Profitability – The missing piece in customer segmentation?

Mikko Varila avarea, customer analytics, Customer insight, customers, data-analytics, data-driven decision-making, profitability

It is only a few years ago, that we stood in awe at how Amazon or Zalando knew precisely what we might be interested in next. However, these days analysing individual customer preferences and marketing accordingly is an everyday part of the sales and marketing process. But what about the flipside of the coin – who should a business be approaching in the first place? Am I an attractive customer, if I repeatedly return orders, and keep customer services on speed dial?

For businesses to approach customers efficiently and profitably, they are traditionally segmented into “baskets” based on various analytical segmentation models. In addition to age, place of residence, and purchasing behaviour, segmentation models often attempt to consider the size and importance of the customer – typically based on revenue. But is bigger always better?

From the perspective of the CFO, customer profitability is equally interesting information to revenue. Profitability is calculated by subtracting customer related expenses from customer generated income, of which the former when carefully defined calls for modelling of how the customer drains company resources, either directly or indirectly through the products and services purchased: production, logistics, sales, customer support, and numerous other supporting functions.

The results of customer profitability analytics are invariably eye opening: some customers generate significant profit for the business, some are reasonably neutral, and others are causing a loss! The same is of course true for products – not all of them are equally profitable. It is also worth noting that profitability is not necessarily tied to the sales dollars a customer brings in. A large customer may also be loss making and weigh you down.

If we go back to customer segmentation and the messaging that is based on it, I would as a marketing representative absolutely want to have more profitability information to generate additional sales, or for churn related predictions and decisions. Should we repeatedly approach a large customer, whose profitability is negative? Does it make sense to allow an unprofitable customer to leave, or can the situation be rectified with a change in product or contract terms? What should we be recommending to our customers based on shopping basket analyses to maximise profitability?

Noteworthy in customer profitability is that it is not a static phenomenon. Customers switch services, come, and go, and all these changes will over time affect profitability. Changes can often be anticipated, and even directed towards a beneficial direction. A customer with profit potential can be elevated into the profitable camp, while the perpetually unprofitable can be let go. Ultimately, decisions should be based on fact, and not on tea leaves in the manager’s morning brew.

At its best, profitability driven customer segmentation and messaging aim to maximise customer lifetime value. The objective is challenging and not only requires a lot of co-operation between marketing and finance, but also analytics. Avarea has experience of numerous cases, both in customer, as well as profitability analytics. Our analytical minds are at your service, if you require assistance.