Many prediction posts get chastised for being self-promotion pieces, saying that the future of the industry can be found in the products that the writer sells, rather than being serious thinking on what change we can expect in the coming year. There is truth in this criticism.
A recent article in the AMA 75th anniversary issue asked industry experts what the fifth “P” of marketing would be as the industry evolves. Not surprisingly, the expert from the “customer experience” company said “People”, the expert running the “Business and Social Purpose” unit said “Purpose”, and the expert from the “privacy” company said, yep, you guessed it, ”Privacy”.
And yet, even within that truth there is a necessary exception. If your firm is truly pushing the boundaries of your industry, is it possible to write a prediction piece that isn’t at least somewhat related to what you sell? It is with that truth and hopeful exception in mind that we write our perspective on the trends of our industry.
The market research (MR) industry is at an exciting shift point and there are many players with niche specialties who all lay claim to owning part of our future. Neuromarketing firms will say that the future of MR can be found in their methods. Consulting firms can argue that the rise of Big Data business analytics marks the end of traditional MR. Behavioral Economics feels justified in taking credit for the coming wave of change in marketing tactics. And if you haven’t heard yet, social media is the future of, well, everything.
For marketers and researchers, understanding the place and potential prominence of all of these waves of change can be challenging. To cut through the clutter, we need to do what we do best in our own client facing work as an industry: get to a fundamental explanation. In our work as an industry, we often find the best inspiration for our clients by uncovering fundamental truths about human motivation and behavior. Good prediction pieces should also look for fundamental explanations, enduring truths, that are relevant in the present as well as the far reaching future. Finding these truths within our industry can lay the foundation for creating the market research firm of the future.
To that end, I offer this statement as an enduring truth: The future of marketing can be found today in the behavioral science literature. This is a statement that we believe will be as true in ten years as it is today.
Marketers are ultimately trying to influence behavior in a desired direction, and often seek insights from MR firms on how to more effectively achieve those ends. Fortunately for our industry, the behavioral science literature, defined broadly to include major disciplines of Psychology, Sociology, Neuroscience, Cultural Anthropology and Behavioral Economics, represents a vast reservoir of insights on the drivers of human behavior that is largely untapped by business.
Strikingly, some of these insights on why people do what they do are 30-40 years old. They are taken for granted as common knowledge among the scientists studying them, and yet, are novel breakthroughs when applied in business. Furthermore, the fact that these disciplines are dedicated to uncovering and publishing new knowledge on the drivers of behavior everyday indicates that this resource of novel marketing inspiration is renewable and enduring.
If this insight is in fact a fundamental and enduring truth, how is it related to the current buzz trends including neuromarketing, big data, behavioral economics and social media monitoring? We would argue that the behavioral sciences offer a more fundamental explanation of the “whys” behind behavior. Therefore, each of these buzz trends can be more profitably studied through a behavioral science lens. When armed with the “whys” behind behavior, marketers can apply and replicate the principles more broadly and accurately for more hits and fewer misses.
Here are a few ideas on how the future can be found in the behavioral science literature and the challenges and opportunities that lie ahead for current advanced approaches:
Neuromarketing has suffered from over-hype and what some are calling the “golden hammer” methodological issue (i.e. neurological measurement isn’t necessarily the best tool for every research question). Yet, neuromarketing is still on the rise and producing valuable new insight for clients by getting around the “can’t say/won’t say” problem that dogs traditional MR.
Nonetheless, the widespread application of neuromarketing is faced with a challenge from implicit behavioral methods which also address the “can’t say/won’t say” problem, but do so more efficiently and cost-effectively with representative samples. These implicit priming and response time techniques offer much of what neuromarketing techniques offer, with some exceptions, and in some cases offer much greater diagnostic information on discrete emotions and subconscious associations.
This raises a critical question for the future application of Neuroscience: is the measurement of brain activity necessary for individual business application research projects, or is it better used as an R&D platform to produce new fundamental knowledge on consumers and to provide neural evidence for the efficacy of other more practical methods of studying the subconscious? Neuroscience has big contributions to make to market research and study of consumer behavior. However, there is an open question of whether that contribution may be better achieved through the identification of fundamental principles that can then be measured more practically and efficiently using other implicit research technology that is less expensive and more representative.
Big data is all the buzz these days and many are saying has big implications for market research. There is a sound argument that it is a threat to traditional MR. It certainly can become a threat in the near-term if enterprises begin to siphon budget from traditional market research and insights initiatives in order to fund behavioral analytics projects on a large scale. However, in order to be a significant long-term threat to MR, big data analytics are going to have to overcome two primary short-comings.
