July 2009

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.

Keith Devlin, NPR’s “math guy” and Gary Lorden, the math consultant on the hit CBS television series “NUMB3RS(tm)” have written an enjoyable and informative book that explains the math behind many of the more sophisticated analytic methods finding their way into the customer knowledge business these days.  If you’ve been perched at the edge of the “supercrunching” pool, wanting to dip your toes but afraid you’ll end up over your head, this book might be just what you need.  Because the context is crime fighting (at least as depicted on network TV), the applications are fun as well as informative.  Topics include geographic profiling, data mining, changepoint detection, Bayesian inference, the math of networks, and a bit of game theory (Chapter 11:  The Prisoner’s Dilemma, Risk Analysis, and Counter-terrorism).

The Numbers Behind NUMB3RS:  Solving Crime With Mathematics.  PLUME (Penguin) 2007.  ISBN 978-0-452-28857-7.

How does your organization generate ideas for new products, services, or business processes?  Many of the companies I’ve worked with over the years rely largely on internal sources for new ideas.  If the ideas come from R&D, they are most likely responses to specific technical challenges or attempts to find applications for inventions.  If the ideas come from product marketing, they are often aimed at creating points of difference versus competitors.  Of course, some innovations result from the combination of technical solutions with product or service differentiation.

Looking at innovation from the technical side of the equation, it’s useful to think of a continuum that ranges from small, incremental improvements in existing solutions (applying a bit of adhesive to notepads to create Post-It Notes) to innovation that springs from discovery of a new phenomenon (such as nano-technology).  Most innovations that make it into the marketplace are near the incremental end of this continuum.  It can takes years or perhaps decades for the discovery of a new phenomenon to result in commercially viable products or services.

It’s a truism that most new products fail–estimates range from 80 to 90% of consumer products.  I once heard the chief marketing officer of a consumer products company cite this statistic and then go on to say that his company’s solution was a fourfold increase in the number of products they planned to introduce.  The products that succeed are those that do a job for customers that either is not being done by existing solutions or not done well.

The idea that customers “hire” products and services to do jobs for them is not new.  In an article in the December, 2005 issue of Harvard Business Review (“Marketing Malpractice:  The Cause and the Cure”) Clayton Christensen, Scott Cook and Taddy Hall remind us that Theodore Levitt would tell his students that customers “don’t want to buy a quarter-inch drill.  They want a quarter-inch hole!”

Some innovations do not change the job so much as the way the job is done.  Before FedEx, people sent documents and packages, but they seldom sent them overnight.  And now, many of the documents that were sent as FedEx overnight letters are transmitted within seconds or minutes as attachments to email.  These are examples of innovations that completely changed the way the job was done.

Whether the job is existing or emerging (more on emerging jobs in a moment), successful innovation depends on understanding the jobs that customers want to perform.  The challenge, form the customer knowledge perspective, is identifying and categorizing the jobs in a way that systematically informs innovation efforts.  Think of the job a customer wants to do as a demand creating condition. We can operationalize demand creating conditions as the concerns and interests that lead individuals to their everyday pursuits, and may lead to behavior in the marketplace, such as a search for a product that does a particular job.  Emerging jobs are those that result from underlying structural changes, such as an increase in the number of mothers of school age children working out of the home giving rise to a host of new “management” challenges for those moms, and opportunities for innovations like mobile telephones.

Geraldine Fennell is a consultant based in Ireland who has developed a framework for understanding consumer motivations. Along with Geraldine and her collaborator Greg Allenby, I designed a study to apply this framework to brand choices for automobiles.  Geraldine breaks consumer motivations into seven different categories, some of which are “sticks” (things we want to avoid) and some of which are “carrots” (things we want to approach).  The sticks include:  solving immediate problems; preventing potential problems; and maintaining the status quo.  The carrots include:  exploratory opportunities and sensory opportunities.  You’re thinking–that’s only five categories.  You’re right.  These five categories are independent of the focal activity.  They apply whether the job I’m doing involves drilling holes in a piece of wood or getting to and from the grocery store. Two additional categories reflect specific experiences in doing jobs:  dissatisfaction in use (with the product or service hired to do the job) and ineffective or frustrating outcomes (when no product or service exists that does the job well).

Companies often fail to identify emerging jobs and jobs that are not done well by existing products and services because they frame the question in terms of the current or existing marketplace.   As an example, the typical “needs-based” segmentation for automobiles will enumerate benefits and associated product features, such as “interior storage,” “rear seat legroom” and “fuel economy” and ask consumers how important or appealing each of these is when choosing a vehicle.  This approach leads to small, incremental improvements in features and benefits.  You won’t hit on an innovation like cupholders by asking consumers how important interior storage is.

A good starting point is qualitative research (and I recommend individual in-depth interviews rather than focus groups) organized around the stick and carrot categories I listed above.  Here are statements reflecting some of the “sticks” that might affect our automotive choices:

  • I’m concerned about getting from point A to point B without getting injured (solving an immediate problem)
  • I’m concerned about the impact I have on the environment (preventing future problems)
  • Driving is no big deal for me (maintaining stable state)

Here are some “carrots:”

  • I am easily bored when I drive (exploratory opportunity)
  • It’s important for driving to be fun (sensory opportunity)

And here are examples for the last two categories:

  • I’m concerned about the mechanical reliability of the car I drive (dissatisfaction in use)
  • It’s difficult to find a vehicle that meets all my driving needs (ineffective/frustrating outcome)

You can use these categories to guide the discussion, even listing them for the interviewee.  A second step involves matching the concerns and interests to specific usage or consumption occasions.  In our case, we asked consumers whether each concern was an issue in usage occasions such as traveling to the store for groceries alone, with children, or with other adults (three separate occasions).

To briefly summarize the study results, we found that a segmentation based on these (and additional) concerns and issues helped explain preferences for luxury car makes.  As an example, preference for Mercedes was strongest in a segment that was concerned both about safety and operating costs.  Volvo also did reasonably well in this segment, and also in a segment of consumers who are concerned about their impact on the environment.  Both of these brands have advertised the safety of their vehicles.

This might seem like a “traditional” needs based segmentation but remember–we did not ask consumers how important it was that a vehicle have certain safety features.  We asked them whether they had any concerns about their safety in each of several usage occasions.

When it comes to innovation, this type of information can help a company focus resources on opportunities that align with consumer motivations.  Each one of these concern-occasion intersections is a potential job that a consumer is trying to do.

Practically every “breakthrough” or game-changing innovation I can think of either enabled the customer to do a new job, or did an existing job better than any existing solution.  The best way to increase the odds of successful innovation is to start with the customer.

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