To stimulate growth in today's marketing environment, companies must identify and prioritize opportunities at points where proliferating segments, channels, and product categories intersect.
When it comes to customer information, these are the best and worst of times for corporations. The digital era has made available rich new sources of data about customers. Yet rapid growth in customer segments, distribution channels, store formats, and product categories means companies must combine and integrate that information in newly complicated ways.
Specifically, marketers must look at the intersection of different types of information (for instance, between customer needs, store formats, and product types) if they are to convert mere data into competitively useful insights about customers—that is, into knowledge beyond conventional industry understanding about why, when, how, where, and what customers buy. Useful insights are the product of two or more combined pieces of information. The common characteristics connecting seemingly dissimilar groupings of customers only become visible when viewed from multiple angles. By focusing on these intersection points, or "cells," marketers can better avoid averaging out consumer preferences that, if properly understood, could suggest new opportunities for growth.
Most companies, though, still regard customer insights as an isolated research capability. As a result, they aren't configured to obtain data at the points where segments, channels, and categories intersect, nor can they integrate the information to generate valuable insights. The isolation of the insights function also inhibits transforming insights into actions and leaves many companies without a common way of looking at and describing customers across functions. Instead, marketing focuses on brands; sales looks at geography, channel types, and key accounts; and the market research organization views the world in segments.
The solution isn't to redraw boxes and lines on the organizational chart but rather to enhance the connections among the various actors needed to generate and act on cell-level insights. Of course, there's a term for a system of interconnecting parts that work together: a network. What companies need today is an insights network that helps them to look at the world through a number of lenses and to develop truly proprietary knowledge about customers. The network should not only integrate data on attitudes, behavior, transactions, and so forth but also encompass relationships with expert third parties (who can help companies manage complex data sets or master innovative qualitative-research techniques) and with key suppliers or customers (who can provide, for example, transactional data contributing to regional or store-level competitive intelligence).
Consider a consumer electronics company that struggled to increase its sales in the mass-market discount stores (such as Wal-Mart Stores), which were taking share from its traditional channels. Customary market research approaches couldn't isolate the cause of the problem. By integrating point-of-sale data with an online survey on shopping behavior in stores and general customer interests, the company learned that a surprisingly large number of people shopping for TVs at Wal-Mart were primarily interested in watching sports. This insight—combined with discrete-choice research on the TV features that sports-minded TV buyers valued most (picture-in-picture capabilities, digital connections, and plenty of audiovisual ports)—highlighted an opportunity to change the mix and features of products the company sold at Wal-Mart and to focus in-store marketing on sports fans.
To capitalize on such insights, companies must embed them in the organization's key decisions by restructuring brand and sales planning, new-product development, marketing investments, and other business-planning processes. By working across geographies and functions to gather common sets of information from the field and to translate the resulting insights into frontline actions—in other words, by behaving in an integrated, networked way—brand, sales, and key-account managers can improve a whole company's ability to make decisions.
Capturing growth at intersection points
Companies can now glean increasingly impressive and potentially lucrative insights by, for example, sharpening their focus on the customer at the point of purchase. A few insights-driven companies have taken this lesson to heart and begun pursuing cell-level customer intelligence and applying it to their marketing and sales endeavors. Consider the following examples:
- One aspect of the European grocer Tesco's approach to understanding customers is focusing on opportunities at the intersection of needs-based customer segments and product category sales in the company's four main store formats (Express, Metro, Extra, and supermarkets).1 For example, by combining loyalty card data on what customers were buying at Tesco with survey research on what customers were not buying, Tesco found that, in some formats, young mothers bought fewer baby products in its stores because they trusted pharmacies more. So Tesco launched BabyClub to provide expert advice and targeted coupons. Its share of baby product sales in the United Kingdom grew from 16 percent in 2000 to 24 percent in 2003.
