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How can business systems analyze customer's personalized needs?

By
  • Sid Adelman, Chuck Kelley, Michael Jennings, Scott Howard, Nancy Williams
Published
  • May 02 2003, 1:00am EDT
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Q:

How can business systems analyze customer's personalized needs?

A:

Sid Adelman’s Answer: Take a look at Jill Dyche’s book, The CRM Handbook and Ronald Swift’s book, Accelerating Customer Relationships.

Scott Howard’s Answer: I think that you are really asking how can a business system anticipate or predict a customer’s personalized needs. The trick here is what we used to refer to as identifying the market of one. We need to profile customers based on what we know about that customer. This information collection and profiling can lead to a very emotional discussion about privacy which we will not address in this column. Once the customer is profiled, they need to be classified or associated with other customers to whom they are statistically similar. They are then assumed to inherit the characteristics of the similar customers. If the similar customer had a particular buying behavior, then through association, this customer will also follow that behavior. This is the concept behind amazon.com’s famous buying circles. What I had just described is a very simple example of data mining, which is truly the foundation of predicting personalized needs without direct customer contact. Your challenge will be to find the analysis tool that can accurately provide these predictions. This is not trivial as inaccurate predictions have a direct negative financial impact in both lost sales and the direct costs of ineffective and inappropriate marketing. If a company is bold and presumptuous enough to tell me that they understand me and my needs, they had better get it right. If wrong, I would have lost my faith in that company to address my needs. In researching that analysis tool, my advice would be that the low cost solution is seldom the appropriate one.

Mike Jennings’ Answer: Customer’s needs can be analyzed and responded to through many methods based on their interaction with your company’s contact points (e.g., Web site, support center, sales). Analysis of customer data can reveal that the purchase cycle for a particular product is excessive, requiring tailoring to meet individual client expectations. User profiles on Web commerce sites can be established to dynamically and personally, update content to fulfill the customer’s purchasing profile. Customer relationship management (CRM) data can be analyzed to infer behavior profiles based on an individual customer interaction with the companies contact points.

Chuck Kelley’s Answer: One way is by looking at a general trend and see if it applies to the individual. For example, on Amazon.com, when you select a book to determine if you would like to purchase it, you will get a section on the page saying that others who bought this book also bought these books. Then by offering you a discount (maybe), they can get your business today instead of tomorrow (or worse someone else gets your business). Another example might be you are a hardware store. The general analysis might show that after the third tool that someone buys, the next purchase is generally a toolbox. Therefore, if someone is in the process of buying their second or third tool, you might have the cash register bring up that fact and have the sales person ask if they would like to purchase a tool box. That (along with a five percent discount) may have the customer adding to the current sale.

Of course, it all depends on the business that you are in as to how customer’s personalization would be done. But there are many ways to do.

Nancy Williams’ Answer: The analysis of customer’s personalized needs can be achieved by analyzing customer’s past behavior and using this as a predictor of future "needs." This analysis can be done by segmenting individual customers based on past sales behavior as well as profiling customers based on the sales behavior of persons with similar demographics or psychographics. This information is very useful in targeting a segment of the customer base with a higher probability of responding to a solicitation. This serves several purposes: marketing dollars are used more effectively, and increasingly customer communication will move away from a shotgun communication style and more toward communication based on the on a customer’s perceived interest or need for a product or service.

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