blog | 4 min read

Acknowledging the Unequal Distribution of Customer Awesomeness

January 1, 2020

Teal datawave pattern
Editor's Note: Enjoy this blog from the Custora archive, acquired by Amperity in November 2019.

When you optimize around product or channel metrics without regard to the customers who are behind the metrics, you act as if all customers are equal. When you recognize the customers who think you’re a special brand, you can focus on making them feel special too.

What is CLV and why does it matter?

The basis of what makes CLV your most important metric is the simple fact that there are some customers in your customer base who spend a lot more money with your business than the majority of your customers.

In the broadest terms, CLV is a measure of an individual’s total spending over their entire relationship with a brand. Almost inevitably, some of your customers will make large-basket-size purchases at regular intervals while others will make just a single small-ticket purchase. The first group of customers is far more valuable; for the average retailer, the top 10% of its customer base generates roughly 50% of its revenue.

Which means that even a marginal increase in your number of high-CLV customers can work wonders for your bottom line. Consider this: assuming the 10%/50% revenue distribution alluded to above, even a modest 1% increase in your number of top customers would boost your revenue by 5%.

When you optimize around product or channel metrics without regard to the customers who are behind the product or channel performance, you're pretending that all customers are equal.

Faced with growth challenges, it can seem easier to unleash a blanket promo or just throw more money at acquisition overall. But that's neither cost-effective nor sustainable. And that's what CLV is designed to solve for: to design and execute on a strategy engineered to boost a customer segment that promises the biggest return on investment when communicated with correctly.

For some retailers, that might mean nurturing their second-highest 10% of high-value customers. For others, it might be testing campaigns to turn one-time buyers into two-time buyers. There’s no one-size-fits-all approach, but the data will tell you what to do.

Let's say you're a multi-category retailer looking at your product sales data. You notice that there are some shoes that aren’t selling so hot these days. Your natural retail reaction would be to stop selling those shoes, maybe even running a drastic markdown just to clear them out.

But imagine that those shoes are actually the entry point for your best customers. There aren't too many of these high-value customers, but when they come in, they buy the shoes and 10 other things inside of a week, and they continue to be active and loyal customers.

What would seem like a perfectly defensible decision based on just the product lens—to nix the shoes that don’t sell well—actually produces negative business results.

Flash Case Study: Winky Lux

This same logic applies to how you might assess your ad spend on certain channels. If there is a channel that has a really low return on ad spend (ROAS), you might consider cutting it. But if that's the channel that attracts your best customers, eliminating your investment in that channel is going to decimate your business in ways that wouldn't be obvious just from looking at the channel-level data.

Flash Case Study: Crocs

Optimizing for product performance or channel performance without a view of the customers behind that performance ultimately ignores the overall health of your business and sets you up to make big decisions with woefully little information.

By identifying the root cause of customer behavior without assuming that it has to do with the product or channel, you can understand the real driver of overall business performance: the people who buy things from you.

Flash Case Study: Eloquii

In short, social media engagement, product returns, promotional email open rates, and other narrowly focused metrics mean very little unless they’re presented within the context of real, flesh-and-blood customers.