Making the economics of customer recruitment and retention add upby
It's easy to spend money on customer acquisition, it's harder to spend it on up-sell and cross-sell, but it's hardest of all to spend it on retention. Professor Merlin Stone believes the solution to this problem - and the law of diminishing customer returns - could lie in cohort analysis and management...
By Professor Merlin Stone
In nearly a quarter a century of work in CRM, the point in any project (or even just in a conversation) that I relish most is when a client or a consultant asks me: “Well, we’ve just completed the first or main stage of our client’s CRM programme, and now we’re wondering what customer base strategy to follow.”
I’m tempted to ask: “Didn’t you decide that before you embarked on your programme?”, but of course that is an unfair and wrong question. It’s a bit like asking a military commander: "Why do you want new weapons?" He could and should answer “to fight our next war”, even if he isn’t quite sure when and where it will be. He knows (or should know) the kind of war he will be fighting - but he might hope it will never come.
The same applies to any new business capability, like a CRM system or a programme. One should have a good idea of how one will use it, but one is not obliged to prepare all one’s plans beforehand. After all, the market may change quite a lot between the time you decide to develop the new capability, and the time it’s ready.
However, despite that, there are some big trends that any sensible marketer must prepare for. Some relate to customer behaviour (eg an internet channel to make purchases; changing channel preferences; and changing tastes), and some relate to competition (eg new entrants and moves from existing competitors). My favourite topic is what happens to the customer base as it grows.
Recently, I have been working at the rough end of the customer base, examining the extent to which companies understand fully the economics of customer recruitment and retention, especially as it applies to new products and services.
I do not mean the old chestnut “customer retention is more cost-effective than customer acquisition” - although it is part of the story, and a story that shows how rotten that chestnut is. As most of us know by now, poor acquisition strategies lead to retention problems, so it is worth spending good money on acquiring good quality customers.
Nor do I mean the Pareto 80:20 rule, though that imbalanced customer profitability or value is a nearly inevitable result of what I’m examining.
No, the bit of the economics that interests me is the law of diminishing customer returns. This states that the larger your customer base – for a given proposition - the lower the average value of additional customers. Of course, it’s not really a law, but it reflects the reality of most companies. If you have a good proposition, and you market it well, typically your earlier customers are the ones who find your product most valuable, and may even be prepared to pay more for it.
The law of diminishing customer returns
If you picture this in terms of the classic product lifecycle, the customers whom you attract in the early stages often form the bulk of your valuable users later on. Later additional customers are harder to attract. If you went for a skimming model of market development rather than one of market penetration with low prices designed to knock your competitors out, they may not have been able to afford your early pricing.
The end result is that when companies try to grow by both acquiring new customers and developing existing ones, they can often hit a brick wall when it comes to acquisition. As their market matures, their average new customer is more price sensitive, less valuable, less loyal and often less creditworthy than the average existing customer. It’s a big contrast with new products and new markets, where the plum customers are often not the innovators who first bought, but those who buy - often in large amounts - once a concept is fully proven.
However, here’s the problem: it’s easy to spend money on customer acquisition (at least you know how many contacts you make!); it’s harder to spend it on up-sell and cross-sell, because to do this properly you need to understand your existing customers’ needs, and many companies haven’t refreshed their data on a customer’s needs since they acquired the customer. But it’s hardest of all to spend it on retention - many companies don’t know why leavers leave, and most companies don’t know what to do to stop them leaving.
Still, the evidence I have from clients is that it is definitely worth confronting the law of diminishing customer returns. You start by due diligence – ensuring that you gather and analyse data on your recent customers separately, to see what happens to them in their first couple of years, compared with the rest of your customers. Did they stay or go? Did they buy much? Did they pay on time? Did they threaten to leave in order to obtain discounts? Were they particularly expensive to service? Did they recommend other customers who shared their possibly problematic characteristics? When you profiled them against external data sources, how did they look compared with the rest of your customers?
However, you must also be honest about whether your proposition really suited them. Did you attract them by push marketing, with a proposition that was more suited to more valuable customers? Did you service them too expensively? Did you sell to them through the wrong channel? Did you assume that they would be just like the rest of your customers? Did you assume that you could sell them the same additional products as the rest of your customers?
Of course, what I’m advocating is not much more than a more consistent approach to cohort analysis and management than most companies have - but strongly focused on comparing recent with earlier cohorts. This includes defining cohorts correctly and understanding their typical lifecycle, keyed back to their original acquisition date. So some data cleaning and creation of meta-data in normally required.
Such a comparison must take into account the customer’s typical time over which they buy your product category (it’s rarely worth doing detailed cohort analysis like this unless they stay in your product category for a few years), as well as the extent to which competitors have been trying to steal your best customers (and of course to palm off their worst customers on you). Also, the length of your own product lifecycle has an effect – specifically the period between major innovations – because this may dictate the need to re-recruit your own best customers.
In summary, the cohort approach can be a great way to integrate the database marketing approach with more classic product management and market development approaches – it is just a pity that so few companies do it properly.
Professor Merlin Stone is one of the UK’s top consultants, lecturers and trainers in changing organisational capability to meet the needs of customers and stakeholders. He is a director of Nowell Stone Ltd, and also a director of The Database Group.
Read more features, practical case studies and white papers about customer strategies.