Selling into Micromarkets

by Manish Goyal, Maryanne Q. Hancock, and Homayoun Hatami

FOR YEARS, SALES REPS at a leading chemicals and services company had successfully worked their territories, but in recent months sales volume had plateaued, because of encroaching competitors and shifting demand. Using its emerging analytics capability, the global firm took a more granular look at its business. It diced its seven U.S. regions into 70 “micromarkets” and zeroed in on those with the greatest potential. It then pulled reps away from overserved territories, created sales “plays” for the newly identified hot spots, and redeployed the sales force. Within a year the sales growth rate doubled—without an increase in marketing or sales costs.

The key to the firm’s remarkable turnaround was its new ability to combine, sift, and sort vast troves of data to develop a highly efficient sales strategy. While B2C companies have become adept at mining the petabytes of transactional and other purchasing data that consumers generate as they interact online, B2B sales organizations have only recently begun to use big data to both inform overall strategy and tailor sales pitches for specific customers in real time. Yet the payoff can be huge: As a sales executive at the chemicals company told us, “There’s no need to rely on intuition and guesswork anymore.”

To understand how sales organizations are beginning to use big data, we interviewed 120 sales executives at a range of companies around the world that have significantly outperformed their peers in revenue and profitability. These in-depth conversations suggest that micromarket strategy is perhaps the most potent new application of big-data analytics in B2B sales. While micromarkets are most often understood as physical regions, they needn’t always be; as we’ll describe even an air-cargo route can be a micromarket. Discovering and exploiting new-growth hot spots involves three steps: Defining your micromarkets and determining their growth potential; using these findings to distribute resources and guide the sales force; and incorporating the big-data mind-set into operations and organizational culture.

Let’s look at each in turn.

Find New Pockets of Growth

Many companies believe that they have a good understanding of the growth prospects for their sales regions or territories, but until sales leaders dice that geography into dozens or hundreds of micromarkets, they will be unable to see which counties, zip codes, or other circumscribed areas are underexploited and which are unlikely to grow. What’s more, they will not have a clear idea of whether they’re deploying their sales force to the greatest effect.

The first step in pursuing a micromarket strategy is to create an “opportunity map” of potentially lucrative hot spots. (See the sidebar “Five Steps to Finding Pockets of Growth” for a step-by-step discussion.) The map taps internal and external data sets from a variety of sources and uses sophisticated analytics to build a picture of the future opportunity, not the historical reality—a key to positioning the sales force for success.

To paint this high-resolution picture, a company starts by determining the ideal size and positions of its micromarkets, given the firm’s goals and resources. Next, managers examine what drives customers’ purchasing in each market, determine the firm’s current market share in each, and look for causes of the variance among markets. On the basis of that analysis, the company identifies which markets represent the greatest growth opportunities.

Given the complexity of the data gathering and analysis that these tasks entail, it is far more efficient to bring sales and marketing together to create a micromarket map than to have dispersed groups across functions pursuing pieces and then trying to cobble them together into a coherent picture. The goal is to define the problem, the methods for solving it, and, crucially, how to translate the resulting insights into tools the sales team can use.

Make It Easy for the Sales Team

For a micromarket strategy to work, management must have the courage and imagination to act on the insights revealed by the analysis. Most sales leaders deploy resources on the basis of the current or historical performance of a given sales region. We believe that while going after future opportunities at the micromarket level can seem risky, basing strategy on old views of markets and their past performance is riskier still.

Five Steps to Finding Pockets of Growth

BUILDCO, A BUILDING PRODUCTS COMPANY, identified lucrative hot spots in its Texas market through a five-step process. (This fictionalized example draws on the experience of a large U.S.-based B2B company we worked with.)

An opportunity map is the foundation of micromarket strategy. Here’s a closer look at each step in the process.

1. Define Micromarket Size

Start by determining the optimal size for your micromarkets. Should they be delineated by county, zip code, or something else? To answer this question, gauge your reps’ territory radius—the average distance they travel from a central point in the field. Choosing a size smaller than the territory radius would underutilize the sales force. Next, identify the points at which market dynamics shift—for example, at the limits of a competitor’s region or the boundary where customer density changes. Finally, determine whether the sales force will be able to execute effectively. A county-level micromarket may seem ideal from a strategic standpoint, but the sales force may lack the resources or capability to cover a region of that size.

