Smart Data Smart Decisions Smart Profits

Gain superior loyalty program returns finally many

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Unformatted text preview: op on-line retail sites in terms of sales growth. Gain superior loyalty-program returns Finally, many retailers have invested significantly in loyalty programs with benefits such as rebates for purchases, advance notice of sales, and service extras, sometimes including personal shoppers. Success for many retailers with loyalty programs can be elusive, given the high costs of providing meaningful benefits for consumers and the challenges inherent in getting customers to spend more, not just collect benefits. Still, leading players 14 ©McKinsey & Company 2000 MCKI29 - Ret. Smart Des.7 8/9/00 11:08 AM Page 15 Exhibit 5 Segment Tailoring Improves Loyalty Program Performance Distinct differences in top customer shopping patterns at mass merchandiser Sales Percent; dollars Customer segment A B 65 59 Annual number of shopping trips 35 41 1,400 800 15 73 2 D 20 400 80 7 1,500 48 Maintain/ reinforce current behaviors Impact • Redesigned historical mass program to address differences in segment behaviors and needs • Improved top customer sales by 20% to 25% Increase frequency 43 27 C 4 Behavioral objectives Capture greater level of spend on current trips Retain/ encourage greater grossshopping Product Categories 1-3 Product Categories 4-6 are crafting successful loyalty programs with multiple goals, including gathering data, sharpening in-store interactions, creating an ongoing dialogue, and making better segmentation decisions. Consider how one U.S. mass merchant heightened the impact of its loyalty program for top customers. Historically, the program had recognized higher spenders, but had achieved little impact on their behavior – neither increasing their spending nor decreasing attrition rates. The retailer wanted better results, so it looked closely at the behavior patterns and needs of top customers. These insights led to a shift from "one size fits all" benefits and communications to an approach tailored to the needs and behaviors of different top customer segments. The response was swift, with the new approach achieving a 20 to 25 percent increase in top-customer spending across segments (Exhibit 5). Smart data, smart decisions, smart profits 15 MCKI29 - Ret. Smart Des.7 8/9/00 11:08 AM Page 16 Making Smarter Business Decisions Customer information also can help retailers to make smarter decisions in areas beyond customer relationships. Retailers can use customer insights to influence how to improve category productivity, enhance marketing spend impact, and deepen local-market penetration. Improve category productivity Every week, retail category teams must make hundreds of decisions: which products to stock, what prices to charge, which promotions to carry, and how much space to give different categories and products. By using customer-level data, these teams have a much richer base for making choices on how to manage categories and overall margin investment both within and across categories. In one example, a European retailer introduced customer segment-level spending, penetration, and promotional behavior into its cate...
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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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