Think like a respondent: improving MR ROI through better survey design

There’s no question that marketers are more focused than ever on the ROI of marketing research.  All too often, however, it seems that efforts to improve ROI aim to get more research per dollar spent rather than better research. 

Better survey design is one sure way to improve the ROI of marketing research.  However, despite advances in our understanding of the cognitive processes involved in answering surveys, market researchers continue to write poor survey questions that may introduce considerable measurement error. 

I think this is due in part to the fact that the processes involved in asking a question are fundamentally different from the processes involved in answering that same question.  Recent contributions to our understanding of the answering process have been integrated into a theory of survey response by Roger Tourangeau, Lance J. Rips, and Kenneth Rasinski (The Psychology of Survey Response, Cambridge University Press, 2000).  According to Tourangeau, et. al., answering a survey question involves four related processes:  comprehending the question; retrieving relevant information from memory, evaluating the retrieved information, and matching the internally generated answer to the available responses in the survey question.

“Think aloud” pretesting, sometimes known as “cognitive” pretesting or “concurrent protocol analysis” is an important tool for improving the quality of survey questions, and  well-designed think aloud pretests often have, been in my experience, the difference between research that impacts a firm’s business results and research that ends up on the shelf for lack of confidence in the findings.

Warning–what follows is blatant self-promotion of a sort.  ESOMAR is offering my workshop, “Think like a respondent:  A cognitive approach to designing and testing online questionnaires” as part of Congress 2011.  The workshop is scheduled for Sunday, September 18, 2011. This year’s Congress will be held in Amsterdam.  I’ve offered the workshop once before, at the ESOMAR Online Conference in Berlin last October.

Hope to see you in Amsterdam.

 

Starbucks new logo

Last week Starbucks CEO Howard Schultz unveiled a new logo for the brand.  By now we should know that any attempt to mess with a popular brand (formula, name or logo) is going to elicit at least a few expressions along the lines of “what are they thinking?”

Schultz tried to communicate just what they were thinking in an online video, saying that the new design respects the brand’s hearitage but also looks toward a future for the firm that’s not just coffee.  And on the Starbucks website one of the company’s creative managers, calling the logo change “the project of a lifetime,” says:  “From the start, we wanted to recognize and honor the important equities of the iconic Starbucks logo.”

Firms do change logos without the flack that The Gap generated a couple of months ago, but that change (abandoned in the wake of criticism) and Starbucks new logo may offer important lessons about when and why to change logos, and what not to change.  As I’ve expressed in a previous post, I’m skeptical about neuromarketing, but logos are one area where I think companies might do well to invest in a little neuroscience before making big changes.  Logos provide a sort of cognitive shortcut, and we humans are cognitive misers.  The more “iconic” a logo is, the more effective the cognitive shortcut.  To be iconic, a logo needs to be distinctive (not easily confused with other symbols) and consistently associated with with a specific set of brand experiences.  Moreover, the iconic elements of a logo are usually basic properties like shape, color, typeface and spatial relationships within the logo.  The true test of an iconic element is the extent to which you can minimize or degrade the image (showing just a small part, for example) and evoke the complete logo or the associated brand.  For example, in the hit CBS drama NCIS the main characters drink coffee from cups that have some sort of green and black circular logo with white lettering–just enough to suggest Starbucks.  I think one problem with The Gap’s proposed logo was that it changed several iconic elements at once (background color, typeface, and spatial relationships within the logo).

Having been on the inside of a few re-positioning efforts–some involving new logos or package designs–I think that we often over-intellectualize the meaning of the elements in a logo.  Starbucks appears to believe that the mermaid (or siren) in the center of the logo is the symbol of the brand, but some of the comments posted to their website indicate that many customers never really noticed that the element in the center of the logo was a mermaid.

I don’t know whether Starbucks (or The Gap, for that matter) did any consumer research in the course of developing their new logos.  However, the typical research methods for this type of thing rely on verbal responses, while logos operate mostly at a nonverbal level.  Perceptual research methods are more appropriate for this type of problem than focus groups and surveys.

Many companies have modified their logos, of course, but those that succeed seem to recognize that it’s more important to understand the Gestalt of the logo than any potential symbolic meaning of the logo or individual elements.  You can tweak a typeface, for example, to look more modern, or play with the saturation and tint of the color scheme, but if several elements change at the same time, or the spatial relationships change, you can expect the kind of feedback that The Gap and Starbucks have experienced.