Using factors such as reps’ territory radius as a guide, BuildCo segmented its 10 Texas sales regions into 254 counties, each one a micromarket.

2. Determine Growth Potential

To gauge each micromarket’s growth potential, determine what drives your customers’ (and potential customers’) purchases. Build a list of 15 to 20 drivers using industry knowledge, interviews with customers and reps, and informed hypotheses. Drivers might include cost of inputs, cost of capital, local demographics, and so on. Determine to what degree each driver influences customer purchases—for instance, derive simple correlations of growth using historical data from the previous two or three years. Understanding which drivers have the greatest influence on customer demand helps you determine in which micromarkets future growth is most likely. Also, information about demand at the individual customer level, when aggregated, can help further define high-growth geographic areas.

By examining the drivers of customer purchasing in each micromarket, such as terrain and age of housing stock, the firm gauged which markets were most likely to grow.

3. Gauge Market Share

Using sales data, determine market share for each micromarket. The key data are revenues and margins across lines of business. Often this step is a sticking point for companies because they don’t have ready access to data at this level.

Next, calculate sales trends in each micromarket for the previous two or three quarters—or two or three years for seasonal businesses—and compare them with data from your opportunity map. This will show how your market share is trending. Market share often varies fivefold or more among micromarkets; share-of-growth may vary by twice that.

BuildCo determined that market share was far from uniform across micromarkets, varying as much as fivefold.

4. Identify the Causes of Differences in Market Share

Next, determine what accounts for the variations in your share across micromarkets. Collect internal and external data on the marketing and sales activities that could impact market share. These commonly include data on reps’ coverage of each market and their quotas and performance within each; related data for your partners in the market; your marketing spend; and pricing by channel and by product. The key is to understand how both your sales strategy and competitive factors affect market share in each micromarket.

Then determine whether variations in these levers account for variation in market share. For example, in a micromarket where you have a low market share, is inadequate rep coverage to blame, or are shifting demographics causing the poor performance?

Sales leaders identified the main causes of low market share in high-growth-potential micromarkets. Low rep coverage and low marketing spend were the easiest and most effective to address.

5. Prioritize Growth Pockets

Understanding root causes of market share variance allows you to prioritize your micromarkets and determine which growth pockets to focus on. For example, companies might want to direct resources to areas having moreeasily addressed causes of low market share, such as poor sales rep coverage, rather than areas where the cause is, say, uncompetitive pricing if their cost structure would make a price war hard to win.

Prioritizing micromarkets is an iterative exercise. Senior management develops top-down guidelines for the approach to each peer group of micromarkets. To ensure buy-in from the field, it’s important that sales managers have the flexibility to maneuver at a local level in, say, deciding how many reps and which ones will move from a low-priority area to a hot spot.

On the basis of the analysis, BuildCo moved more reps and marketing dollars to the top 20% of the high-growth/low-market-share micromarkets while keeping total spend constant.

Once management is on board, the sales team needs to understand the rationale behind the micromarket strategy and have simple tools that make it easy to implement. That means aligning sales coverage with opportunity and creating straightforward sales “plays” for each type of opportunity.

Align sales coverage with opportunity

During the annual sales-planning process, managers determine how to invest resources to capture anticipated demand. The first step is to overlay the rough allocation of resources across markets on the basis of their overall potential. But instead of then applying salespeople consistently across customers, managers use insights about growth opportunities and recommended coverage models for various market types to fundamentally rethink their reps’ distribution.

For example, a high-growth urban pocket with low competitive intensity where a company does not have much coverage should add “hunter” capacity; depending on customer density, that market might be able to sustain a few such reps, each specializing in a particular set of customer segments. A lower-growth market where the company has significant share would require “defensive farming”—that is, fewer reps, but with strong skills in account management. Local sales managers should be trained on how to use the data from the opportunity map to identify more precisely where they want their reps to spend their time and how they want to size their territories.

