Identifying Pockets of Profitability

With a Value-Based Approach to Customers

Perhaps the most important task for any service provider is making decisions based on hard data and facts, rather than emotion, guesswork or assumption. 

It’s a tough world for telecoms operators and an increasingly crowded industry - it can be easy to react hastily to competitors' advances and implement actions that would, on paper, drive revenue. The reality is much harder to foresee. Competition from new market entrants – many of whom are focused on growth and new customer acquisition, as opposed to profitability, is forcing mobile and fixed line operators to drop prices and offer cash incentives to tempt new customers. If a customer takes up these offers, then switches as soon as their contract ends, the operator often loses money – potentially hundreds of pounds in the case of technical installations. If replicated across multiple customers, this can carve a substantial dent in profits. 

This is reducing margins, which are being further eroded by the rising cost of acquisition and alongside Ofcom making it easier to switch, many operators are having to make bets on which customers will cost them money, versus those that will make them money. So, what makes a customer valuable - or not valuable?

Ultimately, the only way to identify which factors make a customer unprofitable is by analysing data to gain a single view of the customer. However, most operators struggle here due to organisational and data siloes.  As a result, many cannot identify which customers are or aren’t profitable, let alone understand why, leading to significant revenue leakage. Perhaps the most important task for any service provider is making decisions based on hard data and facts, rather than emotion. It's also crucial for telecoms providers are realising they must go beyond the averages and really get a granular view of their customers and their intentions. And thanks to a value based management approach, extracting the necessary value from their customer data is no longer a complex and costly thing to do.