The subscription business model has been on the rise for years. But not all subscriptions introduced to the market are an instant success. To optimise your subscriptions, you need to properly monitor a number of crucial metrics. What are they? And what do these metrics tell you?
Netflix, Spotify, roadside assistance, the gym, cloud storage, mobile telephony… Consumers embrace subscriptions and memberships because they meet important needs, such as convenience, inspiration, continuous access to certain services or cost benefits. Companies value the recurring revenues from subscriptions, leading to increased financial stability for the company. As a result, the subscription business model is becoming increasingly popular.
Optimise your subscription business model
Yet the popularity of the subscription model does not mean that every subscription will automatically catch on. As a provider, you need to be thoughtful and customer-focused in order to maximise the chances of success. In my earlier article about the subscription business model, I gave tips that can help.
Once you have introduced one or more attractive subscriptions into the market, the real work starts, in a sense: monitoring, adjusting and continuously learning. This requires insight. With the right subscription metrics, this insight is within reach.
Make or break subscription metrics
A nice side effect of the subscription business model is that in many cases you have plenty of data to measure. However, there is also a downside to a lot of data: you can no longer see the forest for the trees, which means you are unable to gain meaningful knowledge. It is therefore advisable to focus on the most essential make or break metrics when measuring your subscription results. I list the top 8 metrics below.
1. Monthly recurring revenue (MRR)
Everything starts (and ends) with the ability of the subscription provider to generate recurring subscription revenue. The concept of monthly recurring revenue (MRR) therefore deserves a first place in the list of 8 metrics.
MRR expresses how much revenue is generated by the subscriptions on a monthly basis. There are several ways to calculate MRR. The simplest one is:
MRR = monthly average revenue per user (ARPU) x total number of monthly subscribers
The ARPU primarily consists of the subscription fee the customer pays to you. It is important to leave out one-off revenues, such as connection fees. After all, this type of revenue is not recurring.
It may be useful to further refine your MRR reports by looking specifically at the MRR of new customers. Is it higher or lower than that of existing customers? You can also show how MRR is positively affected by customers switching to more expensive subscriptions (expansion MRR) or negatively affected by customer loss (churn MRR). We will deal with the latter point in more detail later.
2. Customer acquisition rate (CAR)
It is good to know that your subscription revenue model can generate recurring revenue. The question now is whether you are also able to acquire new customers each time, so that the MRR can grow even further. An important metric to look at in this context is the customer acquisition rate (CAR).
The CAR indicates the percentage by which the customer base increases in a given period as a result of newly acquired subscribers. In formula:
CAR = (number of new customers in period n / total number of customers at the beginning of period n) x 100%.
So suppose we start with 500 customers in a given month and we acquire 50 new subscribers that month, then the CAR is (50 / 500) x 100% = 10%. A positive CAR means that we are able to acquire new subscribers.
The natural enemy of acquisition is churn. Volume churn is the number of customers lost in a given period. There are many methods for measuring volume turn, the most basic of which is:
Volume-churn rate = (number of customers lost in period n / total number of customers at the beginning of period n) x 100%.
The relationship between the volume-churn rate and the CAR is essential and determines the ability to grow. For example, a monthly CAR of 15% looks impressive, but what is the result when the churn rate in that same period is 17%? Exactly: shrinkage of the customer base. What you learn from this is that you should never consider churn and acquisition in isolation, but in the right context.
One way to give context to your churn figures is to zoom in on cohorts. A cohort is a specific group of customers, in the example below customers who entered in a specific month: January 2019, February 2019, et cetera. Each group is then tracked over time. The table shows the state of affairs in August 2019. If we look at the cohort from January 2019, we now have 8 months of history. For the cohort from August, there is no history yet, only the month of August itself. That is why the table runs back at an angle.
If we zoom in on the cohort of customers who were recruited in February, you will see that 89% of this group is still left in month 2 (11% churn). The following month, this percentage drops to 85%.
By looking at your customer base in this way, you can see at a glance what is going on with the quality of your influx of new subscribers. The table shows that something seems to go wrong with the customers who were recruited in the months of May and June. The customer loss rate there is much higher than in the previous four months. This requires further investigation by the churn specialist.
Tip: as soon as you have the right cohort figures available, it is very easy to present them in Excel in a heat map, as I did above. To do this, use conditional formatting -> colour scales.
Some churn is more painful than others. Suppose you have 200 customers. One half of the customer base has a ‘basic’ subscription and pays €10 per month. The other half are ‘premium subscribers’ and pay €25 a month. Both customer groups have a volume churn of 10%. That 10%, however, works out quite differently for the various newspaper groups:
- Loss of sales ‘basic’ = 10 lost subscribers x €10 = €100
- Loss of sales ‘premium’ = 10 lost subscribers x €25 = €250
The concept of value or revenue churn is important here. The value-churn expresses how much revenue you lose in a given period as a result of customers leaving. In formula:
Value-churn rate = (lost sales customers in period n / total sales at the beginning of period n) x 100%.
Of the total value-churn of €350, a much larger proportion is caused by the premium subscriptions. Namely (250 / 350) x 100% = 71%. In other words, despite the same number of customers and the same volume-churn percentage, the value-churn can vary enormously due to different subscription prices.
Companies do not go bankrupt due to high volume churn, but they do go bankrupt due to high value churn.
The moral of this story is that it is essential to monitor value churn as well as volume churn. Companies with the subscription business model do not go bankrupt due to high volume churn, but sometimes due to high value churn. Managing value churn is therefore a top priority within any subscription-based business model.
