Is There a Difference Between Segmentation and Personalization?

Judy Bayer, Director of Strategic Analytics for Teradata International, and Marie Taillard, a professor of marketing and Director of the Creativity Marketing Centre at the ESCP Europe Business School in London, wrote a very interesting article in which they stated that they no longer believe in segmentation. [“A New Framework for Customer Segmentation,” HBR Blog Network, 12 June 2013] Obviously, the headline for their article (which they may not have personally selected) undercuts that statement; nevertheless, their arguments are both interesting and persuasive. They believe that segmentation (like dividing consumers by gender, ethnicity, geography, religion, etc.) promotes a “rigid methodology that carves out the market” in unnatural ways. They accept the notion that you “can’t be all things to all people,” and they believe that rigid segmentation defies that concept. They continue:

“To resolve these contradictions, we had begun pleading with students and clients to look for ‘jobs to be done.’ The approach echoes Ted Levitt’s famous comment about selling ¼ inch holes rather than ¼ inch electric drills, and advocates a mindset shift away from selling products to ‘doing jobs’ that solve customers’ problems. In Clay Christensen’s words, customers ‘hire’ products or other solutions because they have a specific job to fulfil, not because they belong to a certain segment.”

I find that argument quite compelling. Does that mean that segmentation is bad? Not necessarily. It does highlight the fact, however, that macro-level segmentation doesn’t go far enough in identifying the real needs of clients so that the right offer reaches them at the right time. Back in 2005, Clayton M. Christensen, Scott Cook, and Taddy Hall wrote:

“Thirty thousand new consumer products are launched each year. But over 90% of them fail — and that’s after marketing professionals have spent massive amounts of money trying to understand what their customers want. What’s wrong with this picture? Is it that market researchers aren’t smart enough? That advertising agencies aren’t creative enough? That consumers have become too difficult to understand? We don’t think so. We believe, instead, that some of the fundamental paradigms of marketing — the methods that most of us learned to segment markets, build brands, and understand customers — are broken. We’re not alone in that judgment. Even Procter & Gamble CEO A.G. Lafley, arguably the best-positioned person in the world to make this call, says, ‘We need to reinvent the way we market to consumers. We need a new model.’ To build brands that mean something to customers, you need to attach them to products that mean something to customers. And to do that, you need to segment markets in ways that reflect how customers actually live their lives.”

Obviously, Christensen, Cook, and Hall aren’t condemning segmentation in general; they just don’t believe it goes far enough — exactly the same point being made by Bayer and Taillard. Referring to Professor Levitt’s quip about selling holes, Christensen and colleagues write:

“Every marketer we know agrees with Levitt’s insight. Yet these same people segment their markets by type of drill and by price point; they measure market share of drills, not holes; and they benchmark the features and functions of their drill, not their hole, against those of rivals. They then set to work offering more features and functions in the belief that these will translate into better pricing and market share. When marketers do this, they often solve the wrong problems, improving their products in ways that are irrelevant to their customers’ needs.”

The challenge, of course, is trying to discover exactly what those needs are. Part of the answer is common sense (i.e., people buy drills to make holes); but, sometimes more information is needed to understand consumer needs. That’s where Big Data analytics come into play. Christensen, Cook, and Hall explain:

“There is a better way to think about market segmentation and new product innovation. The structure of a market, seen from the customers’ point of view, is very simple: They just need to get things done, as Ted Levitt said. When people find themselves needing to get a job done, they essentially hire products to do that job for them. The marketer’s task is therefore to understand what jobs periodically arise in customers’ lives for which they might hire products the company could make. If a marketer can understand the job, design a product and associated experiences in purchase and use to do that job, and deliver it in a way that reinforces its intended use, then when customers find themselves needing to get that job done, they will hire that product.”

Clearly, the word “job” must be loosely defined as any activity in which a consumer might want to participate. Listening to music, for example, isn’t typically thought of as a “job”; but, Apple has made a tidy profit selling iPods to satisfy that activity. Bayer and Taillard offer three steps that can be used to segment customers using the “jobs needed to be done” framework:

Step #1: Identify the contexts in which customers are using the company’s products. Examples of such jobs in the mobile telco realm might include: ‘being in touch with family and friends while roaming,’ ‘choosing the best entertainment and dining opportunities on the go over the weekend’ and ‘becoming more confident and secure in the use of a smartphone.’ A mobile service provider using multiple research techniques might find that there are fifty or more jobs to be done across their customer base. One person might typically get several jobs done by a given provider or brand.

Step #2: Combine information about transactions and customer behaviour in the contexts to describe each of the jobs to be done. For our weekend entertainment example, we would look for a combination of weekend searches for entertainment information, searches for local restaurants, movie reviews and social behaviour such as tweets about movies, concerts or restaurants. The ‘becoming confident and secure’ job might use data from call centre interactions and detect unused features on a new smartphone. The actual relevant data for each of the ‘jobs to be done’ is selected during the initial research as a function of the different contexts to be explored and the data available. This is very different from traditional behavioral segmentation which focuses on a wide set of individual variables such as the percentage of voice calls. Here we need a holistic view of the data required to characterize a context.

Step #3: Map individual customers to jobs, using the data. Each customer would be scored according to the relevance for him or herself of each of the jobs done. A specific customer may need 20% of the entertainment job, 2% of the confidence job and 40% of the being-in-touch job. The customer profiles would be spread across all jobs. From there it’s a simple step to cluster customers on their mix of jobs to be done rather than on their ‘raw’ behaviour, demographics or attitudes. For each segment, there may be only three or four jobs to be done that are crucial. This then allows the development of specific solutions for each segment.”

They assert that “setting the job done framework as a basis for customer segmentation allows us to use all the relevant data for customers in a meaningful and structured fashion.” Big Data analytics can help discover some of the less obvious relationships between products and activities. Bayer and Taillard conclude, “As brands access unprecedented amounts of data about consumers’ activities and are able to use them more efficiently and productively, they find broad patterns and trends and can indeed get better at detecting ‘the person behind the data’ and the jobs that person needs done.” In fact, they assert that customers provide data to companies with the explicit expectation that it will be used to make offers more personal. They write, “Customers … now expect that the data which they are implicitly sharing with brands will result in a positive impact on their own personal experience rather than in lumping them into new, irrelevant buckets.”

The point is, personalization is segmentation peeled to its core. Bayer and Taillard quote Peter Drucker, who once said, “The customer rarely buys what the business thinks it sells him.” He was probably correct. Bayer and Taillard conclude, “Big Data now lets us observe that journey. This type of segmentation is more important than ever as technologically empowered customers have more choice and the ability to craft their own solutions. It represents the new job to be done for us all of us in marketing.”

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