A cohort analysis is a powerful tool that helps us observe trends and behaviors over time. It may seem scary at first glance, but once you understand it, it becomes straightforward and insightful. So let's learn how to read a cohort analysis chart!
Breaking Down the Chart
Cohort charts usually share the same structure, making them easy to read once you get the hang of it. Each row represents a cohort of customers, while each column represents a month following the cohort's creation. Month 1, or the first 30 days, is the acquisition month. For example, if a cohort was created in January, Month 1 would be the first 30 days after the first order date, Month 2 would be 30 - 60 days after the first purchase, and so on. The values in the cells represent the metric you’re analyzing, such as LTV. But of course, RetentionX can also analyze other metrics, such as retention rates or number of orders.
What is a Cohort?
A cohort is simply a group of customers based on their first order date. For instance, customers who made their first purchase in February 2024 form the February 2024 cohort. These customers will always be part of this cohort, and any subsequent purchases they make will be tracked to analyze their behavior over time. Understanding cohorts helps in identifying patterns related to the time period of the initial purchase.
How to Read a Cohort Analysis Chart
1. Horizontal Analysis (Left to Right)
Reading the chart from left to right shows how a cohort progresses over time. You can observe trends such as growth, flattening, or decline. For example, you might track the LTV three, six, and twelve months after acquisition to see how it evolves.
2. Vertical Analysis (Up and Down)
Reading the chart from top to bottom allows you to compare different cohorts. This helps in understanding how various cohorts perform relative to each other. For example, the average LTV of the December cohort versus the March cohort may reveal differences that can be tied to specific acquisition strategies or external factors. In addition, the color coding helps you to quickly identify best and low performing cohorts as it compares the cohorts performance to the weighted average of all cohorts during the selected time period. In this case, we can immediately see that the March 2024 cohort is of high quality, highlighted in green, while the newly acquired customers in May 2024 have a much lower LTV in their first month.
3. Diagonal Analysis
The last way to look at your cohorts is diagonal. Diagonal reading shows purchasing behaviors across cohorts at the same point in time. For instance, analyzing all purchases made in November across different cohorts can highlight seasonal trends like holiday shopping spikes.
Analyzing cohort behavior provides valuable insights, such as:
- Effectiveness of targeted campaigns
- Impact of seasonal promotions
- Customer retention trends
Cohort analysis is extremely helpful to identify both problems and wins in the customers' lifetime. Customers remain in their respective cohorts, allowing continuous monitoring of their purchasing patterns. This can reveal characteristics of your best and worst-performing customer groups.
Advanced Insights with Segmentation
Segmentation is key to deriving deeper insights. By dividing your customer base into smaller segments, you can uncover specific patterns. For example, after conducting a broad cohort analysis, you can perform a separate analysis on customers from a specific marketing channel. Comparing these results can indicate which channels attract more valuable customers. The same process can also shed light on the effectiveness of your products, sales strategies, and engagement methods.
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