Vijay Vishwanath

Darrell Rigby

<article-ideainbrief class="article-ideainbrief">
 <h4 class="ideainbrief-title">The Idea in Brief</h4>
 <div class="ideainbrief-contents">
 For decades, Wal-Mart, and other sultans of standardization have dominated the consumer-market landscape with their winning store formats and product mixes. But their “one size fits all” strategy no longer fits: Diverse consumer communities—differentiated by ethnicity, wealth, lifestyle, and values—now demand customized products. And people increasingly rebel against cookie-cutter stores that threaten their neighborhoods’ unique character. Yet if retail giants respond with offerings customized to each location, they risk losing the economies of scale that fuel their profits.
 The answer? Authors Darrell K. Rigby and Vijay Vishwanath recommend localizing by clusters—tailoring elements such as store formats, merchandise assortments, pricing, and staffing to groups of consumers that exhibit similar preferences. For example, casual-wear retailer American Eagle Outfitters—boasting 740 U.S. stores—found that western Florida customers’ purchasing patterns closely matched those of certain communities in Texas and California. By customizing products and promotions to these consumer groups across locations, the company boosts sales while retaining cost efficiencies.
 Localizing by clusters requires extensive investment in technology for collecting and analyzing data; centralized, data-driven decision making; and supply chain partners who can manufacture and distribute customized products efficiently. But the effort pays big dividends. Consider Best Buy: in 2005, its 85 “localized stores” posted revenue gains two times the company’s average.
 The Idea in Practice
 Rigby and Vishwanath suggest these steps for localizing by clusters:
 <h2>Collect Data</h2>
 Gather as much data as possible on key elements of your business for each store—using sources such as local managers’ knowledge, census and other demographic research, data from store scanners and loyalty cards, consumer surveys and unsolicited comments, Internet sales data, and intelligence on competitors. Consider elements related to:
 <ul>
 <li>What you sell—such as product mix, pricing, promotions, store layout, and service levels.</li>
 </ul>
 <ul>
 <li>Where you sell—including consumer demographics, climate, competitor market share, and local attractions and cultural events.</li>
 </ul>
 <ul>
 <li>When you sell—such as monthly, seasonal, and yearly cycles.</li>
 </ul>
 <h2>Develop Clusters</h2>
 Use the data you’ve gathered to develop consumer clusters—groups who share distinct preferences related to what, where, and when you sell. To keep things simple, use the minimum number of clusters that enable you to localize the most promising elements of your offering. Example:&nbsp; 
 Best Buy identified four consumer clusters: 1) busy suburban moms who are the chief buyers for their households and want quick, personalized help navigating the world of technology, 2) young tech junkies who want cutting-edge entertainment and gaming gear, 3) affluent, time-pressed professionals seeking high-end equipment and personalized service, 4) budget-minded family men desiring technology to enhance home life. 
 <h2>Identify Localization Opportunities</h2>
 Localize key elements of your business in ways that generate the highest possible sales and lowest costs. Example:&nbsp; 
 After analyzing local demographics and demand patterns, Best Buy created store types that cater to the consumer clusters it identified. For instance, in some of Best Buy’s locations, busy suburban moms were an untapped segment that offered the best opportunity for expansion. To attract them, Best Buy designed stores featuring uncluttered layouts with wide aisles and warm lighting, technology-related toys for kids, personal shopping assistants, and more floor space allocated to household appliances. 
 <h2>Preserve Economies of Scale</h2>
 No matter how sophisticated your clustering, you’ll still lose some economies of scale—in purchasing, marketing, and other activities. To minimize the loss, start with less costly strategies, such as localizing markdowns or a product’s packaging rather than incur the expense of customizing the product itself. Example:&nbsp; 
 Wal-Mart found that while “ant and roach killer” sells well in southern states, northern consumers are turned off by the word “roach.” Simply by labeling the pesticide as “ant killer” in northern states, the company saw sales increase dramatically.
 </div>
</article-ideainbrief>We’re in the early stages of a quiet revolution in consumer markets. For decades, the chains that have dominated the landscape—titans like Wal-Mart, Best Buy, and McDonald’s—have pursued single-minded strategies of standardization. They’ve fine-tuned their store formats, merchandise mixes, and operating and marketing processes, and they’ve rolled out their winning formulas internationally. They’ve demanded equally rigorous consistency from suppliers, pushing the standardization ethic deep into consumer product companies and across the entire consumer supply chain.

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Reprint: R0604E
Standardization has been a powerful strategy in consumer markets, but it&#8217;s reached the point of diminishing returns. And diversity is not the only chink in standardization&#8217;s armor: Attempts to build stores in the remaining attractive locations often meet fierce resistance from community activists. From California to Florida to New Jersey, neighborhoods are passing ordinances that dictate the sizes and even architectural styles of new shops. Building more of the same&#8212;long the cornerstone of retailer growth&#8212;seems to be tapped out as a strategy.
Of course, a company can&#8217;t customize every element of its business in every location. Strategists have begun to use clustering techniques to simplify and smooth out decision making and to focus their efforts on the relatively small number of variables that usually drive the bulk of consumer purchases.
The customization-by-clusters approach, which began as a strategy for grocery stores in 1995, has since proven effective in drugstores, department stores, mass merchants, big-box retailers, restaurants, apparel companies, and a variety of consumer goods manufacturers. Clustering sorts things into groups, so that the associations are strong between members of the same cluster and weak between members of different clusters.
In fact, by centralizing data-intensive and scale-sensitive functions (such as store design, merchandise assortment, buying, and supply chain management), localization liberates store personnel to do what they do best: Test innovative solutions to local challenges and forge strong bonds with communities.
Ultimately, all companies serving consumers will face the challenge of local customization. We are advancing to a world where the strategies of the most successful businesses will be as diverse as the communities they serve.

Localization:&nbsp;The Revolution in Consumer Markets

Reprint: R0604E Standardization has been a powerful strategy in consumer markets, but it’s reached the point of diminishing returns. And diversity is not the only chink in standardization’s armor: Attempts to build stores in the remaining attractive locations often meet fierce resistance from community activists. From California to Florida to New Jersey, neighborhoods are passing ordinances that dictate the sizes and even architectural styles of new shops. Building more of the same—long the cornerstone of retailer growth—seems to be tapped out as a strategy. Of course, a company can’t customize every element of its business in every location. Strategists have begun to use clustering techniques to simplify and smooth out decision making and to focus their efforts on the relatively small number of variables that usually drive the bulk of consumer purchases. The customization-by-clusters approach, which began as a strategy for grocery stores in 1995, has since proven effective in drugstores, department stores, mass merchants, big-box retailers, restaurants, apparel companies, and a variety of consumer goods manufacturers. Clustering sorts things into groups, so that the associations are strong between members of the same cluster and weak between members of different clusters. In fact, by centralizing data-intensive and scale-sensitive functions (such as store design, merchandise assortment, buying, and supply chain management), localization liberates store personnel to do what they do best: Test innovative solutions to local challenges and forge strong bonds with communities. Ultimately, all companies serving consumers will face the challenge of local customization. We are advancing to a world where the strategies of the most successful businesses will be as diverse as the communities they serve.

Localization: The Revolution in Consumer Markets

Summary.

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