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UFO sighting causation correlation market researchSmallI read a blurb in The Economist about UFO sightings. They charted some 90,000 reports and found that UFO's are, as they put it, "considerate". They tend not to interrupt the work day or sleep. Rather, they tend to be seen far more often in the evening (peaking around 10PM) and more on Friday nights than other nights.
The Economist dubbed the hours of maximum UFO activity to be "drinking hours" and implied that in fact that drinking was the cause of all those sightings.
As researchers, we know that correlation does not mean causation. Of course their analysis is interesting and possibly correct, but it is superficial. One could argue (and I'm sure certain "experts" on the History Channel would) that it is in fact the UFO activity that causes people to want to drink, but by limiting their analysis to two factors (time of day/number of sightings), The Economist ignore other explanations.
For example, the low number of sightings during sleeping hours would make perfect sense (most of us sleep indoors with our eyes closed). The same might be true for the lower number during work hours (many people don't have ready access to a window and those who do are often focused on their computer screen and not the little green men taking soil samples out the window).
As researchers, we need to consider all the possibilities. Questionnaires should be constructed to include questions that help us understand all the factors that drive decision making. Analysis should, where possible, use multivariate techniques so that we can truly measure the impact of one factor over another. Of course, constructing questions that allow respondents to express their thinking is also key...while a long attribute rating battery might seem like it is being "comprehensive" it is more likely mind numbing for the respondent. We of course prefer to use techniques like Max-Diff, Bracket™ or Discrete Choice to figure out what drives behavior.
Hopefully I've given you something to think about tonight when you are sitting on the porch, having a drink and watching the skies.

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Rita’s Italian Ice is a Pennsylvania-based company that sells its icy treats through franchise locations on the East Coast and several states in the Midwest and West.

Every year on the first day of spring, Rita’s gives away full-size Italian ices to its customers. For free. No coupon or other purchase required. It’s their way of thanking their customers and launching the season (most Rita’s are only open during the spring and summer months).

Wawa, another Pennsylvania company, celebrated 50 years in business with a free coffee day in April.  

Companies are giving their products away for free! What a fantastic development for consumers! I patronize both of these businesses, and yet, on their respective free give-away days, I didn’t participate. I like water ice (Philadelphia’s term for Italian ice) and I really like coffee. So what’s the problem?

In the case of Rita’s, the franchise location near me has about 5 parking spots, which on a normal day is too few. I was concerned about the crowds. On the Wawa give-away day, I forgot about it as the day wore on. That made me wonder what other people do when they learn that retailers are giving away their products. So, having access to a web-based research panel (a huge perk of my job), I asked 485 people about it. And here are the 4 things I learned:

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In my previous post I applauded Matthew Futterman’s suggestion that two key changes to baseball’s rules will produce a shorter, faster-paced game, one that will attract younger viewers. While I may not be that young, I’m certainly on-board with speeding up the game. I believe that faster-paced play will lead to greater engagement, and greater engagement will lead to greater enjoyment.

In some sense this is similar to our position on marketing research methods. We want to engage our respondents because the more focused on the task they become, the more considered their responses will be. One of our newer tools, Bracket,TM allows respondents to prioritize a long list of items in a tournament-style approach. Bracket™has respondents make choices among items, and as the tournament progresses the choices become more relevant (and hopefully more enjoyable).

Meanwhile, back to baseball. The rule changes Futterman suggests are very simple ones:

Once batters step into the box, they shouldn't be allowed to step out. Otherwise it's a strike.

If no one is on the base, pitchers get seven seconds to throw the next pitch. Otherwise it's a ball.

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Sandy Hingston wrote an article appearing in the March 2014 Philadelphia Magazine about Milennials’ lack of interest in history, specifically as it relates to baseball (read abridged version here). Later in the article, she quotes Matthew Futterman, who posited in the Wall Street Journal that two key changes to baseball’s rules will produce a shorter, faster-paced game that will attract more youngsters. This notion didn’t sit well with Sandy Hingston.  

