Last July, we announced the new Cohort Report and, as promised, we continued developing new features and enabling new insights to give you a deeper look into how your users engage with your app.
We’re now excited to bring you two new updates that will help you make the most of Cohort Reports.
All of your performance and ad spend data in one place
It often happens that marketers spend money on acquiring new users and end up targeting existing ones (and vice versa!).
This overlap can cause quite a few issues when trying to analyze campaign performance. In order to accurately analyze cohorts, marketers need a tool that gives them enough flexibility and granularity to tease out the right insights and help them make more informed decisions about their campaign optimizations.
With the new Unified view, both UA and remarketing managers can now get an accurate breakdown of their cost and campaign performance data for both new users and existing users, all in one place.
Having a unified view of all the critical data about campaign performance in one place gives marketers the ability to see their true campaign ROI and make informed decisions every step of the way.
Optimize your cohorts by specific KPIs
Marketers across verticals and industries can benefit from Cohort Reports with a vast selection of groupings and KPIs. Whether you’re checking the performance of a weekend shopping campaign or assessing retention according to booked rides, AppsFlyer’s Cohort Reports has the tools you need to understand how your campaigns are performing over time.
But, what if you want to drill down and find out how a specific KPI performs over time?
With the new KPI by Attribution Time view (what we call “trend type” in the AppsFlyer dashboard), users are grouped by conversion time (date).This enables you to evaluate campaign performance over time and to view campaign KPIs relative to the conversion time (date).
Here’s an example:
An advertiser wants to compare the performance of two email remarketing campaigns. Emails are sent on Mondays and Fridays. In order to analyze the performance of these two campaigns, let’s say on day 3, the advertiser can now select the new view to see how much revenue was generated on that day on the y-axis and how both campaigns performed over time.
The result concluded that the ‘Friday’ campaign had a stronger start but soon both campaigns matched performance and displayed a similar reduction towards the end of the month.
Having a new view on how campaigns perform over time enables new insights and allows marketers to optimize their campaigns according to a specific KPI.
Stay tuned for more updates!