Starbucks may well stick by its new logo.  In that case, I suspect customers still will be able to find a store when they want, or recognize Starbucks coffee on their supermarket shelf.  My main issue with these logo changes is that they are superficial.  Consumers don’t buy “Starbucks” or “the siren”–they buy a particular constellation of experiences and solutions to problems.  If you get the latter right and you’re lucky enough to have an iconic logo, why abandon it?

Copyright 2011 by David G. Bakken.  All rights reserved.

 

Spirit’s carry on charge–smart move or not?

You’ve probably heard about Spirit Airlines’ decision to charge customers for carry on baggage–$30 per bag if purchased in advance, or $45 “at the door.” You’ll still get your one free “personal item.”  This latest example of an airline unbundling one more feature of its service offering resulted in a promise to Sen. Charles Schumer (D, NY) from five other major airlines that they will not follow Spirit’s lead, at least for now.

Spirit claims on its website that this charge will lower overall costs to passengers and improve service.  Here’s how this is supposed to work:  fares will be lowered somewhat, as will fees for checked baggage.  Since carry on bags have a big impact on how long it takes to board and to deplane (according to Spirit, but many passengers will probably agree), reducing the number of carry on bags on a flight will reduce turnaround time and get passengers off the plane more quickly once it has arrived at its destination.  Security lines will also move more quickly (ignoring the effect of passengers traveling on other carriers who will still have their carry on bags).

One wonders whether Spirit gathered any consumer intelligence or conducted any experiments to arrive at this decision.  Airlines have had varying success at generating revenues by implementing fees for service features that were once bundled into the fare.  US Airways, for example, seems to have retreated from charging for non-alcoholic beverages (including bottled water).  JetBlue has started charging for headphones but recent experience suggests that on some flights they still may give them out for free once the plane has left the gate.  Fees for checked bags may stick–as long as you get that free carry-on–but any additional fee gives a competitor a potential point of differentiation.  Have you seen the Southwest commercial, “Battle Cry,” where the ramp crew, in the manner of sports fans, flash the passengers on a rival airline with “BAGS FLY FREE” spelled out across their chests?

People’s Express was one of the first post de-regulation airlines built around a low cost no-frills business model, and perhaps the first to charge for checked baggage ($3 per bag).  Many elements of PE resembled Southwest’s model–one type of aircraft, open seating, and really large overhead compartments for those carry-on bags.  Food and drink were available for purchase, and all the seats on a given flight were the same price.  In many ways, the experience was more like being on a train or bus than an airplane, and with one-way fares between Newark and cities like Boston as low as $19, a lot of passengers were likely switching from those modes.   There’s no question that PE helped democratize flying, overcoming the affordability barrier for many passengers.  Following it’s initial success, People’s Express went on a buying spree (taking on a lot of debt) and the legacy carriers discovered yield management, enabling them to match or come close to PE’s fares for at least some passengers.  With all that debt, PE abandoned its original customer value proposition and profit formula and began to look more like other airlines.  Ultimately, PE was acquired by Texas Air and ceased to exist as a brand.

Whenever an airline makes a move like charging for carry-on bags or for using the lavatory (Ryanair), I can’t help but wonder if they even have a customer value proposition.  One problem may be that flying on an airplane is only a means to an end (the job that the consumer wants to do at the other end of the flight) rather than an end in itself.  This makes it hard to find a price that both matches the value to the passenger (which is a function of the value of completing the job at the destination) and the cost of providing the service, plus some profit.  The carriers have long inferred that business travelers place more value on the job to be done at the destination, and they have implemented a variety of pricing strategies to segment their customers based on the assumption that leisure travelers are far more price sensitive.  However, most of the assumptions about pricing do not reflect any understanding of the ways customers evaluate pricing relative to the value of the jobs to be done.  In the absence of such understanding, carriers have resorted to “mechanical” solutions to pricing and revenue generation.

Actions like Spirit’s carry-on fee often provide new instances of the law of unintended consequences.  It will be interesting to see what happens in the next few months.  Will Spirit retreat, or will other carriers follow suit?

Copyright 2010 by David G. Bakken.  All rights reserved.

