Email Marketing: List Retention Analysis

Approximately 5 years ago I worked for a Database Marketing company specializing in Newspaper Analytics. One of the key metrics for segmenting and marketing to prospects for subscriptions was their ability to ‘retain’. We didn’t (always) want to market to prospects that would not retain well so, when we wanted 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 then bailed, they would actually 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. As well, it would also help us to estimate how many customers would leave versus stay so we could schedule our acquisition campaigns accordingly. In summer months where 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).

Here’s a sample Retention Curve:

Retention

Why should you analyze List Retention?

I’m honestly surprised that, given the value of an email address, email marketers have not adopted Retention Analysis. Retention Analysis on email subscribers is valuable for a number of reasons:

  1. With low retention comes high junk/spam reporting. Monitoring your list retention will assist you in building your reputation and avoiding deliverability issues with Internet Service Providers.
  2. Setting retention goals is a great means of ensuring your content is up to snuff. It will basically tell you how many times you can risk poor content before a subscriber decides to bail.
  3. Retention analysis will tell you how bad 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 List:

The example I’ve supplied here is totally made up, but you can see how it might help. In this case, (see the chart) there’s a drop at 4 weeks and another at 10 weeks. If this was a real example, I might want to put some dynamic content in around the 4 week mark that really adds some zip to the campaign! Same at week 10!

Subscriber DaysTo start, 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 a nice job of hiding info where it should be blank and counting only on conditions.

You’ll see the resulting grid holds the total days they were subscribed if they have unsubscribed. This is the information that I will utilize in the second portion of the analysis to calculate the retention rate at each week.

A retention curve is pretty standard in any industry that measures subscriptions, but it can also be utilized to analyze retention for other industries – 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 that). With my fake example, you’ll see that simply to maintain my list counts, I have to add another 30+% of subscribers within a few months. There’s 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:

Retention Spreadsheet

This is just a rudimentary sample that I put together for this post. However, it holds all the information you need to be able to analyze your retention. Simply right-click the chart below and do a ‘Save As’ to download the spreadsheet I’ve built locally.

If you need assistance executing this type of analysis on your lists let me know! It really comes in handy when you have household, demographic, behavioral, content, and expense data as well. That allows you to do some incredible segmentation to better target your marketing and content to your audience.

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