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(originally published by Booz & Company)


The Promise of “Self-segmentation”

Communities provide other advantages over the traditional buckets. Interactions within communities represent an ideal listening post, enabling marketers to glean direct insights without the filter of market research. Next, companies can participate in brand and other conversations rather than competing with the estimated 3,000 to 5,000 messages that carpet-bomb consumers daily. As long as community rules are observed, companies can interact without “do-not-call” or “opt-out” constraints.

Finally, engaged participants can provide product development guidance and identify shortcomings in service or other areas to help a company improve its brand. Dell’s community of customers, for example, not only makes product suggestions and signals developing problems, but also helps fellow customers get more from their PCs.

Thus, self-segmentation provides a foundation for leveraging customer experience and input, as identified in C.K. Prahalad and Venkat Ramaswamy’s work on value co-creation. Google is one of the best examples of the power of self-segmentation. The ubiquitous search firm doesn’t identify consumer segments and target ads to them in the classic way. Rather, it displays ads based on the content chosen by the consumer.

Three Approaches to Self-Segmentation
Companies can utilize three approaches to leverage self-segmented communities — engaging with social networks, tracking online communication behavior, and mass customization.

Social networks: Social networking is having the same revolutionary impact on companies and customer relationships that CRM had on mass marketing. But whereas CRM involved a top-down approach — mapping markets, targeting groups, and positioning messages — involvement with social networks requires a bottom-up, collaborative approach based on a company’s brands, mission, or social goals.

Global social networks such as Facebook and MySpace, visited by 67 percent of the world’s online population, according to Nielsen Online, represent the biggest opportunity to link with self-selected segments. Groups within these networks, which usually incorporate blogs, live chats, message boards, videos, and sometimes rating and ranking systems, allow members to congregate around issues of mutual interest. And the new kid on the global social networking block, Twitter, represents a fast-emerging opportunity to learn from — and communicate with — those interested in companies, brands, or social/business issues.

Another type of self-segmentation is localized business, professional, or other networks like Biznik (“where collaboration beats competition”), Ecademy, and Ryze. These can connect supply chain partners, customers, associates, and others that share an interest or stake in a brand.

Finally, there are corporate, or branded, communities. Worried about the free-for-all nature of some social networks, companies have established “branded communities.” (See “The Promise of Private-label Media”, by Matthew Egol, Leslie H. Moeller, and Christopher Vollmer, s+b, Summer 2009.) The best of these branded communities combine customer input, product and how-to information, promotional premiums, and even social events to facilitate customer and brand relationships; the worst of them tightly control discussions and offer little interactivity. Companies using branded communities to establish bonds with prospects and customers while maintaining some brand control include Walmart, BMW, Procter & Gamble, and Sears. Software offerings like Ning enable even small companies to establish their own branded communities. However, care must be taken to ensure that these communities are used as a listening channel rather than as merely another marketing channel. Consumers are not going to listen to a company’s pitches unless they are first convinced that the company is listening to their concerns.

Communication behavior: Major retailers and larger companies may attempt to understand segments, and even individuals, through website personalization and collaborative filtering. These capabilities allow Netflix, Apple’s Genius, Amazon, and others to match information and offerings based on a person’s interests, clickstreams, or previous visits and purchases.

However, such personalization and collaborative filtering are expensive and complex, and have their weaknesses and detractors. A simpler option is to have a variety of optional content — newsletters, RSS feeds, white papers, blogs, and so forth — that visitors can access. These visitors can then be segmented according to their informational interests.

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