John R. Hauser is the Kirin Professor of Marketing at M.I.T.’s Sloan School of Management where he teaches new product development, marketing management, and statistical and research methodology. He has served MIT as Head of the MIT Marketing Group, Head of the Management Science Area, Research Director of the Center for Innovation in Product Development, and co-Director of the International Center for Research on the Management of Technology.He is the co-author of two textbooks, Design and Marketing of New Products and Essentials of New Product Management, and a former editor of Marketing Science (now on the advisory board).I think it wouldn’t be smart to start this interview with something as dull and complex as a definition. Or am I the only one that likes to read light weight and short articles?Let’s just get it over with.“Website morphing matches the look and feel of a website to each customer so that, over a series of customers, revenue or profit are maximized.”That didn’t hurt as much as I expected. I actually love the idea. It sounds completely logical.But are we talking about a completely new idea?There is tremendous variety in the way customers process and use information, some prefer simple recommendations while others like to dig into the details. Some customers think verbally or holistically, others prefer pictures and graphs. What is new is that we now have good algorithms to identify how customers think from the choices they make as they explore websites (their clickstream).But once we identify the way they think, we still need an automatic way to learn which website look and feel will lead to the most sales. This is a very complex problem which, fortunately, has a relative simple solution based on fundamental research by John Gittins. Our contribution was to combine the identification algorithms with the learning algorithms and develop an automated system that was feasible and practical. Once we developed the technology to morph websites, we were only limited by our imaginations.In our first application we matched the look and feel to customers’ cognitive styles. In our second, we matched to cognitive and cultural styles. We then used the algorithms to morph banner advertisements to achieve almost a 100% lift in click-through rates. Our latest project used both cognitive styles and the customers search history to match the automotive banner advertising to enhance clicks, consideration, and purchase likelihood.I also love the fact that you combine technology with behavioral science. On the psychology side of things you are/have been busy with cognitive styles, cognitive switching and cognitive simplicity.Can you tell us a little bit more about these theories and why you chose to use them?Customers are smart. They know when to use simple decision rules (cognitive simplicity) and when to use more complicated rules.Our research has been two-fold.(1) Website morphing and banner morphing figure out how customers think and provides information in the format that helps them think the way they prefer to think.(2) We have also focused on identifying consideration heuristics. Typically, customers seriously consider only a small fraction of available product. To do so they use simple rules that balance thinking (and search) costs with the completeness of information. By understanding these simple rules, managers can develop better products and better marketing strategies.We can now identify these decision rules quickly with machine-learning methods. But a caveat — customers do not always use cognitively simple rules. The “moment of truth” in a final purchase decision is best understood with more-complex decision rules and methods such as choice-based conjoint analysis.Most recently we’ve combined the two streams of research. Curiously, some of the algorithms used by the computer to morph websites are reasonably descriptive of how consumers take the future into account in purchases they make today. Prior research postulated a form of hyperrationality. Our research suggests that consumers are pretty smart about balancing cognitive costs and foresight.What are your main interests on the technology side of website morphing? Which algorithms take your fancy and why?Website morphing uses an “index” solution to learn the best morph for a customer. Our latest efforts also identify when to morph a website by embedded another “dynamic program” within the index solution. In our research to understand how consumers deal with the future, we’ve demonstrated that indices other than Gittins’ index might be more descriptive of consumer foresight.If I think about it, as a company you can either win the algorithm competition, or the psychology competition. Or lose. Do you agree?Actually, the companies that will thrive are those that understand the customers’ cognitive processes, have the algorithms to match products and marketing to customers’ cognitive processes, and have the organization that accepts such innovation.You need all three.Is this what marketing will be about in 5 years?There are many revolutions in marketing. It is an exciting time. It’s hard to list all of the changes, but here are a few.(1) Big data. We know so much more about customers than we ever did before, but this knowledge is often hidden within the volume of data. One challenge is to develop methods that scale well to be data.(2) Machine learning. There are some problems that humans solve better than computers and some problems that computers solve better than humans. Morphing, identifying simple decision rules, and studying consumer foresight are all possible with the advent of good machine-learning methods. But we have only scratched the surface.(3) Causality. Marketing has used quite successfully small-sample laboratory experiments and assumption-laden quantitative models. However, the advent of big data and web-based data collection has made it possible to do experiments and quasi-experiments on a large scale to better establish causality and to better develop theories that are externally valid. Causality also means replication. There is a strong movement in the journals to require that key finding be replicated.(4) The TPM movement (theory + practice in marketing). Conferences, special issues, and organizations are now devoted to matching managerial needs to research with impact. In fact, a recent survey by the INFORMS Society of Marketing Science suggests that approximately 80% of the researchers in marketing believe that research should be more focused on applications.(5) A maturing perspective on behavioral science. Researchers are increasingly less focused on “cute” findings that apply only in special circumstances. They are beginning to focus on insights that have a big impact (effect size) and apply to decisions that customers make routinely.Companies that combine algorithms, an understanding of customer decision-making, and the ability to use data will be the companies that succeed.Originally published at www.sciencerockstars.com on October 21, 2013.From a quick cheer to a standing ovation, clap to show how much you enjoyed this story.Let’s Fix the Future: Scientific Advisor @jadatascience