What’s a Typical Subscription Commerce Retention Rate?

What’s a typical retention rate for a subscription commerce business?

If you’re trying to model a potential new subscription box business, or just wondering how profitable an existing business is, retention rate is a key variable. What retention rate should you assume?

The answer, of course, is “it depends.”

But you need something to plug into your calculations. So let’s look at some potential comparables.

Retention Rate Comparables

Here’s some retention data that has been shared publicly:

(If you know of some other good public data, please let me know — this sample is a bit limited at the moment!)

Why Churn Rate Tends to Decline Over Time

If you look at the H.Bloom and Relay Foods examples, you’ll see that lots of subscribers cancel early in their subscriptions and the remaining ones tend to be more loyal. I’d expect to see this in most subscription businesses — customers that aren’t getting value from your service are likely to leave early on. Those that remain are likely to be doing so because they like the service. Consequently, as your business matures, your overall churn rate is likely to fall.

Churn Rate Varies by Acquisition Channel and Offer

You will also find that your churn rate is affected by how people sign up. At Boudoir Privé, for example, we found that, when we ran a special offer giving a discounted first box, a lot proportion of those new subscribers cancelled after they’d received that one box.

Churn Rate vs Retention Rate

I’ve been talking about churn rate and retention rate. But how are they related?

Churn rate is the percentage of subscribers who cancel in any one period. e.g. if you have 100 monthly subscribers and one month 20 of those subscribers cancel, then your churn rate for that month is 20%.

Retention rate is simply the percentage of subscribers who remain. In the example here, 80 subscribers remain and your retention rate is 80%.

retention rate = 1 – churn rate

Modelling Retention Rate for Your Business Plan

In my opinion, simple is good where possible. And I think that applies to modelling retention rates and churn rates for subscription commerce businesses.

Here are a few models you may want to use:

1. Average subscription length: Probably the simplest model (and my favourite for back-of-the-envelope calculations) is to assume an average subscription length and not worry about the details beyond that. This is good for estimating whether or not a business is likely to be profitable.

2. Fixed churn rate: To model cashflow, you’ll need to look at retention over time. One simple way is to assume that a fixed percentage of your overall current subscribers will cancel each month.

3. Declining churn rate: A slightly more complex model is to assume a slightly high overall churn rate to start with, dropping gradually over time.

Any of these approximations is probably fair for a pre-launch business where there are large amounts of uncertainty about other key factors of your model anyway.

More advanced businesses with a better idea of their numbers (or early stage ones run by ex-investment bankers) may want to look at a cohort analysis to better predict and model how the churn rate for a particular group of customers is likely to change over time.

Your assumptions about future retention rates significantly affect how profitable a business looks in the long term, so whatever approach you take, it’s worth understanding this component of your model and any simplifying assumptions you’re making.

How about you? Are you trying to model retention rates for a new business idea? What approach are you taking?

 

Comments

  1. Hi Matt,

    Thanks so much for this terrific post. Quick question: how would you build a monthly model using average subscription length (e.g. 6 months)? Right now, we built a model where Monthly Revenues = (# of total subscribers) x (Monthly Subscription Charge). We arrive at total subscribers by assuming a fixed churn rate over last month’s total subs.

    Thanks,
    Donna

  2. Matt Collins says:

    Hi Donna,

    Thanks for your question. Assuming an average subscription length is mainly just a quick and dirty way to get to an estimate of customer lifetime value. It doesn’t say anything about the shape of the distribution of subscription lengths.

    If you’re trying to model monthly cashflow, you’ll need to go further and assume the shape of the distribution, too. A simple model for that is the fixed churn rate you’re already using.

    Mathematically, I believe a fixed churn rate of ‘c’ gives an average subscription length of 1/c. So to get a 6-month average subscription length you need a monthly churn rate of 1/6.

    Does that help?

    Matt

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