But it did sit well with me. Very well, in fact. I’m a Boomer like Hingston, not a Millenial, but I find myself increasingly frustrated by things that, put simply, take too long. Baseball is one of them. In fact, my TV viewing of the Phillies (go Phils!) decreased as my TV viewing of another professional sport was on the rise: golf.

Anybody who watches golf on TV, or attends an event live, will attest that players can take a very long time in between shots, which is essentially the same criticism lobbed at pitchers who take too long between throws. Slow-play in golf is a hot topic, and the golf powers-that-be are quite willing to put players “on the clock” for taking their good sweet time. So to be fair, both sports are grappling with this issue.

A first or second round of professional golf will take the better part of a day to televise. A 9-inning baseball game, in contrast, lasts around 3 hours. Given the disparity between how long each event takes, one would think that I, as someone interested in fast action, would prefer watching baseball. But that’s just not the case.

This got me thinking about an issue that we grapple with in market research: respondent tedium. Long attribute batteries of low personal relevance can tax a respondent’s patience. Even being compensated doesn’t always overcome the glaze that forms over their eyes when faced with mundane, repetitive tasks. That’s why we do our best to keep respondents engaged by having them make choices (our Bracket technique is a good example of this). In bracket, the choices become more relevant as the task progresses – not unlike how play at the end of a close game or match becomes more exciting to the viewer.

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  • Maryann Davoli
    Maryann Davoli says #
    Very interesting, Michele. I'll be looking forward to reading Part 2. Hope you are doing well! Maryann

Recently I had lunch with my colleague Michel Pham at Columbia Business School. Michel is a leading authority on the role of affect (emotions, feeling and moods) in decision making. He was telling me about a very interesting phenomenon called the Emotional Oracle Effect – where he and his colleagues had examined whether emotions can help make better predictions. I was intrigued. We tend to think of prediction as a very rational process – collect all relevant information, use some logical model for combining the information, then make the prediction. But Michel and his colleagues were drawing on a different stream of research that showed the importance of feelings. So the question was, can people make better predictions if they trust their feelings more?

To answer this question they ran a series of experiments. As we researchers know, experiments are the best way to establish a causal linkage between two phenomena. To ensure that their findings were solid, they ran eight separate studies in a wide variety of domains. This included predicting a Presidential nomination, movie box-office success, winner of American Idol, the stock market, college football and even the weather. While in most cases they employed a standard approach to manipulate people’s feelings of trust in themselves, in a couple of cases they looked at differences between people who trusted their feelings more (and less).

Across these various scenarios the results were unambiguous. When people trusted their feelings more, they made more accurate predictions. For example, box office showing of three movies (48% Vs 24%), American Idol winner (41% Vs 24%), NCAA BCS Championship (57% Vs 47%) and Democratic nomination (72% Vs 64%), weather (47% Vs 28%) were some of the cases where people who trusted their feelings predicted better than those who did not. This, of course, raises the question of why? What is it about feelings and emotion that allows a person to predict better?

The most plausible explanation they propose (tested in a couple of studies) is what they call the privileged-window hypothesis. This grows off the theoretical argument that “rather than being subjective and incomplete sources of information, feelings instead summarize large amounts of information that we acquire, consciously and unconsciously about the world around us.” In other words, we absorb a huge quantity of information but don’t really know what we know. Thinking rationally about what we know and summarizing it seems less accurate than using our feelings to express that tacit knowledge. So, when someone says that they did something because “it just felt right”, it may not be so much a subjective decision as an encapsulation of acquired knowledge. The affective/emotional system may be better at channeling the information and making the right decision than the cognitive/thinking system.

So, how does this relate to market research? When trying to understand consumer behavior through surveys, we usually try to get respondents to use their cognitive/thinking system. We explicitly ask them to think about questions, consider options and so on, before providing an apparently logical answer. This research would indicate that there is a different way to go. If we can find a way to get consumers to tap into their affective/emotional system we might better understand how they arrived at decisions.

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