASOindex is higher.
- In 56.5% of cases, the apps have, or don’t have, a video.
- Keyword overlap makes up 9.8%.
Games on Google Play
- The category is the same for 41.5% of apps.
- In 70.1% of cases, the number of installs is higher.
- In 79.3% of cases, the number of ratings is higher.
- In 65.8% of cases, the average rating is higher.
- In 76.6% of cases, ASOindex is higher.
- In 55.4% of cases, the apps have, or don’t have, a video.
- Keyword overlap makes up 15.3%.
P.S.
Game and app data differs from store to store. It’s important to note that the values are average ones. They may vary depending on the category. A more detailed study is on its way. Stay tuned!
