Smart Data Smart Decisions Smart Profits

3 40x 2 channel customers 20 3x 40x single channel

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Unformatted text preview: -channel customers 3.3 - 4.0X 2-channel customers 2.0 - 3X 4.0X Single-channel customers 1.0 - 1.3X Typical retail channels: Stores Catalogs Internet Kiosks 15 Multi-channel Mono-channel Some early players are crafting smart channel strategies based on the insights gleaned from how customers use the Internet and traditional outlets. For example, one company tracked customers’ use of channels and migration across channels by using separate order codes for catalogs and the Internet. This approach let the company discern how many customers used the catalog for browsing but purchased on the Internet; the company could tell that customers crossed channels when they used the catalog order code for Internet orders. Based on this knowledge, the company tailored the focus and functionality of each channel – matching advertising to specific audiences and offering Web-based tools to support browsing or ordering. These examples reinforce the value of customer data and the insights retailers can gain to make smarter business decisions. The task for retailers is to build the capabilities to get and use data to capture sales and profit opportunities. 8 ©McKinsey & Company 2000 MCKI29 - Ret. Smart Des.7 8/9/00 11:08 AM Page 9 Building smart customer databases To truly know their customers, retailers need to track and analyze how people shop and pay, how they behave over time, and how they react to different offers and changes in retail value propositions. With insights from these patterns, retailers can identify and set their priorities for increasing sales, profits, and wallet share. To get going, they require a robust customer database that, at a minimum, includes basic behavioral metrics, channel use preferences, promotion history, and selected demographics (see “How to Build a Smart Database”). Traditionally, retailers have drawn most of their customer data from mass market sources – basket analysis, external and customer surveys, demographic profiles. However, these sources do not enable retailers to understand individual customer behavior over time, which is the critical marker of a retailer’s ability to attract, develop, and retain its customers. Now, customer-level behavioral data comes from loyalty cards, proprietary credit cards, third-party credit card reverse appends2, phone number register-based customer tracking programs, and, more recently, clickstream data from retailers’ Web sites. To create reliable insights, these sources should capture customers generating at least 50 to 60 percent of total sales. The most successful loyalty programs, such as those of U.K. grocers, capture 80 to 90 percent of sales. The required time horizon for tracking customer behavior patterns varies by the shopping characteristics of different retail categories as well as shopping channel. The most important drivers for off-line shopping are 2 Recent privacy legislation may limit or eliminate the use of reverse appends going forward increasing the importance of altern...
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This note was uploaded on 02/08/2014 for the course RCS 391 taught by Professor Jeanielim during the Fall '14 term at University of Tennessee.

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