What Marketers Get Wrong About CLV
With the frantic pace of business, it’s not surprising that marketers are often too focused on the short-term. They’re constantly chasing new customers to replace churners and trying to optimize conversions with minimal investment in customer retention. But just as you can’t spend your way out of a recession, you can’t market your way into sustainable growth – especially if most of those marketing dollars go towards acquiring unprofitable customers who won’t stick around long enough for it to matter. That’s why understanding CLV is critical to effective marketing and retention efforts.
CLV, or Customer Lifetime Value, is the total amount an average customer will spend with your company over the course of their lifetime. CLV is important because it can help you determine which customers are most valuable, what characteristics those valuable customers have in common, how much you should spend on particular customer segments, which channels perform the best for those customers, and how to find new opportunities.
The formula for determining CLV is pretty simple. But there are many ways marketers get it wrong. Let’s take a look at some of the most common things you might be missing when you calculate CLV.
Not differentiating between contractual and non-contractual customers
In contractual settings, e.g., subscription business, we know when a customer has churned: they cancel their subscription. In this case, it’s relatively “easy” to observe churn rates. On the other hand, in non-contractual settings, we never know for sure when a customer has churned – maybe they’re gone, or maybe they’re just in the middle of a purchasing hiatus. In that case, we can’t observe retention rates, and using this formula becomes tricky.
Using only one “average” churn rate
All customers are not created equal. Each customer has their own propensity to churn (observable or unobservable) – some are more sticky, while others tend to churn quickly. This is called customer heterogeneity. A good CLV model takes into account differences across customers, otherwise, you will significantly underestimate the value of your customer base and your company overall.
Relying on historical sales to identify customer value
It’s not uncommon for companies to use historical sales as a measure of customer value. This is a big mistake, as customers who were good in the past will not necessarily be your best customers in the future. A good CLV model must accurately translate past purchasing dynamics into an accurate prediction of future behavior.
Limiting the time frame
We often see such things as a 6-month CLV or 1-year CLV. While it’s much easier to calculate them, they also have limited value. Unlike true “lifetime” value, they don’t tell you how much you can spend to acquire customers, can’t be used to value your entire customer base, and overall create a short-term view of customer value.
Assuming customers spend the same over time
Assuming customers will keep spending the same amount of money in the future is a simple but usually wrong assumption. First of all, every customer is different (customer heterogeneity again) and has their own spend propensity. In addition to that, customer spend can vary over time – it’s not uncommon to see revenue expansion over time, especially in a B2B setting.
Knowing what NOT to do certainly goes a long way towards knowing what TO do. Using your customer data to build a solid understanding of their spending behaviors across segments and over long periods of time will give you the insight you need to deploy effective marketing to attract more of your best customers, and retain them! And partnering with Theta is a great way to unleash your data and take your CLV to the next level. Let’s talk.
