As the mobile industry is growing at a fast pace, we’re noticing shifts in consumer behavior in the mobile app market. Based on this study…
As the mobile industry is growing at a fast pace, we’re noticing shifts in consumer behavior in the mobile app market. Based on this study, we’ve drawn some conclusions that can be very important when designing your retargeting campaigns.
This report is particularly useful when evaluating the performance of your app. We take a look at a benchmark comparison between apps in a certain vertical with an average of its category to measure campaign success. Here are just a few of our key findings:
We analyzed our total app data from September to October 2015, and classified each app vertical’s user activity. Our benchmark report details user engagement trends for the following verticals:
The retention rate is a measure of how engaged users are towards the app. This can be done in different ways, but for this report, we are counting the postbacks of unique open events (discarding events with same device ID on the same day) during a number of days that follow the day of the install as a percentage of the number of total installs. To calculate the retention rate, we decided that the cohort will consider the first 13 days after the install.
This graph shows that user behavior tends to be different in each vertical, user retention for Taxi Service apps being the greatest. This can be explained by the simplicity of the service and available products to choose from. A user’s decision-making process to complete a ride is faster and the risk, in terms of price, is much lower in comparison to completing a purchase in other app verticals.
On the other hand, all the curves are declining, which is normal as not every user that installed the app will continue to use it after a certain number of days. The greater slope in the curves is from day 0 to day 1, where curves differ from one another in the rate at which “app-opens” decline on the first day. The vertical that suffers the greatest for retention drop belongs to the Classified Marketplace curve, and this can also be explained by user behavior in the app. The majority of people in this vertical tend to open the app to post something the day of the install, and may not re-open it while they wait for it to be sold.
In this report, we classified the apps in verticals to find patterns and insights from the behavior of the consumers in each of them. Advertisers and app developers can now measure their own user engagement rates to see if they stack up to the industry average. If you are running an e-commerce app and want to learn more about how to drive better engagement rates, get in touch with us here.