 

Borders on the brink

Yahoo Finance published an article today from Investopedia by Mark Riddix titled “Business on the brink: Change or fail?”  Of the five companies profiled, the only one that evokes a twinge of sadness for me is Borders Books (the others are Blockbuster, Rite-Aid, Palm, and trucking company YRC).

 

Are market research agencies the “back room” to the back room?

An insightful new report from Boston Consulting Group reveals that “most companies have not yet unlocked the value of consumer insight.”  The report is based on a quantitative survey of more than 800 executives from 40 global companies with at least $1.5 billion in sales.  The survey was supplemented with around 200 qualitative interviews, and the participants included line managers as well as members of the consumer insight function in these companies.

The authors found that companies fall into one of four stages of consumer insight capability:

• traditional market research function
• business contribution team
• strategic insight organization
• strategic foresight organization.

The companies falling into the last two stages are getting the biggest return on their investments in consumer insight.  However, according to this report, only about 10% of the surveyed companies are in one of these two stages of insight capability.  In Stage 1 companies, the insight function is more or less an “order taker” relegated to “back room” status, and the focus is on tactical research.  Things are a little better in Stage 2 companies in that  sometimes projects are more strategic, but the insight function is still project-focused.

If the consumer insight function is relegated to back room status in the majority of companies, does that make research agencies a back room to the back room?

 

Social Networking, as seen by The Economist

The current issue of The Economist (January 30 -February 5 2010) features a 15-page special report on social networking.  Typically thorough, the report covers history, the differences between major players (Facebook, Twitter, and MySpace), benefits for small businesses, potential sources of profit for social networking sites, and some of the “peripheral” issues–such as the impact on office productivity and privacy concerns.  For any marketers who’ve been caught by surprise by the emergence of social media and social networking as marketing forces or been watching out of the corner of their eye, this special report might be especially informative.

 

Recommended reading: The Psychology of Survey Response

The Psychology of Survey Response by Roger Tourangeau, Lance J. Rips, and Kenneth Raskinski (Cambridge University Press, 2000) will change the way you think about the “craft” of survey design.  While there are other, well-regarded books on survey question construction (such as Asking Questions by Norman Bradburn, Seymour Sudman, and Brian Wansink, Jossey-Bass, 2004) and tons of individual research papers and articles on various aspects of survey design, measurement scales, question construction and the like, this is the first book I’ve encountered that presents a practical conceptual framework for understanding the cognitive processes that produce a response to a given question.  Moreover, the authors review a lot of relevant research to support their framework.

 

Do you know what jobs your products do for your customers?

The news last week that Kohlberg Kravis Roberts & Co. was giving Eastman Kodak a cash infusion of $400 million prompted me to reflect on the changing fortunes of the yellow box over the last fifteen or so years.  For most of my lifetime, Kodak defined consumer photography.  Sure, there were some threats from Fuji and point-and-shoot 35 mm camera makers, but for the average snapshooter, or the parents of newborns, Kodak pretty much owned the market.  And they understood the need to make photography simple.

They had a great business–revenues and profits were tied to the number of images that people captured on film.  The more pictures people took, the more film they used, and the more paper and chemicals processors consumed to turn those images into prints.  Kodak perfected the model over the years, as processing services became almost instantaneous, and consumers could get two prints of every image for almost no incremental cost (but doubling the volume of Kodak paper that was sold–a big advantage in an economies-of-scale business).

Kodak’s consumer marketing strategy was built around the belief that the primary job that consumers were hiring cameras, film, and processing for was documentation of life’s special (“Kodak”) moments.  Consumer research, for example, showed dramatic increases in picture taking following the birth of a first child (with lower peaks for each subsequent child!).

Kodak’s fortunes in consumer photography were tied to this belief and their initial strategy in response to digital photography included a continued emphasis on simplifying the process (cameras with printer docks, for example) and capturing a big chunk of the consumables volume, primarily photo paper.  But something strange happened with digital photography.  The relationship between the number of images captured and the number of prints produced pretty much evaporated.  This was a clue that maybe there was a different job that digital photography was doing for consumers.  And it looks like that job is sharing experiences.  Are cellphone cameras popular because they eliminate one device or because they allow people to share images and experiences  almost immediately?

The documentation job is no doubt still important, but digital photography has revealed that there was at least one other important job.  Because digital does that job better than film photography (no need to print images to share them, for example) and does the documentation job for consumers at least as well as film, the value network has shifted dramatically.

