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The State Of eCRM, Part I: Page 2

By Arthur O'Connor     Feedback
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tage in attracting and retaining customers will be to know them individually and better than anyone else does, and to be able to offer them what they want, when they want it. This means providing them financial, emotional and other behavioral incentives to stay, and offering personalized, valued services and add-ons.

While most organizations have the ability to collect information, they don't have a coherent and effective strategy to analyze and process this tremendous amount of data into actionable information.

The current wisdom in both the on-line and off-line worlds is that, with storage memory costs continually falling, if you don't know what information to keep, keep it all. Such economics have forced businesses into a data-rich, information-poor scenario. Corporations that have undertaken data warehousing projects have learned the hard way just how complicated and difficult it can be to decide what information to look at, how to analyze it, and what to do with the results.

Despite accumulating huge amounts of data, most businesses have quickly come to realize (or at least strongly suspect) that all customer data aren't created equal. While the science of data analysis is not new, the art of discovering what customer information has predictive value is. Most techniques employed today are still based on traditional, sales-transaction-oriented metrics, such as RFM analysis (recency, frequency and money) analysis, which tracks customers by how much, recently and frequently they purchased your products, techniques which have been around for decades.

For better and for worse, the Internet has its own set of metrics. The good news is that every move a site visitor or on-line customer makes can be automatically captured in a web server log file. Because this information is already electronic, it is relatively cheap and easy to analyze and manipulate.

The bad news is that many companies get carried away with the beauty of the reporting. Some companies spend tens of thousands of dollars on detailed reports of on-line visitor behavior with absolutely no clue how to recover this cost in the form of smarter marketing, more targeted sales, or more informed product development. Many businesses are waking up to the fact that just because it is cheaper to track every move a visitor makes on your site doesn't necessarily mean it's worth doing. While some click stream trends are predictive (for example, increased frequency of a unique visitor to a site indicates likelihood to make an on-line purchase, and collaborative filtering can be an effective sales suggestion engine), on-line behavior modeling is far from mature.

Is there a common theme in these eCRM industry trends and predictions? Well, it could go something like this: despite its youth, eCRM has done a lot of growing up lately. Despite snazzy lingo, fiendishly complex technology, and the continued novelty of the Internet, in many ways, it's back to the future: managing by the numbers.

Compared to the gut-wrenching hoopla investors, technologists, sales people and consultants have suffered through, maybe that's not such a bad idea.

Tune in two weeks from now for the next three trends in eCRM: multi-channel integration, impact on the supply chain, and implementation.

Arthur O'Connor is a senior manager in the financial services practice of KPMG Consulting specializing in customer-facing strategy as well as related architectural and organizational issues. An accomplished author, speaker and consultant, Arthur is one the country's leading experts in customer relationship management (CRM) and eCRM.

This article was originally published on February 28, 2001
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