We’ve talked a bit about why user-centric analytics are important, but you may be wondering what this information can do for you and your app. By taking one of our users, a mobile commerce iPhone app, as an example, we’ll walk you through the process and most importantly, share insights.
This particular app is extremely social in nature. Targeted actions like scanning, sharing, and comparing engage their community of shoppers. Because one of the ways this app generates revenue is through users clicking on a ‘Buy’ button, the publishers wanted to identify the user behaviors that increased the likelihood of clicks. Using ApScience, they set up a revenue funnel.
Because this sort of transactional app has multiple ways that a user can reach and ultimately click the buy button, the publishers wanted to see which types of users had the highest conversion rates. By segmenting users by their behaviors, they saw that those who scanned products rather than searched for them had a higher conversion rate—even higher than the overall rate—and then confirmed that users with a significant number of friends (on the app) converted highest of all. These two very targeted data points allowed their development team to change the user experience to favor these behaviors and generate more revenues.
Conversion funnels are standard practice in website optimization. Mobile app analytics have advanced to where we can, and should, incorporate funnels into mobile apps. Conversion and revenue optimization should be data-driven; as you learn more about your users and refine your app, you create a symbiotic relationship, better benefiting both you and them.