Binge Consumption And Its Impact On Customer Lifetime Value
Written by Eric Bradlow, GBK Co-Founder and Vice Dean for Analytics at the Wharton School
We’ve all heard of the term the “hot hand” in the context of sports. Basketball players go from missing every shot, to scoring in streaks. Steph Curry’s offensive explosion in the NBA Playoffs this week is a great example. After not shooting well in the semi-finals, Steph hit nine 3-point shots in game 1 of the conference finals.
The concept of the hot hand is something we’ve talked about countless times on Wharton Moneyball, a weekly show where statistician experts Shane Jensen, Cade Massey, Adi Wyner and I team up to discuss the world of sports and dig into questions such as ‘what sports streaks are the most impressive? How do you rank the best players?’
Until recently, many scientists dismissed the hot hand phenomenon in sports as a grand illusion. A body of research dating back to the 1980s purported to show that professional athletes do not get hot. But in recent years, there have been several studies that found athletes really do experience temporary bursts of improved performance.
Over the course of my career and through my research at Wharton, I’ve studied the phenomenon of the “hot hand” as it relates to the way consumers tend to buy products and services, or consume content. Simply put, customers who consume or buy content in bunches, then go away and come back, and buy in bunches, are more valuable to companies than customers who buy at a steady pace.
Don’t believe me? Let’s take a deeper look at how measuring binge consumption by customers, or what I call “clumpiness”, can be applied to maximize Customer Lifetime Value, yielding stronger sales and marketing ROI over time.
“The hot hand phenomenon in sports also applies to shopping.”
Maximizing Customer Lifetime Value with Clumpiness
Customer Lifetime Value (CLV) is universally accepted as a central tenet of marketing today. In both academia and practice, it is looked upon as a goal of firm value maximization. That is, more profitable firms recognize that CLV maximization yields greater cash flows and higher long run profits.
Relatedly, mathematical models that allow these firms to predict CLV are commonly based on a framework commonly called RFM.
• Recency – How recently did a given customer make a purchase?
• Frequency – How often they made a purchase?
• Monetary Value – How much did they spend?
These are the cornerstones of CLV calculations and segmentation used by countless marketers and I’m here to tell you: They’re wrong!
Well, sort of, i.e. they are incomplete.
Through research, I have demonstrated and introduced that not only are RFM crucial components to calculating CLV, there is one additional dimension that MUST be factored in: clumpiness (C) or as some refer to it, binge consumption.
“Customers who buy in bunches are more valuable to companies than customers who buy at a steady pace.”
The Hot Hand
Let’s go back to the hot hand example and the player who is scoring points in bunches. Now, juxtapose over the world of marketing and consumers and you have clumpiness, AKA consumers who buy in bunches.
My research shows those who consume or buy content in bunches, then go away and come back, and buy in bunches, are in fact more valuable than customers who buy at a steady pace.
Let me put that another way.
If a given brand knew both – how clumpy a consumer’s behavior is AND how frequently they buy – the better predictor when it comes to their future CLV is their clumpiness. I realize that may shock some of you reading that.
But the fact of the matter is my research illustrates the fact that brands/marketers should be tracking someone’s clumpiness over time, because that’s extraordinarily predictive of their customer lifetime value.
And before I forget, rest assured the “clumpiness factor” if you will, most definitely applies to B2B for we are ALL consumers at the end of the day.
With the rapid adoption of digital, mobile, e-commerce and other technologies, clumpiness or binge-like behavior by customers is happening at an unprecedented level, and is a critically important part of effectively measuring CLV.
Across the board, marketers see far stronger results when they use RFMC data versus only using RFM. By focusing on clumpy consumers as their most valuable customers, brands are able to realize far stronger CLV and profitability.
With that overview in mind, let’s take a deeper look at what various brands have done to improve CLV and better target their marketing to encourage binge purchases by consumers:
“Clumpiness or binge-like behavior by customers is a critically important part of measuring CLV.”
Image credit: Netflix, Stranger Things
Digital Consumers Behave More Clumpily
Ask your family or friends what they did over the weekend, and several will probably admit to binge-watching their favorite show on Netflix or Hulu, or immersing themselves in a new XBox game. On average, 40 to 50 percent of customers are clumpy, according to my research.
