Profiting From Customer Intelligence in a Recession

I attended the IIR Customer Segmentation & Intelligence conference in Monaco last week. It rained non-stop every day I was there, so I had plenty of time to talk to the 100 or so delegates from various companies who gathered to hear what's new in customer intelligence.

As you can imagine, the recession was foremost on everyone's mind. But in spite of the general foreboding about what was to come, the delegates heard over twenty industry speakers talk about how they were creating value from using customer intelligence.

Although there was a lot of discussion about analytical tools and techniques, a number of common themes came to the surface over the three days. They were a mixture of what's new in customer intelligence and how customer intelligence can be used to combat the recession.

See what you think.

1. All customers are not created equal - To misquote George Orwell's 'Animal Farm', "All customers are equal, but some customers are more equal than others". In other words, organisations should concentrate on those customers who are most important to them. They might be the most loyal customers, they might be the most valuable customers, or they might have the most growth potential. Organisations need to know which customers are important to them and to organise their customer intelligence around them.
2. Focus on the bigger value equation - Too much customer intelligence is for the purpose of finding out how customers can be exploited by organisations. Which customers might be the most valuable in the future, which might buy Product A or which are likely to defect to the competition. This is no longer enough. Customer intelligence needs to expand to analyse the value the organisation delivers to customers too. Understanding customer value and customer perceived value, and their trade-offs, is the bigger customer value equation.
3. Co-create strategy with customers - One of the mobile telecoms speakers from Denmark described how they co-created segmentation in discussion with new customers. They only have a six month contract period, which isn't long enough to gather sufficient transational data for traditional analytics. This is one of the best examples I have seen of the new trend to co-creating strategy together with customers. It is one of the best ways to avoid developing irrelevant customer strategies that bear no relation to the market.
4. Keep things as simple as possible, but no simpler - It is all too easy to spend ever more resources extracting ever reducing returns from ever more complex analytics. Academics seem to thrive on this. So do some consultants. But back in the real world, it is much more important to use just enough analytics to develop hypotheses that are testable in the market and then to improve them through a process of step-wise improvement. Analytics should be only as complex it it needs to be to do the job, but no more complex.
5. Learn what works by trying things out - You never know what will really work until you try it out in the market. All analytics concerns itself with developing models; which by their nature are simplifications of the real world, sometimes almost meaningless simplifications. As I wrote in a recent post about New Research on How Loyalty Drives Future Sales, sometimes the models explain so little of the variation in the data that they are hardly better than educated guesses. The only way to see what works is to test it.
6. Sense and respond to changing conditions - Market conditions change rapidly in many industries. And as we have already seen in the recessionary global economy, the changes are coming faster and faster. The only way to be prepared is to build the organisation's sense and respond capabilities so that they can spot patterns in emerging market trends and respond to them in double-quick time. As research by Lehmann and others showed, this approach is by far the most successful at spotting winning new opportunities in the market.
7. Focus on the long-term - It is tempting in these difficult time to focus on the short-term, for example, on tactical marketing activities to move product off the shelves. The short-term is important, particularly at the moment, but not at the expense of the long-term. So while you are busy focussing on tactical marketing, it is well to remember that you need to do it in a way that grows customer profitability over the long-term too. If you don't, you will fall into the Red Queen trap that the US car industry finds itself in today; requiring more and more expensive promotions, to sell fewer and fewer cars, at lower and lower margins. It doesn't sound like a profitable business model to me!

What do you think? Are you using customer intelligence to create value for shareholders and customers alike? Or are you stuck in an analytical rut?

Post a comment or email me at graham(dot)hill(at)web(dot)de to get the conversation going.

Graham Hill
Independent CRM Consultant
Interim CRM Manager

Further Reading:

Graham Hill, New Research on How Loyalty Drives Future Sales

Lehmann et al, The Idea Itself and the Circumstances of its Emergence as Predictors of New Product Success

Stuart Kaffman, Escaping the Red Queen Effect