- Best Buy is renewing its store formats by integrating shopper research, point-of-sale data, and demographic analysis to determine which shopper segments are over- and underrepresented in certain areas and then varying its store formats accordingly. Stores located near large concentrations of affluent male professionals, for example, offer more high-end home theater equipment, specialized financing, and same-day delivery. Stores closer to soccer moms feature softer colors, personal-shopping assistants, and kid-oriented technology sections. After these stores changed to the target formats, tests showed that sales surged by 7 percent and the gross profit rate jumped by 50 basis points.
- Recently, a fixed-line telecom provider integrated a telephone survey of its customers' shopping behavior, Internet use, and telecom needs with the contents of its internal data warehouse, which links demographics to consumption profiles across local, long-distance, data, and broadband services. This analysis revealed an insufficient marketing focus on affluent households with heavy Internet use, so the company reoriented its mix of advertising vehicles (toward more Web-based advertising) and channel promotions (toward store chains visited by Web-savvy customers).
Notwithstanding these success stories, few companies have defined an approach or developed the necessary skills for synthesizing insights across brands, channels, products, and regions. One reason is that brand teams, market research groups, regional sales teams, and channel partners have different views of the world (Exhibit 1). As a result, each group looks for and generates different, often unrelated, customer data from the overwhelming volume available. One consumer products company has marketers who segment end consumers in elaborate ways but a distribution organization that develops channel strategies based simply on retailer types. These differences make it difficult to integrate channel-, segment-, and brand-level data—and virtually impossible to collaborate on understanding and targeting high-value customer cells.
Even when companies generate sets of insights that could inform the sales and marketing actions they take at the cell level, organizational disconnects often make it hard to translate those insights into coordinated activities. A beer company, for example, knows that the battle for growth against brands of wine and spirits takes place in defined locations in specific geographies. It has also determined which consumer segments to target in which type of bar and restaurant chain. But until recently, its marketers still gave the sales force and its distribution partners brand plans that described broad national marketing programs rather than helping sales and distribution teams to understand how they might use more detailed, local key-account or channel insights. As a result, the company failed to exploit its cell-level insights.
Creating an insights network
Companies can integrate data, generate insights, and convert them into cell-level activities by starting with information from diverse sources and then instituting a shared, cross-functional approach and a common set of skills within an insights network of practitioners. This network often includes customer and third-party partners who help provide and analyze data.
Managing insights data
The first step in establishing an insights network is defining what sources of data the company needs. These sources typically include a subset of "foundational" data (such as market- and channel-level sales or category data) that a company's functional units develop in common and share. Then the company should integrate its basic data with more nuanced information on customers or shoppers or with data from loyalty club cards, points of sale and scanners, quantitative surveys, qualitative interviews, and other sources of knowledge to which it has privileged, if not fully proprietary, access. Since the goal is to look at customers through a variety of lenses, the company should ask itself whether the sources selected will, collectively, tell it who its current (or potential) customers are; what they want; when, where, and why they buy; and how much they are worth. For a telecom company, basic data sources might include individual subscribers' usage profiles and demographic information, along with market research on the communications needs of different household segments. For a retailer, basic data sources might include loyalty card and point-of-sale data, which could be combined with region-specific shopper-segmentation data and with in- and out-of-store market research on the drivers of shoppers' behavior. As a company pursues new sources of growth, its frame of reference will likely expand from current to prospective customers. Its research focus must change accordingly.
Many companies find it important to add qualitative observations of customers; P&G's practice of observing them in their daily routines is one well-known example. Among retailers and apparel makers, a common tool today is the closet check: going into homes and looking in the closets and drawers to see what people wear.
For most companies, the key to extracting powerful cell-level insights from all this information is the very human task of analyzing the different data sources and then relating them, through active problem solving, to key business decisions. It's critical to involve a diverse array of people, including some with regional knowledge, others with trade or pricing skills, and still others with skills in branding or key-account management.
An example of how all this works in practice comes from the experience of a European battery supplier that tried to boost its sales at a powerful retailer. The supplier noticed that its highest-margin, "high-tech" batteries were frequently out of stock there. Believing that high-tech users were driving demand, it responded with a prominent new display rack describing the more expensive battery's benefits for digital devices. But instead of rising as expected, sales actually fell.
