Editor’s note: Rob Riester is founder and partner of market research firm Peel Research Partners, Orange County, Calif. This is an edited version of a post that originally appeared under the title, “Are non-conscious market research approaches ready for prime-time?”Â
If you read any of the latest news and literature about the state of the market research industry you might think that traditional conscious market research approaches such as surveys are old school, misleading and a waste of time. Those selling non-conscious approaches such as behavioral economics models, neuromarketing, biometric, observational (big) data and other emerging techniques are the biggest critics.
I do agree that behavioral science has taught us that conscious approaches have limitations since many of our decisions are made with our values and emotions in the subconscious mind. I want to point out that these non-conscious methods have their own set of issues as well due to high costs, complexity of execution and in some cases potentially misleading results. We should continue to utilize and develop these techniques but rather than stomp on traditional approaches that still have value, let’s leverage what we’ve learned from behavioral science to make them as effective as possible until we clearly have something better.
The non-conscious approach to MR
At the heart of non-conscious methodologies is the need to move away from assessing stated behaviors and thoughts, which are subject to cognitive biases, to measuring actual behaviors and thoughts. As an example, behavioral economics approaches use experiments to show that actual decision-making and behavior can be different from what people think or say they would do under certain situations. For instance, in his outstanding book Predictably Irrational, Dan Ariely describes an experiment where people at an auction were asked to write down the last four digits of their social security number prior to bidding on wine. The experiment showed the fascinating power of priming, even if the prime had absolutely nothing to do with the purchase. Those with higher SSNs bid higher on the wine than those with lower SSNs.
Applied neuroscience studies consumers’ cognitive response to marketing stimuli by reading reactions to brain activity. In his book Buyology, Martin Lindstrom sets out to uncover the true reasons why people make buying decisions using these neuroscience research techniques. He criticizes traditional market research practices saying that they don’t tap into the unconscious mind which can have an important impact on buying decisions. With corporate sponsorship, he set out on a three-year, $6 million research study. I was quite excited to read the book, thinking it was going to be a holy grail in consumer understanding but in the end it was a bit of a let down. It seemed like chapter after chapter he kept proving things that were already generally accepted truths, like the power of a brand name, logo or color to initiate emotion or showing that brands elicit a similar brain sensory as religion. I wonder if the corporate sponsors felt like they got their money’s worth.
Those selling other trending approaches like big data analysis, biometrics, facial coding, etc., all use similar arguments. I’ve been hearing it in conferences, trade magazines, blogs and books. If these methodologies are so fantastic, why are they taking so long to go mainstream?Â
Benefits and limitations
There’s a reason why some of these other methodologies have not gained traction over the past several years. They sound fantastic and I really do think they provide value and are constantly improving but just like surveys they each have their limitations. A behavioral economics approach is an excellent way to assess actual consumer behavior but to do so you must set up a controlled experiment in person. This is costly, takes time and is a challenge to execute.
Neuroscience approaches are a great way to assess how a stimulus, such as an ad or consumer message, elicits emotions and can even tell you what kinds of emotions. We know that emotions are the primary driver of many decisions we make, so the better we can test actual emotional response, the better we can understand the impact on consumer decisions. These approaches are very expensive and limiting. You’re reading brain stimulations, not asking questions, so the results of these studies are limited to telling what emotions they elicit. Unlike a survey, you can’t probe into what the person likes or dislikes about the stimulus to understand why, find out how they see themselves using a product or what they associate with the brand to explain why they like it.
Not only that but the effectiveness of some of these non-conscious methods are now being put into question. As an example, a new meta study on emotional reactions shows that our physiological reaction to emotions are not uniform, which questions the accuracy of techniques that rely on them such as facial recognition and biometrics.
In addition, Steve Needel recently discussed the limitations of Implicit Association Test (IAT), which is a speed association test designed to access our subconscious attitudes and feelings about a subject. I had been thinking IAT might be the real savior in helping researchers develop a technique that is practical and affordable at measuring implicit thoughts and improving our predictability. It may still be the case but after reading his article, it sounds like it’s not quite there yet. In another example, Ray Poynter recently published an article on the problems with observational data (big data) that researchers should be aware of.
Opportunities for non-conscious techniques
My point is not to turn people away from these new non-conscious techniques. In fact, I think they are going to drive the future of the research industry. However, I don’t think we should take their salespeople at face value when they say traditional approaches are worthless. We need to do our homework on these approaches and look for validation rather than accept them just because they sound cool and cutting-edge. Rather than position non-conscious techniques as a substitute to conscious methods, we should really be thinking of them as a supplement so we can leverage the strengths of different approaches.
There is a clear opportunity in the field for someone to develop a practical, affordable and scalable approach to leverage the developments in behavioral psychology. I think we’re moving in the right direction but aren’t quite there yet. While we’re waiting for this holy grail, there’s a lot we can do as research practitioners to maximize the effectiveness of explicit, conscious techniques (such as the common survey), to make them as predictive as possible and avoid many pitfalls that drive their weaknesses.