Data Driven Marketing using Cohorts
This post is aimed at marketers, to help them identify hidden trends in their data using some conventional data driven analysis via Cohorts and drive marketing efforts where its critical.
Data is a strong suite of some digital marketers while some struggle with big sets of data. It’s becoming easier than ever to process arrays of time series data to derive interesting insights. These series of posts are aimed at marketers, to help them identify hidden insights in their data using some conventional data driven analysis and help focus marketing efforts where its critical.
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We’ll start with Cohorts.
Cohorts are a conventional form of data driven analysis, they help you identify a “behaviour” or “trend” of a group of people over a given time period. Imagine all the users who install your app on day zero, a cohort analysis will help you see how that ‘cohort’ of people behave (which events do they perform) on Day 1, Day 3, Day 7 and so on. Cohorts can help answer common questions like – “How does the on-boarding cohort look like?” or “They explore our app well, but are they converting?” or “Each download is costly, why are my sign ups so low?” or “What did they do just before installing?” or the pseudo intellectual one,”Where’s the ‘drop-off’? No one knows. Most tools draw an on-boarding or attrition cohort out of the box however would’t it be interesting to be able to do any event to any event cohort?
Marketing campaigns using Cohorts
Cohorts are only seemingly complex, idea is to read them left to right with two events in mind. I’mm going to go through a few uncommon ones today.
Retention Cohort : This cohort shows how many people App Installed for the first time, and went on to perform App Launched again on subsequent days.
Campaign Strategy : A drop from 60% on an average to 20% on day 6 is an overwhelming loss of new users not returning to the app. Two marketing strategies to consider would be to either
(1) Ensure a consistent return by engaging non-returning users on days following the install or
(2) Identify a significant drop on a particular day, and target a campaign for that day. Something like this;
Feature Cohort: The unique ability to plot any event to any event cohort makes CleverTap cohorts one of a kind. Feature cohorts are fun and help you determine sticky quotients of any features/section/functionality and how often do users actually use them. Here, the users are in fact returning to use the feature but there’s a sharp difference when comparing usage on Fri-Sat-Sun to Mon-Tue-Wed.
Campaign Strategy: A cohort of people are not using certain features of your app at all on the weekends, a good campaign to do would be an in-app nudging users on the day they do use the feature to use the feature on the weekends for an added incentive.
Attrition Cohort : Reinforcing the any event to any event ability + App uninstall tracking out of the box, you can not only look at standard attrition (Install to Uninstall) but rather any event to App Uninstall. Some exciting ones you can track are Charged to App Uninstalled, On-boarding Completed to App Uninstalled or App Crashed to App Uninstalled.
ProTip: App Uninstalled to App Launched – how many people are actually reinstalling your app.
Campaign Strategy: You can identify popular patterns which are major causation factors for an Uninstall. The cohorts shows a trend of people uninstalling the following day of an event App Crashed. On an Action’s date and time trigger campaigns here can save the day, it lets you react immediately to a crisis situation (email or push notification) and offer to serve better, report the error or buy them a candy if you have to.
Cohorts can be extremely useful to determine a broader audience behavior trend and help you drive campaigns that really matter. Looking forward to some awesome cohort driven campaigns on CleverTap, we’ll talk Funnels next week. Comments go in the comment section.
Learn more about CleverTap Cohorts