In a recent post on Calculating Customer Health Scores, I had discussed the basic consideration and factors to weigh up in building your customer health score. Whilst incredibly powerful, customer health scores have limitations, most notably that no single formula for calculating the score can be applied to all businesses. Instead, you need to work out what affects your customer health, measure and combine to create a customer score. Customer lifetime value (CLV, or LTV) has a much clearer definition. As I’m no data scientist, I won’t be going into the complexities and formulas of calculating the score. Instead, in this post I want to explain what CLV is, how it can be used (and where you you might misuse it!)
Unlike customer health scores which relate to actual / current customer status, CLV is a predictive measure of the expected net profit of a customer across the entire duration of the customer relationship. Where customer health scores identify inputs (actions), CLV reflects the outcomes of those factors (plus many more within and beyond your control.) Customer health scoring is operational, used daily to drive the team, CLV is more of a trend metric for managers & management (although very useful for the front line teams when explained properly). CLV does not tell you how much you have spent to win the customer, nor what the current value of the customer is to your business. For many smaller businesses, it’s not an easy measure to calculate, but the basic equation goes something like this (although other more complex models may suit your business):
(Average Monthly Revenue per Customer x Gross Margin per Customer) ÷ Monthly Churn Rate
But let’s leave the calculations to the experts. So how why would you bother with CLV? The marketing team would love to know whether the cost of acquisition of a new customer (and also their target markets) are paying off. CLV tells them the exact amount of money you expect to make from a customer, and thus marketing can compare their spend against CLV to become more targeted and effective. It also allows the product team to understand the profitability of customers and segments, to help determine where resource and development should be invested. For customer success, knowing who is most valuable to your business means that your customer success team, resources (physical and online) can he highly organised around nurture activities to maintain retention of high value accounts. Coupled with customer health scores, the management function can determine a rounded view of their customer engagement and expected profit from their customers. So CLV is a really powerful metric across the business, but what are the pitfalls?
If you make the mistake of seeing CLV as the panacea of all metrics, watch out for these three points. Firstly, do not loose sight of the fact that CLV is a predictive number, not an actual number. Whilst the calculations can be greatly refined, it’s very difficult to build in subjective factors (customer satisfaction), or external factors outside your control (market forces, regulation, etc.) So use CLV is conjunction with other key financial metrics to reduce this risk.
Along a similar line, CLV is a dynamic number, changing with the performance of your business. The CLV is an output of your actions – so if you change the inputs (increase retention, reduce marketing spend), the CLV scores will respond accordingly. When using CLV is strategy planning, you need to factor in all the variables of change.
A final point to note is that some detractors of CLV suggest the metric overvalues existing customers at the expense of new acquisition. When used incorrectly, CLV drives focus on the highest value customers, who may already be at saturation point, rather than nurturing the large middle tier segment, where marketing spend and customer success activity could drive a more dramatic increase overall.
So CLV, coupled with customer health scores will be a friend to marketing, sales & customer success, but make sure that you calculate it correctly and base business decisions on other factors as well as CLV.