| KDnuggets : News : 2005 : n22 : item29 | |
BriefsBest Practices for Mining Retail Transactionswww.b-eye-network.com, by Dan Ross, November 8, 2005 There are many benefits derived from analyzing transaction information in a retail data warehouse, particularly when taking “customer-centric” or "visit centric" retailing approaches. In last month’s article, I talked about how to navigate the many obstacles that arise when attempting to analyze transactional level data. In this third and final article in the series, I will discuss the key business insight that retailers should obtain from their transaction data asset. Most retailers are driven by a common fear of being pushed out of the market by larger competitors. They subsequently recognize that they are likely to meet this fate unless they can connect with the needs and behaviors of their customers. Clearly, some of the largest industry players have achieved their status through exactly these behaviors. This means understanding the needs of their customers and doing whatever they could to meet those needs. While customer surveys and focus groups can be helpful, customers truly vote with both their feet and their dollars. The transaction detail in your data warehouse, often called the “T-log,” is a (nearly) perfect record of the decisions your customers make, and how those decisions affect your business. Coupled with other data in your data warehouse, you have much of the information you need to understand the behavior of your customers. You can view the analysis of this behavior from two perspectives: the “customer-centric” and the “visit-centric” perspective. Here is the rest of the story. |
| KDnuggets : News : 2005 : n22 : item29 | |
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