5. Net promoter score (NPS)
There are many strategies, tools and techniques to combat churn. In the end, however, there is only one approach that really works: a great product and satisfied customers.
How do you measure customer satisfaction? A tried and tested method is the net promoter score (NPS). The core of NPS consists of the question:
How likely is it that you would recommend organisation x to a friend or colleague?
The respondent can answer this question with a mark between 0 and 10. Based on the answer given, three different profiles of respondents emerge:
- 0-6 score: detractors (dissatisfied, not loyal)
- 7-8 score: passives (fairly satisfied, but not a fan)
- 9-10 score: promoters (enthusiastic about product or organisation)
NPS has its shortcomings, but it is an easy-to-implement method for keeping a finger on the pulse of your customers’ satisfaction. And therefore a valuable addition to the dashboard of every subscription provider.
6. Customer lifetime value (LTV)
Volumes have been written about the concept of customer lifetime value (CLTV or LTV) and the way in which this should ideally be measured. In essence, LTV represents the financial value that the customer represents over the lifetime of their contract. In its most basic form, the LTV of an individual customer can be captured in the following formula:
LTV = ARPU x customer lifetime
As a simple example, if a subscriber earns €15 on a monthly basis and stays for 24 months, his LTV can be calculated as follows: 15 x 24 = €360.
When calculating LTV, it is a choice whether to include the customer’s costs. You can then think of the costs of acquiring a customer (customer acquisition cost) or servicing the customer (cost to serve). The advantage of this is that you get a more accurate picture of the ‘net’ contribution of a customer. However, the complexity of a net LTV calculation can be a barrier.
There is obviously a relationship between (volume) churn and customer lifetime: the higher the churn percentage, the shorter the lifetime of a customer (group). You can easily derive the average lifetime from the churn percentage using the following formula:
Lifetime = 1 / churn percentage
So let’s say your annual churn rate is 14.5%. The expected lifetime of your customers is then: 1 / 0.145 = 6.9 years. If, after hard work, you are able to reduce the churn to 8%, the average lifetime increases to no less than 12.5 years.
7. Customer acquisition cost (CAC)
We have just indirectly discussed the concept of customer acquisition cost (CAC). The CAC indicates which acquisition costs are related to bringing in a customer. In formula:
CAC = total acquisition costs / number of new customers
So, suppose we acquire 50 new customers with a marketing campaign that cost €10,000, then the CAC is 10,000 / 50 = €200.
Again, you can choose whether to include only directly attributable costs, such as online advertising, or also overhead costs, such as marketing salaries. Whatever choice you make here, it is important that you work with consistent definitions that are unambiguously applied across the various departments in an organisation. Avoid departments such as finance and marketing using different definitions and therefore speaking a different language.
Case study ‘Telecom company’
One more remark about CAC. As I mentioned when discussing churn, it is essential that metrics are considered in the right context. A short case study to explain this.
A telecom company evaluates three different channels: a specialist telecom shop, a retail chain and its own webshop.
The sales department of the telecom company is initially very satisfied with the retail chain with which an agreement has been made. This channel brings in no fewer than 200,000 customers on an annual basis. The retail chain’s CAC (customer acquisition cost) also looks good and is well below that of the telecom shop.
However, the finance department points to a number of other metrics: churn and ARPU (average revenue per user). These show that the retail channel does generate volume, but much less value. After all, customers walk away quickly (32% churn) and the ARPU is relatively low. Based on this analysis, the telecom organisation decides to focus more on the telecom shop channel and its own webshop.
8. Efficiency (LTV : CAC)
Let’s continue with the case of the telecoms organisation. The sales department is now wildly enthusiastic about the telecom shop as a channel. The ARPU of the customers from this channel is by far the highest and the churn is only 8%. However, an attentive finance employee is not yet convinced and does further calculations.
His calculation of the LTV (lifetime value) confirms sales’ view: customers connected by the telecom shop generate by far the highest LTV. However, the rosy picture becomes slightly more nuanced when the CAC (customer acquisition cost) is involved. The finance department looks at the efficiency of the channels with the following formula:
Efficiency = LTV : CAC
The higher this number, the more efficient the use of the acquisition euro (channel). According to finance, the conclusion is that the webshop scores best overall, despite the fact that the churn percentage and ARPU are not as good as those of the telecom shop.
Make your subscription revenue model grow (fast)
Is there an ‘ideal’ outcome of LTV / CAC? Some claim that this value should be somewhere between 3 and 5. The thinking then is that a ratio that is too low means that your profitability will come under pressure. Think about it: a ratio of 0.5 means that you spend twice as much on acquisition costs than you eventually earn back from a customer.
A value of LTV / CAC that is too high is not ideal either. That may sound strange. You might say that it’s only good if the LTV of your customers is a multiple (e.g. 20) of the acquisition costs. This is true, of course, but a high LTV/CAC ratio also means that you are ‘leaving money on the table’. If you can acquire customers at very attractive acquisition costs (in relation to their LTV), then there is a lot to be said for putting your foot on the acquisition accelerator and making a growth spurt.
This blog was also published (in Dutch) on Frankwatching.
Subscriptions are a common thread in Bas Verhoeven's career. As a marketing manager, he introduced numerous subscriptions to the market for multinationals such as Wolters-Kluwer and Vodafone. As a consultant and interim marketing manager, he also helped many SME organisations to increase their recurring turnover.