This is a common dynamic with disruptive innovation.  The success of the incumbent technology obscures the fact that it may not do all the jobs it is hired for equally well, or not as cheaply as it could be done.  AT&T, for example, when confronted with competition from the likes of MCI and Sprint, assumed that the “job” they were doing for consumers was providing access to any telephone in the world.  It turns out that the job a significant number of consumers wanted to perform was connecting to a very small number of specific telephone numbers, and MCI and Sprint enabled that at a much lower price.  The rest of that story is telecommunications history.

Copyright 2009 by David G. Bakken.  All rights reserved.

 

Book review: buy-ology: Truth and Lies About Why We Buy

buy-ology:  Truth and Lies About Why We Buy by Martin Lindstrom, Doubleday, 2008

The author bio on the inside of the jacket describes Martin Lindstrom as “one of the world’s most respected marketing gurus” and claims that he has a “global audience of over a million people.”   Even so, until this book was published I’d never heard of Martin Lindstrom in my many years as a marketing consultant.  More than anything, my ignorance points to the fragmented nature of the marketing world, where it’s entirely possible for an individual to be known to a relatively small group of clients until he or she publishes a book that makes the New York Times best-seller list.

Lindstrom’s book is, sort of, about the application of cognitive neuroscience to marketing and, more specifically, to branding. Technological advances have given neuroscientists new tools for localizing and measuring the level of activity in different areas of the brain, and these tools are being applied to marketing and other areas of economic behavior.  The technology that is getting the most attention is functional magnetic resonance imaging, or fMRI.  In the typical diagnostic MRI, a series of images are captured  that reflect “snapshots” of an area that, taken together, paint a detailed internal picture of some part of the body.  fMRI improves upon this (at least from the neuroscientist’s perspective) by creating a sequence of images over time. Because the fMRI can detect changes in blood flow to different parts of the brain, this effectively allows a researcher to map the areas of the brain that are “engaged” in different cognitive tasks.  Like a patient undergoing a diagnostic MRI, a subject in an experiment that employs fMRI must lie inside the MRI machine.  Any external stimulus (such as an advertisement or task instructions) must either be auditory or presented to the subject by reflecting it onto a small mirror above the subject’s face.  If you’ve ever experienced an MRI, you know that there is loud and frequent banging during the test.  Most fMRI studies are conducted on small samples of consumers (fewer than thirty, in many cases).

The main alternative technology for “brain imaging” is electro-encephalography (EEG).  Much like an electrocardiogram that measures electrical activity in the heart, EEG measures electrical activity in the brain. Over the years, technological refinements have made EEG measurements more precise, leading to an ability to isolate the activity in different regions of the brain.  Whereas the increase in blood flow detected by fMRI has a small delay (e.g. one to three seconds), the responses detected by EEG are instantaneous.  EEG is therefore very good at detecting what we are paying attention to.  And, because the sensors for EEG can be embedded in something like a baseball cap, it’s possible to monitor brain activity while subjects are, for example, watching television programs in a group.  The form of EEG monitoring used in most neuromarketing studies, steady state topography (SST), is also less expensive than fMRI.  A new EEG technology, magneto-encephalography (MEG), is, like fMRI, not portable and at this early stage, relatively expensive.

Most “neuromarketing” brain imaging research relies on correlating brain activity that occurs in response to some relevant stimulus (which could be viewing a television program, watching an advertisement, or making a choice from a simulated shelf, as examples) with what we know about localization of function in the brain.  If different stimuli or cognitive tasks lead to activity in different regions of the brain we can make inferences based on what we know about the functions performed by those areas of the brain.

Our understanding of localization of brain function is based on anatomy, on behavioral changes or impairments that result from injury or damage to some part of the brain, on studies with direct measurement of neural activity (by inserting electrodes into individual neurons), and on brain imaging studies.  Some functions are clearly localized in specific parts of the brain, particularly sensory and motor functions.  For example, the areas of the brain that process visual and auditory stimuli are distinct and, except in rare cases of synesthesia, there is a one-to-one correspondence between sensory input and the area of the brain that is activated.  When it comes to processing complex information, the picture is not so clear cut.  We may know which areas are involved in, say, emotion, but we cannot precisely determine the form of that involvement.  Thus, it’s one thing to observe that areas of the brain believed to involve emotion and reward “light up” when we are exposed to an advertisement, and quite another to conclude that a brand message must activate particular areas of the brain in order to create loyalty to the brand.

