If you came here looking for complex math on how to calculate and measure your average revenue per customer, then you’ll be mildly disappointed to find out that I tend to avoid lengthy discussions of math like the plague. Sure, math is a big part of business, but it’s the part of it I leave up to the number crunchers in my own business dealings, let alone try to discuss them intelligently here.
What I want to talk about isn’t how you come by this information, but how it can be useful to you in many aspects of your business and your customer experience at large.
Average revenue per customer isn’t the same as real value of individual customer values. However, it does provide a good overview of how much all of your customers are worth on average, since each customer individually, in real value terms, can vary significantly.
You need averages like this to assign on a wide band, because if you need customers, and their perceived values and metrics, to be units for higher level measurements. If each one of them is its own special unit, it’ll be a problem realistically analyzing most things in your business.
Let me explain. With this average value, the first thing that’s affected is your marketing and needs generation strategies at the far flung beginning of customer experience. You know what existing customers are worth on average, and thus you can also forecast what future customers will in turn be worth.
With this understanding, and knowing what potential customers would average in worth and value, you have better insight into what an acceptable budget for customer acquisition might be. Otherwise, it’s easy to overdo the budget for your acquisition, compared to the value of the customers as determined by these measurements. This would be a major inhibition of growth.
Along with this, especially in SaaS, your ability to take churn for the significance it could have relies strongly on the knowledge of these average values. In this situation, you know exactly how much a unit of churn is costing you in revenue, and how serious the problem really is. This also has meaning in the terms of growth as well as stability.
Going further with that, loyalty, which is the opposite of churn, takes on more concrete meaning and significance once you have these average values as well.
Finally, while good customer service should always be a top priority, you also need to know how much a satisfied customer is worth, and how costly a dissatisfied customer can be. With these real, average values assigned to your customers, then every metric and variable in your business has a more significant, “personal” meaning, and thus, when it’s severe, you can incentivize stakeholders to address problems, and stem them from overreacting when things aren’t as bad as rank percentages could wrongly imply.
So, the average revenue per customer is important to adding contextual, practical meaning to many other metrics and factors you must contend with and mind closely in SaaS. It’s not difficult to calculate, but that’s not what this was about anyhow. To learn about calculating this concept, research into this isn’t hard to find, and its math is explained far better than I could accomplish.
