When calculating customer lifetime value (LTV),there is one KPI that is often neglected, clumpiness. Clumpiness is a term coined by Eric Bradlow, a marketing professor at Wharton. Think of clumpiness as binge-watching Ozark (or, if you must, Tiger King). Rather than an extended, constant period of consumption, a short, intense buying burst. By understanding and tracking this behavior, you have a significant weapon for improving LTV.
Defining clumpiness
Clumpiness refers to the fact that people buy in bursts and that those customers could be extremely valuable. When calculating customer value and segmentation, we focus on analysing recency, frequency and monetization of the customer (what Bradlow refers to as RFM). This analysis is based on customers making purchases in a regular pattern, i.e. coffee, diapers or milk. Bradlow’s analysis, however, shows that for certain products (and I would classify social and casino games here), customers actually monetize in bursts. Thus, you need to add C for clumpiness to your RFM modeling.
Why clumpiness is important
Bradlow researched how to predict the future value of customers (predicted LTV). Bradlow explains, “[l]et’s imagine you want … to predict who are going to be the valuable customers in the future. And you have four things you can use to predict it. As I mentioned: recency, frequency, monetary value and let’s say the marketing spend towards the customer. Those are the classic ways in which companies build what are called scoring models…. [T]he findings of my research suggest that higher clumpy customers are worth more out of sample, meaning in their future value, even after controlling for RFM and marketing expenditure — which means we have found another variable that firms should track [concerning] our customers and use it to predict their worth in the future.”
This finding is particularly interesting as most companies, especially in the game space, currently base their LTV projections on the RFM model. While this calculation may have worked in the traditional retail economy, consumption has evolved, especially for digital goods. Binge consumption is a fact of life in the entertainment space, and gaming sits squarely at the center of the modern entertainment environment. This analysis is consistent with Bradlow’s findings, where he says, “[i]f you look at historically purchased goods, clumpiness really isn’t there. But if you look in the new wave, the new economy, clumpiness is pervasive in every data set I’ve analyzed.”
Using clumpiness insights
Calculating clumpiness should be easy and not require tracking any new events. It is the same data you are using to calculate R, F, M and LTV. There are then several applications for this insight:
- Incorporate it into your segmentation to get a better understanding of who your VIPs and high value players are, then focus your premium treatment (and benefits) on these players.
- Use clumpiness to predict better what players are likely to become VIPs. This will help you concentrate your early retention efforts and reinvestment.
- Focus reactivation on your clumpy players. Bradlow explains, “[i]f you reactivate them, they’ll come back and be clumpy again, and do a lot of stuff in the future. “
- Do not simply rely on the KPIs you have always been trusting. Do not rely on simple theories of how your players behave, also look at things about arrival time or when people play. People who come in bursts, then go away and then come back in bursts and then go away are fundamentally different and have a different LTV.
By understanding clumpiness, you have a more accurate predictor of LTV. Once you know how to predict your LTV, you can then impact it by making changes that drive these variables.
Key takeaways
- We normally focus on analyzing recency, frequency and monetization of the customer but by adding a new KPI, clumpiness, we get a much better understanding of their expected value.
- Clumpiness refers to the fact that people buy in bursts and that those customers could be extremely valuable.
- Clumpiness can help you better segment players, predict VIPs and target your reactivation efforts and spend.
