Cohorts by Retention Rate

To boost customer retention you must identify what makes existing customers stay. So let's take a look at your Cohorts by Retention Rate: 

Definitions

Without cohort analysis, it is difficult to establish correlations between customers and profitability, especially in terms of scale. But before you dive into data analysis, let's ensure that we are on the same page. The Cohorts by Retention Rate report breaks down your customers into related groups to gain a better understanding of their purchase behaviors.

In this case, you have the option to divide your customers by when they placed their first order or by when they placed an nth order (could be their first order or not). By measuring the retention of these cohorts, you can determine how many of your customers continue to buy from you after they have made a purchase from your store. You also have the ability to see an overall view of the weighted average per column in the first row of the report.

The color of the cell is indicating the performance of that cohort compared to the weighted average for the column, with a color scale that goes from the darkest green, indicating the best performance against the average, to the darkest red, indicating the worst performance against the average.

Let's take a look at the definitions:

New Customers vs Customers

For this analysis, it's up to you to decide how you want to build your cohorts. By default, we group your customers based on their first order date, but you have the option to change this to create a cohort based on order date.

• New Customers: analyze only the customers acquired in a certain period. Can be useful, for example, to review the performance of a certain acquisition campaign.

• Customers: get a wider view and see all customers that placed an order in this period, regardless of whether it is their first order or not.

Cumulative vs Incremental

You have the option to choose whether to monitor the KPI development of your cohorts in a cumulative or incremental way:

Let's explore what this setting implies:

• Cumulative: Shows the aggregated retention rates over time for the cohort.
  Taking a look at Dec 2022: From customers acquired in Dec 2022, 6.05% came back for another purchase during their first 30 days. The share of retained customers from this cohort increases to 8.51% within the first 60 days.
• Incremental: Shows the change of the retention rates within specific time periods.
  Taking again a look at Dec 2022 again: From customers acquired in Dec 2022, 6.05% came back for another purchase during their first 30 days. Between 31 and 60 days, you were able to retain additional 3.05% of your customers from that cohort.

Use cases

Isolating and analyzing cohorts is powerful when you want to quantify the response to short-term marketing campaigns as an email campaign including a one-day coupon. This report can also show how the behavior and performance of individual user groups changes from week to week, month to month, or year to year compared to the time your customers were acquired. So let's find out:

• What percentage of my customers place a second order at all?
• After what time, what percentage of my customers place a second order?
• Have my marketing efforts been successful and were they able to accelerate the second order?
• When is the best time to re-engage with your users?

What you need

For this report to work properly, the following data must be imported:

• Order ID
• Order Date
• Customer ID

Not using RetentionX yet?

Read our full blog post about cohort analysis for Shopify stores here.