Long-term Relationships with Customers: Existing Customer Marketing via Cohort Analysis
Returning customers are essential for every online shop as they ensure profits in the long term. Collecting and analyzing customer data is the first step towards an optimized marketing mix for long-term customer retention, because insights into repurchase behaviour of specific customer groups enable the marketer to address existing customers individually and thus gain their long-term loyalty.
So – what data is necessary to understand my customers’ repurchase behaviour? And how can I deduce the right action recommendations?
Gaining an overview: cohort analysis by month of first order
First insights into customers’ repurchase behaviour are offered by the cohort widget in the minubo web frontend – here, customer groups (cohorts) segmented by the month of their initial order are monitored including their repurchase rates in the course of the following months. How many months after their initial order did how many costumers of which cohort place another order?
A first insight
It becomes apparent that the July cohort shows the whole data set’s highest repurchase rate amounting to 4,14% after five months (in December). Apparently, the right marketing mix has been applied here to successfully stimulate repurchases.
Detailed analysis: Getting started with the minubo Excel frontend
In the minubo Excel frontend, this value can be analyzed in detail. Excel can drill-down a great variety of metrics to several dimensions by using Pivot Tables and thus allows you to create very detailed analyses with just a few clicks of a mouse.
Going deeper into the analysis of the July cohort
This analysis displays the July cohort’s performance over time. As already seen in the web dashboard, the December values turn out to be significantly high. But what also becomes visible in this detailed analysis is the remarkable average order value of this month: It is vastly higher than in the previous ones.
Drill-down by marketing channel
These values raise two questions: Where do high shopping cart values originate from? Which marketing channels were successful drivers?
To find out, the timeline is dragged to the filter, too, and only December is selected. Additionally, the various metrics (number of customers, average order value, revenues etc.) are replaced by just a single one: gross order value after discounts*, attributed by the “Last Touchpoint” model. Breaking down the value at a marketing channel level, it becomes apparent which channels lead to the highest order revenues. Now, the Pivot Table as shown on the left:
* The “Last Touchpoint” attribution model is especially suitable when analyzing which channels gave the final impulse to buy.
Weight and evaluate touchpoints purposefully
Towards the goal of optimizing the existing customer marketing mix, not only Last Touchpoints, but all Touchpoints of a successful journey have to be considered in terms of how they contributed to the final purchase decision: First Touchpoints as purchase initiators as well as Assists functioning as purchase supporters. One possibility of weighted touchpoint analysis is the “Bathtub” attribution model.
Touchpoints weighted by the „Bathtub“ model
Applying the “bathtub” model, it becomes apparent that the channel “Partner” ranks far better than before. This fact reveals that “Partner” admittedly was very often not the Last Touchpoint before the actual purchase, but frequently initiated or supported it. When starting to optimize marketing spending, this needs to be taken into account.
Revealed: The most important marketing channels
By sorting order revenues using the bathtub model, it becomes apparent which marketing channels contributed most to the July cohort’s high repurchase rate in December.
Direct, SEM (brand), Affiliate and Newsletter (CRM) are the most outstanding drivers for the remarkably high repurchase rate of the July cohort in December. In the future, marketing investments can be allocated in a more target-oriented way thereby increasing overall profitability. For example, weaker channels such as price comparison or non-brand SEM should be treated carefully regarding further investments.
For the purpose of more detailed action recommendations towards achieving an optimized marketing mix, a deeper analysis on a campaign level is needed. By successfully reactivating profitable costumers through the right channels and campaigns, it is possible to increase margins by up to 12%.* Read more about it in a further minubo use case! Coming soon…
*based on anonymized costumer data