According to Mr. Lindstrom, the basis for this book is a research study involving about 2,000 individuals that he conducted over a three-year period with the help of Richard Silberstein of the Brain Sciences Institute at Swinburne University in Melbourne, Australia, and Gemma Calvert, Managing Director of Neurosense, a UK consultancy specializing in the application of neuroscience to consumer marketing.  About 90% of the subjects participated in studies employing SST/EEG to measure brain activity.  The remainder took part in fMRI measurements.  The $7 million (US) or so that Mr. Lindstrom claims the research cost was provided by a few client companies.  Mr. Lindstrom reminds us repeatedly (4 times in the first 11 pages of the book) that this is the “most extensive study of its kind ever conducted” (and “twenty-five times larger than any marketing study ever conducted”).

Unfortunately, the book fails to deliver the goods promised in the subtitle, “Truth and Lies About Why We Buy.”  It may be that Mr. Lindstrom kept all the good stuff for the clients who kicked in to fund his study.  Instead of an informative report on a comprehensive program of research, we get only the sketchiest details of the neuroscience experiments (and when we do, the results are usually “shocking”).  Mr. Lindstrom has received some attention for his finding that warning labels on cigarette packs and advertisements may actually trigger a craving for the product.  He tries to extend this finding to broader areas of marketing, but I’m not sure that physically addictive products are the best neuroscience model for other consumer goods.  His general technique is to toss out a proposition about some underlying, presumably unconscious process that determines our marketplace choices, provide a number of anecdotes as examples of this proposition and, finally–in some but not all cases–share some finding or other from his study that proves what he’s telling us.

In a paper presented at the ESOMAR Congress 2006 (title “Cognitive Neuroscience, Marketing and Research:  Separating Fact from Fiction”), Jane Raymond, a neuroscientist at Bangor University in Wales, and Graham Page of Millward Brown note that “a great many papers have been written and presented on cognitive neuroscience in recent years–some by neuroscientists, some by enthusiastic amateurs, some by start-ups with a product to sell.”  By the way, this paper is an excellent introduction to cognitive neuroscience and it’s potential relevance for marketers.  I’m not sure if it’s available anywhere except in the conference proceedings.

Mr. Lindstrom’s enthusiasm for his topic is evident throughout the book and despite the fact that he comes up short with respect to practical information or to my standards for research-based books, it’s still a fun read.  One thing that annoys–almost all of the notes are presented in the form of URL’s rather than bibliographic citations, and almost all of them are from secondary sources rather than the original research reports or articles.

So, by all means read this book if you like, but don’t take it as the final word on the way our brains govern our marketplace choices.

Copyright 2009 by David G. Bakken.  All rights reservcd.

 

The Path to Customer Knowledge

If we’re going to create a pathway to customer knowledge, we ought to start with some kind of definition, so we’ll know where we’re trying to go.  One might argue that anything we “know”–any facts that we have about customers–constitutes “knowledge.” At one level that’s true.  But, as I’ve suggested in an earlier post (“The Advantage in Customer Knowledge,” May 21, 2009) knowledge is more than just a collection of facts.  In our ESOMAR paper “Creating Customer Knowledge” (ESOMAR Consumer Insights, 2004), Mike Lotti and I defined customer knowledge as “the understanding of customer motivations, attitudes, perceptions, and experiences such that we can predict customer behavior.”  In other words, customer “knowledge” really represents our “theory of the customer.”

Almost all marketers have one or more implicit models of customer behavior that guides their decision-making.  In many cases, these models are developed on the basis of limited information, combined with specific psychological processes that we use to help us explain and predict the behavior of other people.  These processes are sometimes referred to as implicit psychology and they affect our perceptions of others in predictable and biased ways.  For a good introduction see Implicit Psychology:  An Introduction to Social Cognition by Daniel M. Wegner and Robin Vallacher (Oxford University Press, 1977, still in print).

To create our theory of the customer we need to mimic the explicit process represented in the scientific method we all learned in school.  Around the time Mike and I were preparing our paper, an article by Clay Christensen and Michael Raynor appeared in the Harvard Business Review (“Why Hard-nosed Executives Should Care About Management Theory,” September, 2003) describing this process as applied to management theory.  Theory building begins with observation and description of the phenomenon of interest.  This has been a major role of market research–to observe and describe the behavior of customers.  The second step is categorization of the observations and descriptions, perhaps revealing patterns of association or correlations in the data.  The third step is the development of predictions or hypotheses about causal relationships.