For information on how to understand and influence customer preferences at specific touch points, see "Better branding."
Only after the company conducted a series of studies at a local hypermarket did it understand this counterintuitive customer response. Exit interviews with people who purchased batteries clarified why they did so, and in-store observation showed how they shopped. In fact, few of these people were buying the more expensive high-tech product for digital devices; instead, they bought it in the belief that it lasted longer (a fact not emphasized in the displays) or by simple chance. The company returned to the original display in the do-it-yourself section and created a new high-tech-only display for the multimedia one. Sales in pilot stores then shot up by 20 percent because customers no longer had the impression that the main reason to buy the batteries was their performance in digital devices. This well-targeted response resulted from the company's effectiveness at integrating point-of-sale data and general category knowledge with findings from surveys and observations in the channel.
Collaborating with insights partners
In addition to involving each of the key marketing and sales functions, more insight-driven companies are enlisting a new set of partners and third-party research providers, which can boost the odds of developing cell-level insights.
Channel partners. Manufacturers, upstream suppliers, and downstream retailers should learn to collaborate on the basis of shared insights, since their data sets are complementary. Retailers often have transactional data describing what takes place in a product category at a very discrete level. At the other end of the channel, branded manufacturers have rich information, by segment and region, about consumer relationships with their brands and categories.
Projects with vendors must shift from an assembly line for processing data to a collaborationinvolving joint data collection and analysis
Sharing such insights can yield powerful results for either or both parties. One of Alcoa's cardboard suppliers, for example, shared its research findings about the way consumers replace soda in their refrigerators. The aluminum manufacturer then pitched a new refrigerator-friendly package to Coca-Cola—a proposal that contributed to a 10 percent uptick in Coke's sales during the three months after the package was introduced. Another example comes from Wal-Mart, generally considered to be the only retailer in Europe that can collect and organize clean and consistent electronic point-of-sale data. Through Wal-Mart's Retail Link tool, the company provides this information to key suppliers online, thus helping not only them but also itself because, in return, the suppliers share the results of some of their own analyses.
Vendor partners. The network must also include vendor partners that specialize in developing insights and will likely require a company to shift its business from relationship-driven, full-service vendors to firms with unique abilities to probe the intersection of different types of information. Such vendors include data-cleansing houses and predictive-modeling shops, anthropologist networks, in-context interview specialists, and firms that mine retailers' transaction records. The expertise that such vendors provide is difficult (and expensive) for marketers to build within their own companies.
The marketers' exchanges with vendors will shift from outsourcing low-value tasks and commissioning tactical research (such as concept tests) to identifying cell-level opportunities. So the process of working with vendors must also shift, from an assembly line for processing data—the marketer poses hypotheses, the vendor conducts research, and the analyst interprets the data—to a collaborative effort involving joint data collection and analysis. Collaboration yields a larger number of connections between marketers and vendor partners and a more sustained set of relationships, which together help marketing and sales organizations build the skills they need to develop cell-level insights.
Embedding insights in key decisions
To be valuable, cell-level insights must help companies to develop integrated marketing and sales activities spanning their product-development, brand, sales, category-management, and key-account teams. Making this happen requires a shift from managing insights primarily within a single function, as most companies have traditionally done, to embedding them in the planning processes and resource allocation decisions that guide all marketing activities.
Insight-driven decision processes
To embed insights in the way companies make their most important marketing and sales decisions, they must address the underlying processes that shape those decisions. Consider the following examples.
Marketing planning. Traditionally, insights about customers have informed certain elements of marketing or brand planning—for instance, setting priorities for raising (or defending) market share across a portfolio of brands, targeting high-potential customer segments or channels, and allocating advertising and promotional investments. One packaged-goods company has combined such familiar marketing-plan practices with new, cell-level insights, such as shopping habits in a key channel's core consumer segment. These insights in turn influence the company's channel-level packaging and pricing plans. Embedding insights more deeply in marketing plans calls for well-connected analysts and marketing managers. They must have incentives not only to integrate channel-based insights about shoppers with traditional insights about the way core segments see brands but also to work with brand, product and packaging, and field sales teams to use this analysis in refining plans and decisions.
