It’s no secret that consumers are irrational creatures. Marketing professionals know, for example, that people will drive out of their way to get an advertised 50 percent discount on a $10 calculator, but they won’t make the same detour for a 5 percent discount on a $100 jacket. Most fail to compute that each trip offers the same $5 saving.
“Our research has shown that in many cases, consumers simply react to whatever information is put in front of them,” said Subimal Chatterjee, associate professor of marketing in Binghamton University’s School of Management.
Shoppers often approach buying decisions without strong preferences, Chatterjee said. “The environment, or what we call the context, surrounding the consumer is what ultimately drives the consumer’s preferences.” Context might include the variety of brands on display, the way items are placed, the range of prices available, a friend standing by with advice or a host of other factors.
Despite the resources poured into surveys and focus groups, the influence of context makes it hard to predict what consumers will buy, Chatterjee said. But it also offers opportunities to shape consumer choice. Marketers who understand context effects can turn certain elements on or off to steer shoppers toward the products they want to sell.
“My research focuses on the more descriptive aspects of consumer decision-making,” Chatterjee said. In one recent project, he and Timothy Heath of Miami University in Oxford, Ohio used laboratory experiments to explore how people make decisions that involve risk. Their goal was to improve upon prevailing theories, finding a more accurate way to predict when people will or won’t embrace uncertainty.
In one experiment, subjects were asked if they would rather receive $5 or take a one-in-one thousand chance of winning $5,000. Most subjects chose to gamble. One popular theory, called prospect theory, suggests people do this because they “overweight” the small probability of winning.
To test this explanation, Chatterjee and Heath offered another set of subjects the choice between $500 or a one-in-one thousand chance of winning $500,000. “If the prospect theory’s interpretation is correct, they would still overweight one-in-one thousand and go for the riskier alternative,” Chatterjee said. But most people in this group chose the $500.
When subjects explained their choices, members of the first group said that $5 is “a pittance”-too small a sum to dissuade them from trying for a higher reward. But $500 is “a lot of money”-enough to persuade the second group to accept a sure gain rather than gamble on a jackpot.
Working phrases such as “pittance” and “a lot of money” into a rule is difficult, but such expressions are more useful than the old mathematical formulas for explaining as well as predicting behavior in this kind of situation, Chatterjee said. And these descriptions can be useful to people who market products that involve risk, such as lottery tickets and insurance. Chatterjee says it is still not clear whether most people buy lottery tickets because they overweight the small probability of winning or because they think that the price of the ticket is a pittance to pay for the joy they get from dreaming of what they would do with untold riches. It’s also possible that this isn’t an either-or matter. It’s very possible that one perspective is more true for some people, while the other is more important to others. Both perceptions quite possible simultaneously factor into decisions made by a third group of lottery players, Chatterjee said.
Along with information gained in experiments in the lab, Chatterjee is starting to exploit the wealth of data that supermarkets capture when they scan bar codes and swipe shoppers’ loyalty cards. Studying data on purchases of staple products over eight years, Chatterjee and Heath are testing whether a discount steers shoppers in a particular direction. In lab experiments, they have found that national brands of orange juice benefit from discounts more when they dominate a store’s own lower-priced brand. Now they want to see if the same pattern holds in the real marketplace.
“When a national brand is discounted, did we see a sudden spike in their market share?” Chatterjee asked. “Preliminary results show that it makes a huge difference. Deep discounts of national brands, when they create such dominance effects, help those national brands more as compared to discounts that do not create dominance.”
Real-world data is also helping Chatterjee explore the economics of movie sequels. Films succeed when they exceed expectations, he explained. When a studio follows “The Matrix,” for instance, with “The Matrix Reloaded” and “The Matrix Revolutions,” audiences expect more gratification with each film, making success even harder to attain. To keep attracting crowds, movies in a series must get better with each release. However, Chatterjee said, “if you believe in the regression to the mean, then successes and failures should converge to the mean quality of the Matrix franchise.”
“Studio managers are very smart people. So the reason they make these sequels must be that they have figured out some way of beating the so-called regression to the mean argument,” Chatterjee said. Together with Suman Basuroy of the State University of New York at Buffalo and S. Abraham Ravid of Rutgers University, Chatterjee has assembled a database on more than 500 movies, with information on box office receipts, distribution, production budgets, positive and negative reviews and more. The goal is to define the characteristics of sequels that make money and sequels that don’t.
“Perhaps there is no point in thinking in terms of a mean quality level. Perhaps when studios make the sequel, they make a deliberate decision to be even more lavish” than in the first movie, Chatterjee said. An earlier collaboration between Chatterjee, Basuroy and Ravid showed that a large budget and popular stars often blunt the effects of bad reviews. Could those factors also work in favor of a sequel, no matter its quality? “We’re trying to gather the data, but our initial hypothesis is that successful sequels keep exceeding expectations” with ever-bigger budgets and stars.
Whether the data support that hypothesis or point to a different explanation, Chatterjee welcomes the results. “It’s nice when your theories are supported, but it’s even nicer when they’re not, because then you know that the problem is more rich than you thought,” he said. “Whenever I get into my research, I try to keep as open a mind as possible. And I love these surprises.”