Despite all the data that are available about customers from transactional databases, surveys, focus groups, and so forth, many organizations are unable to capitalize on opportunities to create customer knowledge.  There are at least four reasons for this.

• Much data gathering is aimed at answering specific and urgent tactical questions.  Research may be conducted to populate marketing dashboards, to measure reactions to new product ideas or to gauge the impact of specific marketing actions (ad copy, price changes, etc.), but research is seldom conducted specifically to develop and test theories of customer behavior. That does happen in the academic community, but sometimes such work is too theoretical or focused on too narrow a problem.  At any rate, once the immediate question is answered, management’s attention quickly turns to the next tactical problem.
• Most data gathering is project-specific.  This is a consequence of the combined effects of the tactical and decisive nature of most research and the budgeting process in most firms.  I helped create business unit market research budgets when I worked for AT&T, and it was a process of estimating the number of concept tests we would do in a year, ad copy tests, customer satisfaction tracking studies, and so forth.  No one ever said “How much do we need to spend to understand our customers?”  This makes it difficult to integrate multiple studies into the kind of programmatic research–typical in the academic world–that is essential to the development and refinement of theory.  Granted, some firms are adopting knowledge management technology to facilitate retrieval of information that has been gathered across multiple projects, but that’s a far cry from systematically designing research to build on what’s known and to test specific propositions about customers.
• Market researchers and users of market research too often equate correlation with causation (there’s a related problem in that we sometimes see illusory correlations–associations that we expect to find based on our implicit models that are not actually present in the data.  If you don’t think this happens, take a look at How Doctors Think by Jerome Groopman).  As our analytic methods and our computers have become more powerful we’ve come to rely almost exclusively on number crunching to to develop “predictive models” of customer behavior.  
• The internal politics of the organization may derail even the best intentioned and executed knowledge creation efforts.  Different stakeholders have different motivations, and they often have different ways of gathering and interpreting data from customers (think of the way the sales force thinks about customers compared to the way a product marketing manager or brand manager thinks about customers).  In some organizations, much of the customer data is “owned” by the management information systems or information technology groups.  

Market segmentation research offers a good example of the ways in which companies can squander opportunities to create customer knowledge.  There are many varieties of market segmentation, but the original paper on the topic by Smith (“Product Differentiation and Market Segmentation as Alternative Marketing Strategies,” Journal of Marketing, 21, 3-8, 1956) described an orientation based on understanding the varying motivations that buyers bring to the marketplace.  In this view, segmentation requires an in-depth exploration of consumer motivations outside the marketplace.  This is a critical distinction. As Greg Allenby of The Ohio State University and his collaborator Geraldine Fennell point out, demand creating conditions–the problems that consumers are trying to solve to improve their well-being–are spawned upstream of the marketplace.  

Best-practice market segmentation requires a multi-stage research solution, beginning with broad qualitative research to understand the potential variability in consumer motivations, followed by more qualitative to refine the hypotheses generated in the first round, and finally, carefully designed quantitative research to put those hypotheses to the test.  What we’d really like to see is quantitative that allows us to test competing hypotheses about the drivers of consumer behavior, rather than confirmation or disconfirmation of a single hypothesis.  This tends to make best-practice market segmentation (where the goal is understanding variability in consumer motivations, rather than simply targeting consumers based on differential response to marketing efforts) complex and expensive, especially in today’s environment when firms need to understand their customers on a global basis.

In my recent experience, many firms are “doing” segmentation.  That is, they are commissioning their research supplier partners to conduct segmentation research.  All too often that involves a kitchen sink set of questions and whatever method the supplier recommends for clustering survey respondents based on the answers to those questions.  Good segmentation work is still being done, but there is a lot of poorly conceived segmentation work happening as well.

What’s missing in most segmentation research today is the systematic upfront development of theory to explain variability in consumer motivations.  Quantitative segmentation studies should be confirmatory, not exploratory.  If you don’t have a pretty good idea of the conceptual dimensions (or “constructs”) that will define the segments going in, you’re likely to be disappointed with the results of a quantitative segmentation study.

Look for more on best practices in market segmentation in future posts.

Copyright 2009 by David G. Bakken.  All rights reserved.