First, big data analytics are necessarily backward looking. Surely there is great insight to be gained by looking at past behavior, but there are also significant limitations to using past behavior as a predictor of future behavior. Advanced primary MR techniques still hold the advantage of being forward looking through the use of experimental design informed forecasting.
Second, Big Data analytics will suffer from producing unsatisfactory explanations of the why’s behind the behaviors being observed and correlated. One of my favorite examples of this is oversimplified in IBM’s business analytics “Panini in the sunshine” commercial. In this spot, the company claims to have found insight through analytics for a small business. The insight is that when the weather gets warm, Panini sales go up. Left at this level of explanation, this insight leads to the very practical action of offering panini in the summertime to increase sales volume. However, if we had a more fundamental explanation of why Panini sales go up when the temperature rises, we would be able to do more than offer Panini when the sun is shining. Deeper levels of explanation would allow the small business to offer an optimized suite of complementary products, market more effectively with motivationally targeted messaging, optimize inventory management and so on.
This example actually reveals how big data analytics offer a tremendous opportunity for MR. Observations coming out of big data analytics are going to be begging for deeper explanations. Primary research informed by behavioral science is the best tool for uncovering the true whys behind behavior, and these fundamental explanations provide a platform for replicating observed past behaviors in ever-changing future markets.
Behavioral Economics is another current buzz topic. Recent writing by Sunstein, Thaler, Ariely and other great translators has effectively begun to bridge the gap between behavioral science and business. The conversation around human rationality has changed and the application of findings from this literature is growing. Many MR firms are excited by these developments and are scrambling to show expertise in the area. Similarly, enterprises are implementing the principles independently and seeing some successes along with some failures.
We predict that the staying power of Behavioral Economics in business will be dependent on the successful codification of these principles into a business application taxonomy. The discipline will need to move beyond just having a list of exciting effects that companies are trying to implement on an ad-hoc basis. MR firms that prove to be successful as behavioral economics consultancies will provide guidelines on which behavioral economics effects are relevant to specific business applications, and on how to implement the effects for successful business outcomes.
There is one additional boon for MR that arises from the Behavioral Economics boom. The approach generates many new ideas on how to market more effectively. Most of these ideas should be tested prior to going to market in large scale. Thus, Behavioral Economics consulting offers a great research platform for MR firms who specialize in experimental design and choice studies. On balance, the most successful implementations of Behavioral Economics principles will be those that were rigorously tested prior to launch.
Finally, Social Media is influencing marketing and operations decisions in many industries and MR is no exception. What we like about social media data analysis, is that it gains insight through observation. Insight through observation is the key to revealing the true drivers of behavior and it is the foundation of the most powerful advanced methods: neuroscience derives insight through the observation of blood flow and electrical behavior in the brain, big data derives insight through the observation of past behavior in the market, behavioral economics derives insight through the observation of behavior in different experimentally designed conditions, and social media analysis derives insight through the observation of the character of conversation.
All of these approaches effectively solve the can’t say/won’t say problem. In best case scenarios, social media data reflects the observation of a natural social interaction rather than reflecting answers to direct questions from a researcher. In predicting the future role of social media in MR, we anticipate the following.
First, using social media platforms to conduct surveys will continue to rise in the near future. However, this only represents the use of a new access point to consumers and does not represent fundamental innovation for the MR industry. In fact, this use of social media will face the same challenge that traditional MR practices have: explicit survey questions of consumers suffer from the can’t say/won’t say problem and often do not reveal the true drivers of behavior, nor accurately predict future behavior. MR firms who develop applications for assessing the subconscious motivations and emotions of consumers through a social media platform will be in better position to leverage this new access point while simultaneously evading the perils of can’t say/won’t say.
Second, advances in text analytics are empowering companies to derive insight and quantify consumer sentiment in the social conversation. These advances will continue and become more broadly accessible and implemented by small to mid-sized firms. Furthermore, insight through observation of the social conversation will form a solid platform for MR firms to execute deeper dive primary research projects to reveal the fundamental drivers behind the sentiment being expressed socially.
Reflecting on these predictions it is apparent that we see the future of industry as being fundamentally grounded in gathering deeper insights on the why’s behind behavior. Furthermore, we think that many of these insights can be found today in the behavioral science literature, and that this will be the case for years and years to come. So yes, our predictions end up being squarely positioned around many of the products that we sell to solve the can’t say/won’t say problem in MR. Whether this ends up being the future of behavioral marketing research or just a hopeful outlook on our business model remains to be seen. It is our hope that our approach to these predictions has found a level of explanation that is fundamental enough to be enduring long into the future and practical enough for our industry to put to use today.