Email Marketing: Simple Subscriber List Retention Analysis using Excel or Google Sheets
Subscriber retention has its roots in the newspaper industry. Several years ago, I worked for a Database Marketing company specializing in Newspaper Subscription Analytics. One of the KPIs for segmenting and marketing to subscription prospects was their ability to retain. We didn’t (always) want to market to prospects that would not retain well so, when we tried to acquire quality prospects, we would market to neighborhoods and households that we knew retained well. In other words, they didn’t grab the 13-week special and churn; they would renew and stick around.
To analyze how well the product was doing and how well our marketing was doing, we would continuously analyze our customer retention. This would help us stay on goal. It would also help us estimate how many customers would leave versus stay so we could schedule our acquisition campaigns accordingly. In summer months, when folks would go on vacation, we might market to low-retention prospects simply to keep the counts up (subscriber counts = advertising dollars in the newspaper industry).
The Retention Curve
A retention curve is a visual representation of customer retention over a period of time, typically shown as a line graph. It tracks the percentage of customers who continue to engage with or use a product, service, or platform after a specific starting point, such as the first purchase or registration date. The retention curve helps businesses understand how long customers stay active and can highlight patterns in customer behavior.
In the Google Sheet I provide, we display both the retention curve as well as the churn rate by week:
In sales and marketing, retention curves are valuable for:
- Evaluating Customer Loyalty: By showing the rate at which customers stop using a product, companies can gauge the stickiness of their offerings.
- Improving Customer Lifetime Value (CLV): Insights from retention curves can help identify the point where customers are most likely to leave, allowing targeted interventions to prolong engagement.
- Optimizing Marketing Strategies: Retention data helps teams understand what factors contribute to customer longevity, informing decisions on customer experience improvements, loyalty programs, and personalized offers.
- Predicting Growth and Revenue: A high retention rate suggests a steady customer base, which is crucial for forecasting revenue and developing long-term business strategies.
Retention curves are often segmented by cohort (e.g., month of signup, acquisition channel) to identify trends and compare the effectiveness of different marketing campaigns or customer onboarding approaches.
I’m surprised that, given the value of an email address, email service providers (ESPs) don’t offer Retention Analysis. Retention Analysis on email subscribers is valuable for several reasons:
- Low retention leads to high junk/spam reporting. Monitoring your list retention will help you build your reputation and avoid deliverability issues with Internet Service Providers.
- Setting retention goals is a great way to ensure your content is up to par. It will tell you how many times you can risk poor content before a subscriber decides to bail.
- Retention analysis will tell you how badly your lists are degrading and how many subscribers you must continue to add to maintain your list counts and, as a result, your revenue goals.
How to Measure Retention and Attrition on your Email Subscriber List
The example I’ve supplied here is made up, but you can see how it might help. In this case (see the chart), there’s a drop at four weeks and another at ten weeks. If this was a real example, I might want to make a firm offer around the 4-week mark that entices the subscriber! Same at week 10!
The spreadsheet I am using basically takes every subscriber and calculates the date they started and their unsubscribe date (if they’ve unsubscribed). Be sure to check out the calculations—they do an excellent job of hiding information that should be blank and counting only on conditions.
The resulting grid holds the total number of days they were subscribed if they have unsubscribed. I will utilize this information in the second portion of the analysis to calculate the retention rate for each week.
A retention curve is pretty standard in any industry that measures subscriptions. Still, it can also be utilized to analyze retention for other sectors – food delivery (how many deliveries and how often before someone leaves for good… perhaps a special ‘thanks’ right before that point is in order), haircuts, movie rentals… you name it, and you can calculate attrition and retention for your clientèle.
Retaining clients is typically much less expensive than acquiring new ones. You can use Retention Analysis to calculate and monitor your retention curves.
With my fake example, you’ll see that to maintain my list counts; I have to add another 30+% of subscribers within a few months. There are currently no Email Marketing standards for Retention Analysis, so depending on your industry and your campaigns, your list retention and attrition may vary dramatically.
Download The Retention Spreadsheet
This is just a rudimentary sample that I put together for this post. However, it contains all the information you need to analyze your retention. Open the sheet and copy it to your Google Workspace account.
Let me know if you need assistance executing this analysis on your lists! It also comes in handy when you have household, demographic, behavioral, content, and expense data. That allows you to do incredible segmentation better to target your marketing and content to your audience.
