We have all heard of the term "burning hand" in the context of sport. Basketball players are going to miss every shot, to score in playoffs. Sometimes players are in a "zone" as it seems they can not miss. Baseball players also tend to hit circuits at home.
Throughout my career and research in Wharton, I have been studying the "burning hand" phenomenon with respect to how consumers tend to buy products. and services or consume content. In simple terms, customers who consume or purchase clustered content, and then go back and forth to buy clusters, are more valuable to businesses than customers who buy at a steady pace.
Do not believe me? Let's take a closer look at how to measure customers' excessive consumption of customers, or what I call "comfort," can be applied to maximize customer value in the long run, thus generating a higher return on investment for customers. sales and marketing over time.
CLV is universally accepted as the central marketing principle today. Both in academia and in practice, it is considered as a goal of maximizing the value of the company. In other words, the most profitable companies recognize that maximizing CLV generates higher cash flows and higher long-term benefits.
At the same time, the mathematical models that allow these companies to predict CLV are generally based on a framework called RFM. ] Recency – How long has a given customer made a purchase? Frequency – How often did they make a purchase? Monetary value – how much did they spend?
These are the cornerstones of CLV calculations and segmentation used by countless marketers and I am here to tell you: they are wrong!
Well, sort of. They are incomplete.
Through research, I have demonstrated and presented that not only RFM components are essential for calculating CLV; there is an extra dimension that MUST be taken into account in: articulation (C) or, as some refer to it, excessive consumption of alcohol.
The Warm Hand
Let's go back to the example of the hot hand and the player who scores points in clusters. Now, juxtapose the world of marketing and consumers and you have squat groups, AKA consumers who buy in clusters.
My research shows that those who consume or buy content in clusters then go on, come back and buy in clusters. , are more valuable than other customers.
Let me express this differently. If a given brand knew both factors – how well the consumer behaves and how often they buy – the best predictor of their future CLV is their agglomeration. I realize that sounds shocking, but it's true. My research clearly shows that brands and marketers should track the progressive evolution of a person's muscle mass as it can predict their CLV in an extraordinary way. By focusing on the busiest consumers as the most valuable customers, brands can achieve a much stronger CLV and profitability.
Keep in mind this overview, take a closer look at what different brands have done to improve the CLV and better target their marketing to entice consumers to make excessive purchases.
Digital consumers behave more aggressively
We are all very familiar with the video surveillance series on Netflix, or any other excessive consumption of YouTube content at games. But consumers have extended this behavior beyond digital content and we are seeing it everywhere – from shared services such as AirBnB, Lyft and Uber to retail and online shopping.
Many factors can cause agglomerating behavior. In the case of content, the determining factor is availability. For example, Netflix publishes a new season of a given show, and everyone wants to watch it quickly. They literally plan their lives based on that.
Consumers can spend weeks between two major purchases, then have the "hot hand" to make multiple purchases or consume an unusual amount of goods or services over a short period, or spend more. money in a concentrated time.
The Two Aspects of Density and Demographic Vision
There are two types of density when it comes to consumers: visit the big ones and buy big ones. Consumers who visit the slaps get close to the classic "window shopping" of yesteryear. They visit online and offline channels without necessarily making a purchase. On the other hand, demanding buyers accumulate a lot more value over time.
As part of our research we examined several retailers belonging to specific product categories. Among the main conclusions, we find that the millennial generation is lumpier than other generations and that women are more massive than men.
As marketers struggle to find a way to sell themselves, this information can be helpful. By understanding the agglomerated nature as an essential facet of CLV, brands turn the page and get better results.
By understanding agglomerated behavior, seeking out and analyzing its level, marketing and other key decision-makers gain a new metric to measure and predict CLV and choose which clients to focus on and when. They can also better understand customer satisfaction and respond more quickly.
Challenging the Chances
When I started conducting the research for the first time, I would have bet that the results indicate that regular buyers were more loyal than those who were buying in groups. It turns out that my research, as well as others, suggest that regular buyers are in fact no more loyal.
These are often subscriber customers who buy without worrying about their redemption decision. There is a lot of research now showing that you are losing money. You pick someone who buys according to a regular pattern and try to sell it because he does not even think he's buying normally.
We call it "sting the bear asleep". who uses your service regularly but who is not even consciously … say monthly. And saying, "Hey, why do not you buy too … a product?" You mean I spend $ 300 a month for your product? Forget it! J & # 39; cancels! But your goal was to sell them and you made them turn. I am not, therefore, a strong supporter of loyalty. What seems to be observed over time is not really the loyalty observed.
I am sure that many of you who read this will have doubts. Many of you will want to stick to the tried and true RFM method and you are obviously more than welcome to continue doing so. But I can tell you, without reservation, that if you do not start taking factor C into account, you will never read a true picture of your customers.
Although response time, frequency and monetary value (RFM)) The segmentation framework and associated probability models remain an essential pillar of CLV. Companies must extend this framework to include grouping to predict future customer behavior.
After studying thousands of data sets from companies belonging to all categories, we '#' s We found that C adds to the predictive power, beyond RFM and firm marketing action, both churn, impact and monetary value of CLV. Therefore, we recommend an important implementation change: from RFM to RFMC.
The measurement of density is of great practical value. Cluttered consumers are worth more money and businesses need to find them and use marketing to push customers to over-use.
The opinions expressed in this article are those of the invited author and not necessarily those of Marketing Land. Associated authors are listed here .
About the Author
Eric T. Bradlow is President of the Marketing Department of Wharton, Professor KP Chao, Professor of Marketing, Statistics, Economics and Education, and co-director and co-founder of the Wharton Customer Analytics Initiative. He is also a co-founder of GBH Insights, a marketing strategy, consumer behavior and analysis consulting firm. He has won numerous teaching awards at Wharton, including the MBA Core Curriculum Teaching Award, the Miller-Sherrerd MBA Core Teaching Award and the Excellence in Teaching Award. Professor Bradlow earned his doctorate. and an MA in Mathematical Statistics from Harvard University and a BA in Economics from the University of Pennsylvania.