Consider the case of the chemicals company. Instead of looking at current sales by region, as it had always done, the company examined market share within customer industry sectors in specific U.S. counties. The micromarket analysis revealed that although the company had 20% of the overall market, it had up to 60% in some markets but as little as 10% in others, including some of the fastest-growing segments. On the basis of this analysis, the company redeployed its sales force to exploit the growth.

For instance, one sales rep had been spending more than half her time 200 miles from her home office, even though only a quarter of her region’s opportunity lay there. This was purely because sales territories had been assigned according to historical performance rather than growth prospects. Now she spends 75% of her time in an area where 75% of the opportunity exists—within 50 miles of her office. Changes like these increased the firm’s growth rate of new accounts from 15% to 25% in just one year.

What Is Big Data?

“BIG DATA” REFERS TO VAST DATA sets typically collected in multiple forms from many sources, often in real time. In B2B contexts these data may be pulled from social networks, e-commerce sites, customer call records, and many other sources. These aren’t the regular data sets that companies have in their CRM databases. Ranging from a few dozen terabytes to many petabytes, they’re so extensive and complex that specialized software tools and analytics expertise are required to collect, manage, and mine them. They can be used for everything from extracting sales insights from unstructured data (such as comments about particular brands on the internet) to assessing regional weather patterns to predict beer consumption to understanding the competitive landscape at a granular level.

Create sales plays for each type of opportunity

Micromarket analyses present myriad new opportunities, so the challenge for companies is how to help a generalist sales force effectively tailor messaging and materials to the opportunity.

Companies should identify groups of micromarkets—or “peer groups”—that share certain characteristics. For example, one peer group might be high-growth micromarkets with limited competitive intensity. Another might be made up of markets with similar operating cost structures. Because they are structurally similar, peer groups represent similar sales opportunities. Companies usually find that a set of four to 10 peer groups is a manageable number.

For each peer group, marketing managers develop the strategy and “play”—the best way to sell into that set of customers or market. For example, the chemicals company grouped its 70 micromarkets into four peer groups and outlined a strategy for each, such as “invest,” in which it sought to capture an outsize share of growth, or “maintain,” in which it sought to hold on to its market share while maximizing operating efficiencies. The play usually encompasses guidance on the offer, pricing, and communications and may include tailored collateral materials.

Companies typically devise and perfect plays either by adapting approaches that have been successful in similar settings or by testing new plays in pilot markets. One telecommunications company we spoke with continually tested plays on different customer segments to determine which offers at which price points with which types of services were most successful in various markets.

Finally, sales managers communicate to the field sales force the rationale for how markets or customers have been assigned to the peer groups and the strategies and plays for each group. This transparency will be important in motivating reps and helping them understand performance expectations, as we’ll discuss further on.

All this came together in the case of a cargo airline that used micromarket strategy with great success. In an innovative move, this airline delineated micromarkets not by geographic area but according to flight paths—regarding each route as a micromarket. It then gauged demand in each one—looking at variables such as volume and timing—and sorted customers into peer groups. One customer, for example, needed to ship fresh sea bass from Italy on Wednesdays for weekend consumption in New York. For another customer, a commercial greenhouse, peak demand occurred during the week before Valentine’s Day.

Drawing on this analysis, the company developed a different negotiation play for each peer group. For instance, it could increase prices for customers that shipped at high-demand times or on high-demand routes, and it could relax volume commitments for customers shipping on lower-demand routes. It could also adjust pricing according to how much capacity was available on a given flight or route and could recognize which customers were contributing more within challenging micromarkets and target—and reward—them accordingly.

Support the sales force in executing the plays

For a micromarket strategy to succeed, the sales training has to be experiential. Salespeople should engage with the opportunity maps that reveal hot (and cool) micromarkets in a given geography and test their intuition against hard data. (It can be eye-opening for them to discover that data analysis is often superior to anecdote in this realm.) Training should also allow them to act out and hone the recommended sales plays. Not only does this hands-on engagement help win over sales reps, but it’s a much more effective teaching method than lectures or demonstrations.

