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Issue Date: April 2004

True analytical customer intelligence pays off

April 2004

There is a vast difference between basic customer relationship management (CRM) and analytical CRM - and the former has simply not lived up to its promise. In fact, it is widely accepted that at least 50% of all CRM projects have failed.
"True analytical customer intelligence, on the other hand, does lead to increased revenue," says Retha Keyser, product manager at SAS Institute SA.
According to Alan Bonde, a CRM analytics consultant, CRM solutions are very good at automating processes, but they are less successful at optimising interactions.
"CRM is great for managing account information, helping people choose the channels for customer interaction, and tracking transactions within those channels," says Bonde. He says that CRM doesn't tell you what to do at a point in time. CRM doesn't really address the issue to maximise each and every interaction with the customer, whether it's during a campaign or during a customer-service call. That's the gap that has to be bridged." (Source: Finally, CRM Begins to Pay Off by Joe McKendrick).
Analytical CRM does just that, according to SAS.
Keyser gives an example of how this was achieved at South Africa's largest insurer, Old Mutual. The company implemented an analytical segmentation solution from SAS Institute which assisted in defining the organisation's customer segments, as well as analytically defining strategies to develop each segment. The solution was designed to dynamically adapt to meet the changing needs of each customer division.
"By using analytical CRM, Old Mutual has successfully aligned its products and marketing campaigns to specific customers, allowing for strategic and accurate cross- and up-selling of products," Keyser says.
In the US, Eddie Bauer, a major online and catalogue retailer, was able to better focus its catalogue and email promotions, and therefore increased customer spending by between 30 and 50% annually. It did this by employing predictive modelling with SAS data mining software against its 28-million-customer database.
"Old Mutual and Eddie Bauer are good examples of how major companies are showing return on investment by going the analytical CRM route," says Keyser.
Eddie Bauer was trying to build one-to-one relationships with more than 15-million retail, catalogue and Internet customers. "The SAS solution gives it the means to know its customers and the ability to view their shopping experience from the client perspective," says Keyser.
"Using analytical CRM, the company now has a firm grip on data and effective ways of analysing customer behaviour, together with the power to make projections based on that customer information."
Now, Eddie Bauer uses predictive modelling to decide who receives specialised mailings and catalogues. For example, each year Eddie Bauer features an outerwear special, and - thanks to data mining - it can determine which customers are most likely to buy.
Data mining also allows Eddie Bauer to determine seasonal buying habits. Then the company can identify people with similar characteristics who don't normally buy outerwear and target them with mailings to bring them into the store or encourage them to buy from the catalogue.

For more details visit SAS Institute at

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