User activity ≠ value creation

4 min read

The number of logins or usage pattern are rough, and often a highly inaccurate approximation of the value created by a SaaS Product. So, in addition to basing your Customer Health score on user activity, make sure you include metric(s) more tightly coupled to the actual value created.


There’s been a lot of discussion about customer health scores lately, for example, the thread Customer Health Score vs. User Health Score in the Customer Success Forum on LinkedIn. By now it should be clear to everyone that a solid health score needs to be based on multiple independent parameters (a.k.a customer success dimensions). As discussed in one of our previous blog posts most companies will calculate their Health Score based on a weighted average of several “objective" parameters/dimensions such as Customer Activity, Executive Sponsorship, Contractual Set-up, a Subjective Score, etc.

Unfortunately, user activity as measured by the number of logins, the number of users, or even by usage pattern has for a long time been considered synonymous to value created. As a result, a lot of SaaS companies don't have a clear picture of the actual value they're delivering. It's reflected in the pricing of SaaS products which generally have been 'per user’ rather than 'per value'. As discussed in the article "Stop Per User SaaS pricing; You're Killing Growth" that kind of pricing is not only 'unfair’ to customers, it also tends to limit growth. Pre-SaaS, the number of users was often the best possible approximation for value created, and sometimes user activity still is the closest you can get, but most B2B products can do a lot better than that.

Example of Activity vs Value

Let's look at a concrete example from the HR-industry that helps us understand (a better measure!) of value creation.

Example: Different approximations of value created by an Applicant Tracking System (ATS)

An ATS is supposed to help organizations with their recruitment processes by, among other things, receiving applications and helping recruiters collaborate throughout the selection process.

1st-degree approximation

The actual value created by the ATS is the reduction in time spent by recruiters on administrative tasks, as well as the (potentially) increased precision and quality of the recruitment processes. If we could quantify that increase in efficiency and quality then we would call it a 1st-degree approximation to the actual value created.

2nd-degree approximation

Unfortunately for ATS providers and their customers, those metrics are not easily captured. Instead, they have to look for the next best approximation – a 2nd-degree approximation. In this particular case, it might be the number of requisitions/job ads published or alternatively the number of applications received and processed.

3rd-degree approximation

The number of recruiters with a user accounts in the ATS clearly has nothing to do with the value created and the number of times recruiters login to the ATS is at best a very rough estimate of the value created. This is what we would call a 3rd-degree approximation.

Understanding the actual value creation parameter(s) is a MUST for a SaaS company. It makes sense for it to influence the pricing model, and it is certainly indispensable for an accurate Customer Health Score.

Some industry specific examples

We created a table below that will help drive home the message. The table shows a few different examples of SaaS products and how a "good", "okay" and "bad" approximation measures the actual value created for the users of these products.

Please note that we're not arguing that user activity (think "logins") shouldn't be part of the Customer Health Score, only that you can often find a complementary and in the long term better Customer Health predictor. Actually, ‘usage' or 'user engagement' often serve as a good complement to your main value creation metric. Typically it's more responsive to changes and can thus serve as an early alert for potential churn or up-sell opportunities. Just remember that it’s a rough indicator of the value you’re actually creating. Also take into account the potential correlation between the two dimensions when weighting them together!

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