A variety of different factors can drive clumpy behavior. In the case of content, the key driver is availability. For example, Netflix releases a new season of a given show, and suddenly everyone wants to watch it ASAP. They literally plan their lives around it. People have also expanded clumpy behavior beyond digital content. We now see it everywhere — from shared services such as AirBnB, Lyft and Uber to retail and online purchases.
Consumers can go weeks in between major purchases and then get the “hot hand” making multiple purchases or consuming an unusual amount of goods or services in a short period of time, and/or spending an more money in a short period of time.
A customer may exhibit clumpy behavior when traveling, or based on a life event such as the birth of a child, getting a new job or influx of cash or income, or when certain items go on sale. Marketers must take all of these factors into account when measuring clumpiness. A company’s most valuable customers will demonstrate clumpy behavior consistently, not just around certain life events.
“By understanding clumpiness as a key facet of CLV, brands are turning the corner and seeing better results.”
Visit Clumpy vs. Purchase Clumpy – Understanding Behavior to Improve CLV
There are two types of clumpiness when it comes to consumers —visit clumpy and purchase clumpy.
The first thing to know is that consumers who are visit-clumpy are not necessarily purchase clumpy and are thus not necessarily more valuable whereas purchase-clumpy shoppers tend to have long-term value.
To elaborate somewhat on the visit-clumpy consumers of the world, these are very much akin to the classic “window shoppers” of yesteryear. Moreover, these are consumers who visit both online and off without necessarily making a purchase.
Our research shows that it’s irrelevant to the world they visit in i.e. online vs. brick and mortar – their behavior remains the same and their purchase-clumpy counterparts are significantly better indicator.
Additionally our research examined multiple retailers in specific product categories. Among the key findings were that Millennials are more clumpy than other generations and that women are more clumpier than men. This is helpful in particular because many marketers are struggling to figure out how to market to Millennials. By understanding clumpiness as a key facet of CLV, brands are turning the corner and seeing better results.
The fact of the matter is that by understanding clumpy behavior, knowing to look for it, and analyzing the level of clumpiness, marketers and other key decision makers gain a new metric for measuring and predicting CLV and choosing which customers to focus on and when. They can also gain a better understanding of customer satisfaction and react to it faster.
“Regular buyers are in fact not more loyal. Clumpy consumers are worth more money and firms need to find them.”
Defying the Odds
When I first set out to conduct the research I would have bet that the findings would indicate that regular buyers were more loyal than those who buy in clumps. Well it turns out that my research, as well as others, suggest that regular buyers are in fact not more loyal.
Many times these are subscription customers and in fact just buy without even thinking about their repurchase decision. As a matter of fact, there’s a lot of research showing that’s how you lose money. You take someone that buys in a regular pattern. And try to upsell them because they don’t even think that they’re even buying in a regular pattern.
We call it “poking the sleeping bear.” You poke somebody who’s just using your service on a regular basis but isn’t even consciously … let’s say monthly making the decision to do so. And by your saying “Hey, why don’t you also buy …product?” “Holy cow! You mean I’m spending $300 dollars a month on your product? Forget it! I cancel!” But your goal was to upsell them and instead you made them churn. So I’m not a strong believer in just observed loyalty. What appears to be observed loyalty over time, that’s not actually loyalty.
Final Thoughts
I’m sure many of you reading this will have doubts. Many of you will want to stick to the tried-and-true RFM method and you are of course more than welcome to continue to do so. But I can tell you, without reservation, that if you do not begin to also factor in C (clumpiness) you will never get a true read on your customers.
Although recency/frequency/monetary value (RFM) segmentation framework, and its related probability models, remain a CLV mainstay, companies need to extend the framework to include clumpiness to successfully predict future customer behavior.
After studying thousands of data sets from companies across categories, we’ve found that C adds to the predictive power, above and beyond RFM and firm marketing action, of both the churn, incidence, and monetary value parts of CLV. Hence, we recommend a significant implementation change: from RFM to RFMC.
Measuring clumpiness has huge practical value. Clumpy consumers are worth more money and firms need to find them, and use marketing to drive customers to binge consume.
Interested in measuring clumpiness to improve your marketing? You can learn more by watching my YouTube video here. My latest research on the topic as well as an Excel worksheet are also available upon request.
*Note: An alternate, shorter version of this article originally appeared in Marketing Land
