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New Product Research

In Thinking, Fast & Slow, Nobel winner Daniel Kahneman (click here previous post about Thinking, Fast & Slow) talks about the two selves people have: the experiencing self and the remembering self. The terms are self-explanatory and vacations are a good way to think about them. The part of us that is enjoying the vacation is the experiencing self, while the part that is reliving it later (sometimes years later) is the remembering self. Neither one may be more important, but the emphasis we place on one or the other could determine our behavior. So, for example, you can enjoy the vacation or take plenty of pictures to relive it later, depending on the self that is more important. A way of finding out which self is more important is to ask ourselves whether we would go on a certain vacation if we could only enjoy it, but not take any pictures (or video, etc).

low response rateA recent discussionon Linkedin pondered whether MR is having its own global warming crisis in the form of an ever dwindling respondent pool. As always, this brought on arguments that response rates need to be improved, quality enforced and of course talk about how much we have slipped as an industry since the good old days. Some blame clients for this (they demand speed and lower cost without concern for quality!) and some blame researchers for not holding clients’ feet to the fire.   It struck me that this is yet another case of researchers not viewing things from a client perspective.

Segmenting Movie Goers

Posted by on in New Product Research

A few months ago I posted that we researched 18 factors in deciding which movie to see and where to see it. We reported that “It’s in 3D” was at the bottom of the list, and concluded that 3-D was unlikely to save the American movie box office.  

What made the top of the list was “I like the plot or story,” followed by “It is in my favorite movie genre” and “It has my favorite stars.”  

But surely the plot isn’t the critical decision-maker for every movie-goer; there must be groups of viewers whose decisions revolve around some of the other items on that list. We took their ratings and ran a segmentation analysis. While this type of analysis is done on a much grander scale by researchers in the movie industry, we thought it would be interesting to do some analysis of our own.

daniel-kahneman-thinking-fast-slowIn his opus Thinking, Fast & Slow, Nobel winner Daniel Kahneman (click here for previous post) relates a story from early in his career when he was leading a team to develop a curriculum and write a textbook on judgment and decision-making in high schools. He had assembled a group of experts and after working diligently for a year they had completed an outline of the syllabus and written two chapters. One fine day when discussing procedures for estimating uncertain quantities, it occurred to him that he should get an estimate from everyone on how long he thought this whole project would take. Being the clever psychologist that he was, rather than ask the group to guess publicly, he asked each person to make a confidential prediction. The mean was about two years and the range was about half a year on either side. In other words, the group was very consistent in its prediction.  

Then Kahneman had the idea of asking the curriculum expert in the group, Seymour Fox, for his specific opinion. Only this time he asked Seymour to think about other teams like theirs and asked how long it had taken them to finish. After a long silence the astonishing answer came out. Nearly half the groups never even finished the project. Among those who did the average time taken was about seven years! Seymour Fox also estimated that this group was slightly below average in terms of the skill set it possessed compared to the other groups. The killer, of course, was how long it actually took Kahneman’s group to complete their project. Eight years!

Effectively what had happened was that a group of experts in judgment and decision-making had somehow fooled themselves into thinking way too optimistically about the future and had made predictions based on it. This included the expert who in spite of having the best information somehow ignored that in favor of an optimism bias. As Kahneman graciously adds, it also included a leader who did not pull the plug on a project that would likely take another six years and was a coin toss as to whether it would even be completed.  

The biggest lesson Kahneman draws from this episode is that there are two approaches to forecasting which he labels the inside view and the outside view. The inside view is when we focus on the specifics of our own situation, try to form a coherent story and somehow convince ourselves that given the “special” nature of our situation success is just around the corner. In some ways this probably explains the enormously high failure rates of new products and the only slightly lower failure rates of new small businesses. The outside view is one that takes into account the general failure rate of the reference class of objects. Assuming the reference class is properly chosen, the outside view should provide a nice ballpark of where the estimate is going to be. In practice it is better to start there and adjust it using the special knowledge of the inside view and thus avoid embarrassing predictions. Not following this kind of procedure is why we routinely read about say, large transportation projects often running over by years and into several times the original projected cost. It is also why kitchen renovations routinely cost twice the initial estimate for the average household.

So are there specific lessons for market researchers? Of course. One is with the likelihood of success of any kind of new technological advance (mobile, neuro, text analytics, social media monitoring, whatever). Without understanding the reference information for how such new technologies can ultimately fare, we can too easily get caught up in the fanciful nature of a specific technology and make prognostications not just about success, but also about time frames within which such things can come true. On the flip side the death of older technologies can be too gleefully forecast (“Surveys will die in a year!”) because of the glamour of newer techniques if the reference cases are not carefully analyzed.

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Even Economists Are Gamifying

Posted by on in New Product Research

Gamification as a means to understand consumer choice is a relatively new idea for research (and controversial in many circles), but it is not new everywhere. For example, one sociologist, Dmitri Williams, has been studying economic behavior using gamfication for four years. His experiments were based on the online fantasy game EverQuest II, which involves thousands of players selling millions of virtual items every month. In essence it is a fantasy economy that works like a real economy.  

Professor Williams theorized that this provided an opportunity to observe the choices players made without fear of the Hawthorne effect (some people give different answers when they know they are being watched).   It also allowed him to set up test and control groups and observe what happens when, to take a simple example, prices go up (if you guessed “people buy less” you win) and to look at gender roles. He saw applications in many fields, not the least of which being testing the impact of various government intervention options before implementing them in the real world.

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