Product development. Companies can use insights to identify new-product opportunities and make more intelligent decisions about whether to continue financing ideas at different stages of development. A cell phone manufacturer looking for promising offerings in several profitable markets, for example, established customer segment panels, whose members were asked to maintain diaries detailing where and how they used PDAs and wireless devices. With this information in hand, the company's brand and segment managers could ensure, at key stage-gate points in product development, that the teams of developers were truly meeting the needs of target customer segments in critical markets by proposing appropriate new-product and packaged-service ideas, such as business- or entertainment-oriented browser interface designs. These managers also helped to create the sales plans needed to focus the new offers on targeted customer cells. It's difficult to see how the usual practices, such as developing ideas for new products based on leading technology or market trends, could yield similar results.
Account planning. Companies can significantly improve their key-account plans by combining data from retailers with insights from suppliers. The resulting rich trove of information could be used to develop not only account-specific, regional, and even store-level product ranges, mixes, and pricing targets (including in-store promotional programming and priorities) but also category-management goals for large accounts.
The importance of cross-functional integration
Insights can inform key decisions only when people in a company—especially its marketing and sales professionals—work well across functions. Facilitating cross-functionality often requires clarifying who in the organization will play key insight-related roles. These responsibilities include incorporating channel-, region-, and customer-specific insights into plans for brands, products, packaging, and pricing, as well as generating key-account plans that help salespeople take advantage of insights about shoppers and of intelligence developed through collaboration with channel partners.
The key challenge typically isn't resources; the people already work somewhere in the organization. Rather, it's ensuring that they have access to common sets of data, use a common set of approaches, have the right skills, and work in a coordinated way. Here's how a tire manufacturer achieved these goals:
- The company identified people from sales, marketing, and market research who would combine their cell insights to develop an integrated view of channel opportunities. Members of the sales organization collected volume data from retailers; people in the marketing department conducted research into shopping behavior; and colleagues in the market research group surveyed shoppers in different channels and undertook a conjoint analysis of the results.
- By integrating these insights, the cross-functional group identified product lines the company could charge a premium for without encouraging consumers to switch to discount channels.
- Finally, the group worked through established brand-, sales-, and business-planning processes to develop account plans that articulated, for each customer, the insight-driven rationale of changes in pricing policy.
As this example shows, the brand, sales, and channel managers who play key insight-related roles don't have to be new hires or devote all of their time to the effort. Rather, the company reallocated them for a period from their original functions and managed them through a common approach based on the use of shared data and analytical tools.
Suppose a business that manages insights as a functional responsibility wants to switch to developing a company-wide capability that could benefit from the involvement of far-flung participants (Exhibit 2). First, there must be a top-down commitment—usually driven by the CEO, the chief marketing officer, and the head of sales—to work in accord with common practices and definitions concerning insights. The CMO and the head of sales should play a governance role by resolving conflicts about brand, channel, and regional priorities and by setting growth goals at the cell level. They must also promote the use of a common language for insights and of shared metrics for the performance of brands or categories and for channels, segments, and regions. While the idea of such metrics may seem straightforward, adopting them takes many companies at least two annual planning cycles. Finally, senior executives shouldn't overlook the role of social skills and of what Daniel Goleman calls "emotional intelligence" in making collaborative processes work.2 By hiring and developing people with these skills and qualities, companies can improve the performance of an insights network.
Today's proliferating marketing environment creates opportunities to outsmart and outgrow competitors by generating and acting on cell-level customer insights. To do so, marketing and sales organizations must first create an insights network that mobilizes partners to generate and analyze the appropriate data and then embed the relevant capabilities in the organization's key planning and decision-making processes. 
About the Authors
John Forsyth is a principal in McKinsey's Stamford office, Nicolo' Galante is a principal in the Milan office, and Todd Guild is a director in the Tokyo office.
The authors would like to thank Yoram Gutgeld and David Sackin for their contributions to this article.
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