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[Guide] Customer retention metrics: Multiply eCommerce profits

To create a thriving business, you need a handle on retention metrics.

This post serves as an overview of retention, and how eCommerce stores can measure their success.

Customer retention metrics overview

The key to successfully tracking retention is defining what retention means for your company.

For eCommerce stores, the most common and simplest form of retention is based around repeat purchases. But this gives a singular view on retention. 

To have a more nuanced view, stores can define multiple retention definitions, and use them to better segment customers. We've put together a few guides on customer segmentation techniques you can use below.

1. Customer retention rate: the core retention metric

The core retention metrics is "customer retention rate". Customer retention rate measures what percentage of customers continue to buy over a given period of time.

We wrote a full guide on retention rates, and I encourage you to check it out here.

In brief, we calculate retention rate by defining what a retained customer is and what time frame we are interested in.

The final equation looks like this:
(Customers Ending - Customers New) / Customers Starting

2. Customer retention curves: evaluating success over time

Customer retention rates show how a customer group is behaving in a moment in time.

Customer retention curves build on rates by plotting them over time. This results in a "curve", which allows eCommerce stores to assess efforts at bringing customers back.

To create a retention curve, simply compute a customer group's retention rate at specific moments in time and chart them in a line graph as shown below.

There are three general "shapes" your retention curves can have. 

  • Flattening curve: This indicates that a core set of customers have adopted your brand and become loyal, making regular purchases or engagements with your brand.
  • Declining curve - If the retention curve continues to decline, it indicates that your brand is constantly churning customers. Eventually churn will outpace acquisition abilities.
  • "Smiling" curve - Finally  there is a smiling curve, where a brand is able to not only establish a base set of loyal users, but actually grow this base over time (thus increasing the retention rate over time).

3. Cohort analysis: increase sales and optimize ad spend

Cohort analysis brings much more detail than retention rates or retention curves can.

As outlined in our article, "How to use Cohort Analysis to Increase Sales, Ad Spend, + More", cohort analysis is a behavioral segmentation technique focused on tracking different user behaviors over time.

While retention rates give you a moment in time understanding of your entire business, cohort analysis lets you see how specific segments of your customer base are interacting with your store.

Typically, cohort analysis is displayed in a table format, like this.

4. Purchase frequency ft. Target

The next step in understanding your customer's retention is to layer in more complex behaviors The first of these is purchase frequency.

Most brands define retention as whether a customer bought within a certain timeframe. For most businesses, that is every 30, 60, or 90 days.

However, this treats a customer who makes a single purchase in 90 days the same as one who makes five purchases.

This is where purchase frequency comes in. Recall our discussion in RFM Analysis where we detail how purchase frequency is a key indicator in which types of offers they will respond to.

Below, Target crafts a personalized email campaign to increase purchase frequency. Note how the offer, a $30 gift card, gives customers a clear incentive to come back.

5. Customer payback periods

Traditional lifetime value metrics have a number of challenges.

It is often impossible for eCommerce businesses to have enough data, it assummes your product mix, customer behavior, and acquisition channels won't change, and doesn't take into account cash flow concerns.

For these reasons, we suggest implementing payback periods as a fundamental customer retention metric.

Establishing a payback period lets you have concrete data around your metric. It also has the benefit of focusing your attention on the most pivotal moments a customer has with you - the first 30 days after purchase.

Next steps....

Barilliance helps eCommerce stores improve retention metrics by

  • Connecting data- Especially important in an omnichannel world, Barilliance can sync customer sales data across channels to properly define retention
  • Defining customer segments - Second, you can make powerful behavior based customer segments across any type of action that you define as "retained". 
  • Personalizing offers - Finally, Barilliance empowers customers to capitalize on gathered data and make personal, relevant offers to increase conversions and repeat purchases.

If you would like to see how Barilliance can help you create personalized retention marketing campaigns, request a demo below.

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