Tracking the Elusive Consumer
Consumer choice modeling can help companies improve their market share by offering a better understanding of consumer preferences.
Consumer choice modeling can analyze the most complex consumer decision processes and yield valuable insights for demand-driven strategy development by providing customer value segmentation maps, measuring market share impact of new product–service combinations, and assessing overall brand equity, finds a new report by Booz & Company.
Knowing what the customer wants, why individuals prefer one product or service over another and how consumers make their purchasing decisions will allow marketers to do their jobs properly and will determine the success or failure of virtually any business venture, especially in a world where today, consumer attitudes are harder to read than ever due to so much choice.
“The consumer choice analytical tool examines the personal reasons for individual choices and provides techniques researchers can use to measure and predict those choices,” explained Gabriel Chahine a partner at Booz & Company. By exploring why individuals make specific choices among various options, consumer choice modeling can determine what people in different economic and demographic strata are looking for and how much they are willing to pay.
This technique has dramatically evolved from lengthy paper-and-pencil surveys offering a series of preconfigured and static product or service possibilities, with shallow insights into preference. Instead, with advances in experimental designs and information technology—including broadband Internet access, digital imaging, video, and faster computing speeds—researchers today can better approximate the shopping experience when asking questions by adjusting product choices in reaction to a person’s answers.
“Analyzing responses from a representative sample of consumers allows researchers to produce econometric models that depict the relative weighting of specific product features and price points,” stated Chahine.
In 2007, Booz & Company surveyed more than 1,800 consumers in the United States applying consumer choice modeling to identify and measure the drivers of demand for mobile phones. People were asked to compare their existing package—device and mobile service contract—with alternatives.
The majority of the low-end and midlevel consumers were highly commodity driven. Other than by offering an attractive handset price, it is almost impossible to convince an individual to change his or her current mobile phone package. Of all phone users, owners of some low-end handsets value their phone package the least. Consequently, these consumers are the most willing to switch to another carrier and handset—an opportunity for competitors to attack that brand’s base by, for example, producing a low-cost package with a function or two that outpaces the relatively plain existing product.
Consumer choice modeling also has the ability to predict the impact of future products and services on the market. To illustrate this, Booz & Company used the data collected from the mobile industry surveys to simulate the characteristics of “the ideal high-end phone”. From this, the survey gleaned that features, design, and brand are of paramount value to consumers considering a higher-priced model. These factors were exactly what Apple focused on in developing its blockbuster iPhone, launched in July 2007.
One of the more fascinating conclusions of this study: although Apple Inc.’s iPhone was still months away from release and its price tag would be higher than that of most other phones, the Booz & Company model correctly predicted that it would be the most attractive overall offering to consumers.
Hybrid-electric vehicles are a good topic for consumer choice modeling research. Sales in the US have tripled since 2004, and today, these cars are attractive to consumers put off by higher gasoline prices because they offer improved fuel economy and, since they use the electrical power of the vehicle’s cordless battery when they can, do not require a new recharging infrastructure. Sales of hybrids have also risen because of government tax incentives.
Advances in diesel and biofuel technology suggest that there may be more palatable choices to power the traditional automobile engine in the near future. Meanwhile, all-electric and hydrogen-powered vehicles are also in development and show some early promise. “At present, auto companies can focus on one factor they can understand and address: consumer demand. What do consumers really want? As opposed to what they say they want,” explained Chahine.
Consumers make their car purchase decisions by simultaneously weighing brand, cost, performance, fuel economy, comfort, styling, service, environmental friendliness, and more. But if you asked individuals how they weigh these criteria they would be hard-pressed to articulate their decision-making process. Consumers’ choices in today’s complex marketplace are beyond the ability of even the consumers themselves to describe.
A consumer choice modeling project focused on hybrids would offer people different vehicle options and allow them to think like car buyers as they compared their typical past purchases with various hybrid possibilities. It would uncover the reasons individuals make specific choices among various options, such as fuel usage, CO2 emissions, battery range, performance, vehicle design, and price. With this data, auto companies could then deduce whether various consumer segments really want an environmentally responsible car, what features they require and how much they would be willing to pay.
“Perhaps most importantly, consumer choice modeling can reveal salient differences between managers’ beliefs about customers’ needs and preferences and customers’ actual needs and preferences,” Chahine said. For managers seeking reliable feedback on how customers view their products and services, consumer choice modeling provides a rigorous way to turn customer-driven feedback into profitable and sustainable tactics for retaining or capturing market share.