Leigh Caldwell

Readers of this blog are likely to be already familiar with many of the experimental results of behavioural economics (BE). Discoveries such as anchoring, hyperbolic discounting, loss aversion and other cognitive biases are now quite well-known in the market research world. Each of them comes with its own tricks for how to influence consumers, or pitfalls to look out for when designing questions. (those who are less familiar can find out lots more about them from some of the leading BE books: Predictably Irrational by Dan Ariely, Thinking Fast and Slow by Daniel Kahneman or Basic Instincts by Pete Lunn).

These experiments and their associated influence tricks are the most visible aspect of behavioural economics as a field. And they’re useful too – but only in specific circumstances. Most research projects don’t have a specific need for an understanding of hyperbolic discounting or loss aversion. To put this into practice in market research, we’d like to have a clearer set of rules about what BE says about consumer insight.

There is a more powerful way to look at the empirical discoveries of BE. As well as standalone discoveries, they are also a set of clues to deeper and more important underlying insights about how people think and decide. These general lessons are applicable in many different situations – and can lead us towards finding the specific biases, limitations, heuristics or methods of influence that apply to our own consumers.

The drawback is: there is no single theory of how people make decisions. Scientific psychologists, working backwards from the results of experiments, have come up with a number of alternative frameworks. They aren’t mutually exclusive – think of them as different, valid, ways to look at the world. As a researcher or marketer, you may want to understand more than one of these models in order to decide which one to use in a particular project.

In this article I’ll briefly look at three of the leading theories of decision making. Each of these can be useful in understanding how consumers think about, and hopefully how they decide to buy, your clients’ products.

The first is the information processing model of Payne, Bettman and Johnson. This theory says that when we make a decision, we have to process the information available to us by using a series of smaller individual steps. The steps include small tasks such as estimating how good a product is, comparing two different products, or choosing to look for more information before making the decision. When confronted with a choice such as which car to buy, we decide on a strategy, gather and process more information until we’re ready to make the decision, and then choose one of the options.

Payne and Bettman also propose that while doing this, we are governed by “meta-motives” or goals that we want to satisfy during the decision-making process itself. There are four possible meta-motives:

  •  maximising decision accuracy
  •  minimising cognitive effort
  •  minimising negative emotions such as regret or anxiety
  •  being able to justify our decision to others

Different people focus on different meta-goals, so in order to appeal to the widest set of consumers, your clients might want to communicate in several different ways to match these four decision-making styles.

A second theory is the fast and frugal heuristics approach of Gerd Gigerenzer, Peter Todd, Ralph Hertwig and other researchers in the “ABC” school. This theory says that we have a toolbox of standard mental shortcuts which we use in different situations. For instance, in evaluating products we might use the “Take The Best” rule, which say that we first compare the available products on their most important feature; if one is clearly the best product on this dimension, that’s the one we buy; otherwise we move onto the second most important feature, and so on. Collectively, these shortcuts are known as the adaptive toolbox and they are thought to have been developed by evolutionary pressures as near-optimal solutions for tricky or dangerous environments.

The third model is the modified expected utility (or subjective expected utility) approach, which says that we take a generally “rational” view of our decisions – roughly estimating our expected outcome from each option, and picking the one that seems best – but subject to some modifications or approximations such as avoidance of risk. Under this theory, we mostly avoid risky options, those which might lead to a negative outcome or those whose outcomes are ambiguous, and therefore act in a relatively conservative way. The prospect theory model of Kahneman and Tversky is an example of this approach.

Other models include decision field theory (Busemeyer and Townsend), which says that we gradually “drift” towards a decision as we randomly consider various aspects of the different options available to us; decision by sampling (Neil Stewart), which suggests we compare options with randomly selected experiences from memory and see whether they appear to be better or worse than those memories; and ACT-R (John Anderson), which is less a theory of decision processes than a model of the structure of the mind, and is often used to simulate various different decision approaches and find which best matches the behaviour of real individuals.

Sometimes “theories” that we hear about, such as “nudge theory” are not general theories as such, but collections of techniques for influencing decisions. Nudge theory, as well as most of the experimental observations of behavioural economics, is compatible with several of the above models.

Any of the above frameworks can be used to understand more about how your respondents make decisions either in a real purchase context or during your research process. However, instead of a list of dozens of cognitive biases, you now have several competing decision making frameworks to choose between – a partial improvement but still no clear answer. So in future posts, I’ll suggest ways to unify these into a practical approach you may be able to use in your daily work.

Leigh Caldwell is a consultant and writer on pricing and cognitive economics and partner at The Irrational Agency