Compareitor’s Core App had a retention problem, users install the application once a year for hiring car insurance and afterward delete the application. In addition, the rest of the products that can be compared on the service (telephony, financial products, travel, electricity, spare parts of cars, wheels …) go unnoticed for the user.
The retention of the app was at 17% while the average of the sector is 30%. So one of the strategic objectives of the year was to reach this 30%
The hypothesis I wanted to contrast was: Can I improve the user experience by correctly using push notifications in the app?
So I define an action plan:
Investigation: ¿What our users think of push notifications in apps?
Evaluate the technology that exists in the market and its cost and compare it with the cost of following the development internally.
Define a user experience that does not trigger the drop-off.
Evaluate the implementation. The criterion of acceptance for this sprint was that at least increase the retention by 5%
My technical team told me that they had worked on a push notification system based on Firebase for the app but that it was not finished. On the other hand, based on the concept of the customer life cycle, I elaborated a statistical model in which, depending on the age of the user and the date of the year, a conversion probability could be assigned to each of the products.
I evaluated 5 suppliers and finally decided that the technical team should continue its development of push notifications. We also develop a management dashboard and an engine to manage the logic of notifications.
It was complicated to define a proper user experience there was no expertise on the company about doing something like this. So I create a cross-section workgroup
1 person of branding,
1 person of graphic design
1 from the marketing team
1 from customer care
After 3 meetings we define the briefings and the contact plan for every group of customers.
After 1 month of tests, we launched the functionality to production and we managed to dramatically improve the retention especially on iOS where we got to have cohorts of 41%. The improvement in Android was slower and we reached a 27% retention. We also valued the rest of the company’s services and managed to improve revenue per user by 25%.