User Retention Cohort Analysis is easy to compare how different user groups behave over time in onboarding, registration, purchasing, and uninstalling.
Visualize Engagement & User Retention Via Cohorts
Do not let activity of the new users conceal the lack of engagement from the dormant users. User Retention Cohort analysis helps you understand and group users who have demonstrated a certain behavior in your app, then track their actions on a daily, weekly, or monthly basis.
Measure User Retention Cohort Analysis, engagement, or business metrics such as time to purchase or how a cohort reacts to a new feature release.
Product Stickiness Cohort
Determine the sticky quotient of a features and how often users can actually use it. Allocate resources to build complementary new features or enhance existing features
Measure how long it takes for first time purchasers to make their further purchase. Retention is often associated by how successfully your application encourages repeat behavior. Keep users coming back for more.
Compare User Retention Cohorts
Identify particular patterns in user behavior to measure the success of your retention strategies on different groups of users. Analyze your users by product acquisition source, category, geography, or customer type, and understand the differences in cohort behavior.
Optimize the On-boarding Experience
Cohort analysis helps you to identify how long it takes before different user cohorts drop-off. With user retention cohorts, you can improve on-boarding experience of users to ensure that they reach the core value of your app as quickly as possible.
In order to track how users behave over time to time or how the same behavior differs for different cohorts, cohort analysis helps to compare these people by the way or time they were assigned or by the retention of those users over time.
But, how to break the users of groups into cohorts for cohort analysis – can be done in two ways:
- Acquisition Cohorts divide users when they signed up first for your product. For your application users, you might break down your cohorts by the day, the week or the month they launched an app, and thereby track daily, weekly or monthly cohorts.
In this case, by analyzing the retention of these cohorts, you can determine how long people continue to use your app from their start point.
- Behavioral Cohorts divide users by the behaviors they have taken in your application within a given time period. These could be random number of discrete actions that a user can perform – App Install, App Launch, App Uninstall, Transaction or Charged, or any combination of these actions / events.
Behavioral Cohorts: Customer Retention Analysis
A sample example of behavioral cohort can be all users who read reviews prior to purchasing a product. This can answer interesting questions, like,
- Are the users who read reviews have a high prior conversion rate than those users who don’t read reviews, or
- Are the users more engaged – longer sessions, more time in application, fewer drop-offs
Cohort Analysis to Improve Customer Retention
Cohort analysis always looking at the groups of people, over time, and observing how their behavior changes.
For instance, if we post out an email notification to 100 people, some may buy the product on day 1, less on day 2, even fewer on day 3, and so on. But, if we send random email to 100 people, after few weeks, they’ll be buying the product on their “day 0”while the first sent email might show its prevalent lag effect on the buying decision.
Cohort analysis is a simple, yet effective way to understand the performance of your acquisition efforts and marketing retention. We at Locus IT provide Oracle Cohort Analytics training, Cohort Analytics support, Cohort Analytics implementation services and Cohort Analytics Staffing. For more information please contact us.