CRM in the real world

There is no end of reading material on 'Customer Relationship Management' - white papers, research reports, newsletters, survey results and expert opinions on every aspect of CRM. And most of it can be put into one of two categories.

There is no end of reading material on ‘Customer Relationship Management’ – white papers, research reports, newsletters, survey results and expert opinions on every aspect of CRM. And most of it can be put into one of two categories.

1. CRM is technology. The aforementioned reading materials revolve around software. Although useful and informative, many are written by the software vendors themselves, and must be taken with a grain of salt. The business assumption in most of these articles, however, seems to be that once the software is in, CRM happens. I doubt if anyone but the most insular IT person still thinks that way.

2. CRM is an end in itself. These articles talk about customer relationships in lofty altruistic terms with the inference that marketing and sales are crass commercial endeavors to be shunned by true CRM practitioners. ‘We don’t do those, ugh, marketing things, we manage customer relationships.’ They tend to forget that CRM is just one ingredient in the recipe for complete business success.

Now don’t get me wrong. I am a firm believer in all of the best objectives of CRM, but we need to make it work in the very practical real world where success is measured by business results.

Why CRM?

Some material on CRM warns of high failure rates experienced by early adaptors of CRM technology. It’s enough to scare any sensible business manager away. So, of all the things that a company could do to be successful in the real world, what brings CRM to the top of the list?

The primary reason for managing customer relationships is to generate a greater exchange of value – as perceived by the customer – and as measured by business results.

It’s the ultimate win-win situation. Isn’t that nice? But let’s get real. The customer communication plan in most companies is produced by a marketing group and is based on company needs, not customer needs. Company needs like:

* Budgets/resources: How much money do you have for customer communications?

* Fiscal timing: The CFO is calling for record first quarter results to impress the market analysts.

* Seasonal programs: I bet someone out there is working on the fall/winter/spring/summer catalogue or the Christmas promotion right now. Is that CRM? I don’t think so.

* Business priorities: Are you in expansion mode or retention mode? Full speed ahead or stop the bleeding.

* Moving inventory: Get this old stuff outta here – we need room for the new stuff.

Meanwhile, your customers are saying: ‘Give me a reason to stay!!’ And if you don’t show you care, it’s getting easier every day for them to switch. ‘But wait,’ you say, ‘I’ve got a business to run. I don’t have time for relationships. I need to produce more revenue, more profits, more shareholder value.’

How can you resolve this dilemma? How can you improve your chances of achieving real improvement in business results while investing what will probably be a whack of money in CRM?

Begin with the problem, not the solution. Consider the following quote from Stamford, Conn.-based IT and business strategy research and consulting firm, the META Group: ‘In 100% of the CRM projects we’ve seen that lack CRM analytics, there was a total and complete inability to affect change in the customer relationship.’

In my experience, data mining has two principal applications and both are required to help define the problems that CRM is supposed to solve.

1. Customer knowledge. (Customer level data mining) The objective here is to discover and analyze customer behaviours, preferences and value to the company. This can range from relatively simple analysis of customer activity data found in transaction files to the more sophisticated segmentation and predictive modeling that produces estimates of future customer value and risk that should, in turn, drive CRM investment decisions.

2. Business segment measurement. (Business level data mining) To be truly meaningful in real world CRM terms this must go beyond standard balance sheet or P&L financial reporting. You need to be able to map the customer metrics through to the fiscal metrics that roll up to business performance reports. That way you can measure the contribution that CRM is making to your improved business results.

So how can data mining make a difference in your CRM expectations and results? You can begin to explore some questions in the following areas.

Behaviour patterns. Are some of your customers consistent while others are sporadic buyers? Can you predict what or when a customer might buy next? Can you tell when a customer is at risk of defection?

Purchase trends. Can you identify your most profitable customer segments and what they buy? Are they growing or declining? What does this tell you about your CRM priorities?

Product/service affinities. Are there particular combinations of products or services that appeal to certain segments of customers? Does this suggest bundling opportunities?

Channel preferences. Is there an opportunity to personalize the relationship by making it more convenient for some customers to communicate via the channel they prefer?

Customer value. How much is each one worth, now and in the future? What is ‘value’ to you, and to them?

Questions like these can certainly lead you to a more customer-focused marketing strategy. More importantly, it can help you define a CRM strategy. And make no mistake, if you don’t have a CRM strategy going in, you won’t get results coming out.

Effective data mining, applied early in the strategy formulation phase, will improve your chances of effecting real improvement in customer relationships and ultimately in business results. That’s about as close as you will get to a guarantee in the real world.

Dave Young is director of marketing consulting at Toronto-based Tener Solutions. He can be reached at 416-585-2900 or In future articles, Young will demonstrate data mining techniques that can be applied in the development of CRM strategy.