In addition to interactive training, reps will need direct coaching on specific pitches. To this end, several leading companies have created in-house “win labs” in which sales and marketing experts help reps craft their pitches. (The opportunity map, devised early in a micromarket analysis, provides invaluable information because it reveals drivers of demand: what makes a given customer buy.) Salespeople are required to bring their pitch plans to the win lab—usually virtually—and the lab team provides data, insights, and value-proposition collateral about the market or similar customers that the rep can use to create a sales play for a specific customer.

For example, our chemicals company produced pitch packs for each industry it served. The packs were further customized for the decision maker with whom the sales rep would interact. “Previously my documents looked like chicken scratch,” one rep eloquently put it. “Now I have slick, tailored materials ranging from a four-page summary for the factory manager to a more in-depth technical document for the R&D manager.”

Obviously, supporting the sales team to execute on micromarket strategies is not a onetime effort; management must create ongoing support capabilities. For instance, at the air cargo company, management developed a simple performance dashboard to help reps manage pricing and volume negotiations with large customers by route, time, capacity, and competition. The dashboard includes critical real-time information, such as whether the specific flight is overbooked, as well as information on the weekly itineraries of the airline and its competitors. The sales manager holds weekly sales strategy discussions with each rep to ensure that he or she is well positioned to negotiate the best deals. This effort has generated an average increase in share of wallet as high as 20% to 50% with key customers.

Put Data at the Heart of Sales

To sustain the early wins from a micromarket strategy, companies need to change their approach to sales force management in three ways: They must rethink performance management, open new channels between sales and marketing, and invest in talent development.

Performance management

Few managerial moves will kill new initiatives faster than continuing to reward old behaviors. As a start, managers must shift from assessing reps’ performance relative to the entire sales force to assessing it relative to the opportunity. You don’t necessarily want Mary to try to outperform James; you want her to hit or surpass a target you set on the basis of the micromarkets and peer group she’s selling to.

How data can drive sales growth

Traditional approach Micromarket strategy

Data management

Sales collects customer data from internal sources (CRM, billing, customer-service databases)

Sales combines very large databases of internal and external data such as demographics, social media chatter, and competitive intensity

Data are updated and analyzed quarterly or semi-annually

Data are updated and analyzed monthly, weekly, and daily

Outside analysts provide tools, advice, and statistical services

Data collection and analytics are done by in-house experts

Resource allocation

Sales coverage is defined by large regions and territories

Sales coverage is segmented into dozens or hundreds of micromarkets

Sales resources are allocated according to a region’s historical performance

Resources are deployed at the micromarket level according to expected future opportunity

Performance management

Rep (and channel partner) performance is assessed relative to other reps (and other channel partners)

Performance is assessed relative to the opportunity within micromarkets

Collaboration

Sales, marketing, and other departments are siloed

Sales, marketing, strategy, customer service, and other functions are collaborative

Performance management in a data-rich sales environment can get closer than ever before to measuring true performance of a sales force. An age-old source of frustration (and skewed impressions) is that a great salesperson in a declining market may be working miracles but she will look like she’s underperforming if she’s measured against historical data or colleagues who cover growing markets. By sorting micromarkets or customer sets into peer groups according to the future sales opportunity they represent, companies can create better-informed sales plans and targets. They also can, finally, compare apples with apples by looking at sales performance among reps working the same peer group and evaluating the reps against carefully considered targets for that group, rather than against arbitrary growth numbers.

Cross-functional collaboration

In micromarket-focused organizations, marketing often takes on an expanded role, particularly in providing sales with data analytics and supporting the development and testing of sales plays for a specific micromarket or customer peer group.

Consider the case of an Asian telecommunications company that found through a micromarket analysis that 20% of its marketing budget was being squandered in markets with the lowest lifetime customer value. The firm shifted these funds to its most lucrative markets, where two-thirds of the opportunity lay. Marketing then partnered with sales to reset customer-acquisition goals at the micromarket level, on the basis of each market’s potential; previously, the goals had been uniform across markets. In the past, when marketing opaquely set targets, sales would treat them skeptically and try to lower them; but under the new micromarket strategy, marketing collaborated with sales to set targets in a transparent way. Far from pushing back on targets, sales sought quotas 10% higher than those of the previous year—and met them.

