From the last article, you have checked retention in two ways. It’s time to improve the retention rate. You should, of course, monitor indicators to diagnose current situations. However, if you don't take any real action with this information, it becomes meaningless.
Let’s check the retention curve derived from cohort analysis below.
As shown in the image, you can improve retention by making action plans. After the execution, you should optimize the action plan based on the result, which is retention rate. (As it is easy to handle, e-commerce players normally follow the retention rate and improve action plans on a monthly basis.)
The most retention curve becomes gentle after a steeply falling section, so you should establish separate action plans for each section.
For example, if customers leave a lot between the first 0 ~ 10 days, you can establish a hypothesis based on the purchase drivers for the first order. And you should track retention rate after executing the action. After ten days, you can repeat the promotions and optimize them to make people repurchase
You should make action plans according to your business’ condition. In the case of Company A, they focus on the initial section which has a large churn to improve the retention curve. On the other hand, in the case of Company B, which steeply falls on the long-term curve, they focus on slowing down the section.
So far, we've seen how to check and improve the retention in total. However, it is not enough to analyze the business. As many factors can affect retention, even in the short term period, It is necessary to examine the details of the variables with the Cohort analysis
For example, you can evaluate the hypothesis and action by comparing the retention of the period where a particular variable made to the previous period. You can write down all the actions you've taken, external elements, etc. as much as possible and check which actions affect the retention of the groups. You should always keep in mind that the indicators change with various variables.
Company C saw that the performance of a specific month was relatively high and the main reason was the change in membership coupon benefits. After checking it, through product changes and optimizing the landing page, they were able to achieve high results.
[Image that records variables such as promotion on a specific date]
Some variables remain in the log that you can easily track, but many important factors need to be noted manually, so we highly recommend you to manage them separately.
[Image that checking the cohort chart on a specific date that the promotion was conducted]
Looking at the cohort chart after checking the effect of promotions, you will be able to track the group's purchasing patterns.
If you have diagnosed your service through retention analysis, try to check which sections to improve, what actions to take, and the make result with MakeDashy right now!