Rationalizing the Sometimes Irrational CustomerBy Guest Author Print
Consumers can make emotional buying decisions, but analytics can help businesses better understand, and even predict, seemingly irrational customer behavior.
By John Lucker
Traditional business intelligence systems typically use management reporting and statistical methods to interpret customer behavior with one underlying assumption: that the customer is rational. It’s no wonder so many of these systems fail to live up to expectations of the businesses that have invested in them.
The fact is that customers are human, and humans are often not rational. Therefore, customers, by definition, are not always rational. These deviations from what is expected of customer behavior often confound companies and their leaders.
Being human, consumers can make emotional buying decisions. While many economic and business axioms are predicated on behaviors using the law of large numbers, on an individual basis, consumers can often move in contrarian directions to what’s expected.
Thus, if companies subscribe to traditional economic expectations, they risk not understanding what truly motivates their customers on an individual basis. This lack of understanding leads to asynchronous connections between companies and their customers, which, in turn, can translate into lost, missed or declining revenue.
Analytics can help businesses better understand, and even predict, seemingly irrational customer behavior. By interpreting signals (which are sometimes faint) and clues to customer behavior, analytics offers businesses a way to make sense of and capitalize on idiosyncratic customer preferences.
Customer choices and actions can be statistically scrutinized to determine how and why behaviors may “make sense” in accordance with our logical assumptions—or perhaps violate much of what was previously thought to be true. Despite the views of many classical economists, consumers do not necessarily optimize utility functions based on some fixed set of preferences embedded in their psyches.
Factors such as life experiences, framing of situations, habits, self-control or lack thereof, social impacts, and decision fatigue are examples of important components for determining what makes people behave as they do. In this manner, complex individual and market data can serve as the customer’s “window to the soul,” but it may not always perfectly predict outcomes. The probability, circumstance and impact of imperfect predictions should be factored into all business solutions and actions.
The Roots of the Irrational Customer
Classic economic theory tells us that consumer behavior is born of certain traits: unbounded rationalism, willpower or restraint, even selfishness. Historically, these traits have been identified as the reasons humans make certain choices under specific circumstances. In business, these cognitive perceptions have long been relied on to inform business strategies, guide product development and give marketing executives their directives.
The problem is that consumers don’t always follow these rules of thumb or conform to our experience and wisdom. Marketers often find that traditional evaluative methods of supply/demand models, consumer surveys or observational focus groups can go only so far to help understand individual behaviors.
When faced with value choices, some consumers make decisions that appear counterintuitive. Perhaps humans are fickle, acting more often on whim than fact. But there are forces today that are changing human behavior faster and more radically than ever before.
For example, our insatiable appetite for connectedness is spawning vast online social networks where experiences and desires shape actions within large communities of “friends”—all with stated “likes” or “thumbs up or down” points of view. Thanks to mobile technology, instantaneous communication propels many toward decisions that are tethered to evolving beliefs, emotional actions and input from others with whom consumers are in touch with in real time, as they travel with their mobile devices through everyday life.
Confusing the issue is that most consumers think they are rational. While they may research a purchase in detail before making it, in reality, a tangled web of correlations–along with a network of influencers, followers and transient leaders—often sways their behavior without their being aware of it.
With the pervasiveness of product review information, a seemingly rational purchase choice can be driven by others’ nonfactual, subjective or irrational influence. Too often, misinformation can be viewed as accurate information.
Fortunately, as consumers travel through this interconnected network, they leave behind quantities of digital exhaust in the form of data. Within this data are clues to what customer behavior might be—with and without the externalities previously discussed—and how buying patterns are formed, and what might happen next. Because we are not always rational, superior predictions can result from granular observations of how individuals, and those like them, actually vote with their wallet and their feet.
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