Predictive customer lifetime value (CLV) measures the future financial worth of each of your customers during their entire relationship with your business. It’s actually one of the most important yet underused metrics for marketers across all industries. In fact, only about 34% of marketers are actually familiar with the term and its connotations. The algorithms to calculate predictive CLV vary from different marketers and different bloggers, but this isn’t a post about the math it takes, you can find that in about a million other places on the internet. This is a post that simply states why marketers should care about CLV, especially when it comes to creating retention and acquisition strategies.
Marketing has two main goals:
- To bring in new customers
- To retain existing customers and increase their CLV
Now, even though it costs a lot more to bring in new clients than retain existing clients, a majority of businesses spend much more on customer acquisitions than they do on retention. Honestly, this is sort of weird if you think about it.
80% of our profits come from 20% of our existing customers. That means we have a bucket of valuable customers with specific characteristics and behavioral traits that can help guide us when it comes to creating successful customer acquisition strategies. If we use predictive analytics, we can get answers and insights into that 20%: Who are they? What channels did they come from? What products did they like most? What can we do in our power to make them stay and increase their purchase frequency or average order value?
Predictive analytics is a type of analytics that utilizes historical and current data to make predictions about unknown future events or outcomes and/or uncover real-time insights; it is used to forecast future probabilities by looking for patterns in the information that exists. For example, with predictive analytics businesses can predict which customer will leave them for a competitor or what the type of campaign to create to maximize conversion rates.
With predictive analytics you can answer all the questions you need to understand your most valuable customers to the fullest and have a CLV benchmark number. And when you understand them better, you’ll be able to:
- Know which tactics to use to ensure they stay your customers
- Know which tactics to use to increase their CLV and spending habits
- Know which customers you should be investing your marketing dollars on
So if predictive CLV is so important, why isn’t it a priority for every marketing department across every industry? Probably because organizations are facing barriers when it comes to their data and skills gaps which can be solved with the right predictive analytics tools and platforms.
To read the full version of this article, download our e-book Predictive CLV 101 today!