Using Big Data to Target Individual Prospects

MICROMARKET ANALYSES ARE POWERFUL TOOLS for identifying granular growth opportunities and promising sales areas overlooked by competitors, but knowing which accounts within each micromarket are the best prospects turns a broad target into a narrow bull’s-eye.

To tailor offers, communications, and pricing, companies must seek data on potential customers’ specific characteristics, such as purchase history and service experience, satisfaction with offerings, and actual use patterns. For example, an agricultural equipment manufacturer that had divided its sales regions into micromarkets realized that its sales teams had relatively little insight into individual end users’ needs other than what they gleaned from focus groups, which often included “friendly” customers. The sales teams set out to collect and combine large data sets from partners about the ordering patterns of individuals and groups of customers and their geographies and then developed hypotheses about purchasing behavior for each peer group.

Building on its success in exploiting purchasing data, the company piloted a more audacious initiative that used remote sensing data to determine individual farmers’ activities. This provided the insights for sales programs tailored for individual farmers according to the types of crops they had under cultivation. This required sophisticated analytics, but the payoff was significant.

Some B2B firms use social media analytics to create highly targeted lead lists. One tech company, for example, identified keywords or search terms that signaled sales opportunities (for example, queries about how to use specific products or applications). Data scientists tracked IT managers using the keywords on Twitter, Quora, LinkedIn, and Facebook in real time and determined their location (using either IP address or public mobile phone location data). The location data was matched with internal data to place the people at specific companies. Those leads were then sent to the reps with a simplified set of sales insights related to the specific questions posted on social media. Sales reps converted these solid leads almost 80% of the time.

Given the historical tension between marketing and sales, management must establish clear, standardized processes at key bridge points. These include data handoffs and feedback loops that, for example, allow for insights provided by marketing to be tested by sales in the field and for the results to be returned to marketing to guide further research and analytics.

But this arms-length interaction doesn’t maximize the potential of true collaboration. What’s ultimately needed is to put marketing and sales in the same boat, as some of the most progressive organizations have, where they learn to function as a team. One way to do this is to formally (and physically) combine marketing and sales on certain tasks, as win labs do. Another is to hold marketing accountable for sales growth, an effective and increasingly common arrangement.

Talent development

To take advantage of the opportunities offered by micromarket strategy, both marketing and sales teams will need to step up their capabilities, particularly with analytic talent. That will be a challenge. The McKinsey Global Institute reports that by 2018, U.S. companies alone may face a shortage of up to 190,000 people with deep analytic skills as well as 1.5 million managers and analysts with the know-how to use big-data analysis to make good decisions. And yet the most effective sales organizations will be those that put data analytics at the center of their strategies.

The critical component in this talent equation is the bridge between analysis and action. While analytic talent is important, the best sales leaders put equal emphasis on translating the analysts’ insights into guidance that the field can act on. High-performing companies typically embed a few experienced and respected sales managers in the analytics team. They function as a link to the field and translate insights into language the field can follow and spread as best practices across markets. Some companies identify a few talented salespeople who are strong problem solvers, ground them in data methodologies, and challenge them to come up with innovative plays that take full advantage of big data. The firms follow through by funding their pilot ideas. This sort of frontline talent and capability building is essential and will produce the kind of inventive thinkers that are critical to creating successful micromarket strategies.

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Finding growth with big data is more than an add-on; it affects every aspect of a business, requiring a change in mind-set from leadership down to the front lines. This is a theme that echoed across our conversations with sales executives around the world. Describing such a transformation at Pioneer Hi-Bred, a DuPont agricultural products company, Alejandro Munoz, the vice president for the Americas and global production, told us, “This granular view is really a new way of thinking … and it takes time for it to become part of the company’s DNA.” At Pioneer, it took years, he said, but today it guides “how we run our commercial operations, how we invest against opportunities, and how we deploy sales and marketing.”

Micromarket strategies are demanding, but they consistently give sales a competitive edge. Sales leaders should ask whether they can afford not to embrace big data.

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