What to do with decision theories?

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This post originally appeared on RWConnect on 4th March 2014

In my last post, I explained three broad theories of human decision-making which different psychologists put forward as alternative explanations for the discoveries of behavioural economics.

decision ahead - proceed slowlyHeuristics and biases assumes that we’re basically meant to be rational but some design flaws get in the way; adaptive toolbox says that there’s no such thing as rationality, we just use a collection of ad hoc mental tools to solve problems as best we can; and information processing viewpoints propose an underlying mechanism in our minds, which act as a sort of imperfect computer to make decisions based on the information the world throws at us.

In this article I won’t try to answer which model might be better, but let’s say you’ve decided which one best fits the consumers you’re studying. What should you do next?

Each of these models gives you a way to understand how customers are making the decision to buy, or not to buy, your (or your client’s) product. Each of them also challenges the traditional, unstated, powerful assumption that most market researchers make about consumer decisions.

You may be one of the rare marketers who does not make this assumption. While others do not know they are making it. But the assumption is revealed every time a questionnaire asks a respondent how much they like something, and every time an interviewer says “Tell me why you bought that.”

What is this hidden assumption? It is this: that the decision process is based on consumers buying products that they like, because of the attributes of the product, and knowing why they do so. In other words, that it’s an economically rational process. All three parts of this assumption are disproven by behavioural economics. The three models each give an alternative description of the decision and buying process, and this process is where researchers can focus their efforts in order to make behavioural economics work for their clients.

The heuristics and biases model says that the basic economically rational process is still the right framework, but consumers make errors of judgement in deciding how much they like things. If you follow this model, you should still look at product attributes but you should also look at how they are communicated and what context they are in, because this affects the value that consumers place on them. By understanding these context effects, you can learn how to emphasise the attributes on which your client’s product is strongest, which contexts it will do best in, and how to segment consumers by their biases and contexts. A methodology for analysing this process can be based on listing product attributes, enumerating the contexts in which the product (and its competitors) will be seen, and using a cognitive biases list as a checklist for how consumers might be influenced to put a higher or lower value on each attribute.

If you use the adaptive toolbox model, you will need to instead think of how consumers might make a good-enough decision about this product category – how they will satisfy themselves that the product they are choosing is OK and meets most of their needs. There are a number of standard heuristics or rules of thumb that consumers typically take to do this. One is to pick the one most important product attribute and focus on that (this might be price, or something category-specific like miles per gallon). Another is to copy what their friends or peers are doing. A third is to do what they did last time, if there were no significant negative consequences. You can find out which rule consumers are using by observing them, asking them (in the right way!), or testing their behaviour in a controlled experiment which is designed to distinguish between these rules. When you know the rule(s) they use, you’ll know the basic parameters about how to design product communications, how to position and price the product and how to change consumer behaviour for the better.

Finally, the information processing model says that consumers make their decisions by gathering information in pursuit of a goal. To analyse this process, you would start by understanding what information the consumer already has – this both forms a baseline to ask what new information they will seek out, and influences the goals they choose to satisfy. In this model, other drives such as emotions and preferences are seen as specific types of information. Then consider the capabilities of the consumer to gather information, the sources they use, the way they interpret and combine new facts with existing knowledge, and some basic parameters like how quickly they can read and interpret information, and their rate of consumption of social or other media. You can then quantitatively and qualitatively determine which (and how many) products each consumer might consider. You can also use the same framework to estimate which contextual, product or communication factors they are most likely to focus on when making their final choice.

Whichever model you use, the tools of traditional market research can fit into it. These new frameworks give a new way to think about the consumer and how to understand them, but they do not in themselves provide new methodologies. Qualitative approaches, survey research, concept tests, panels, eye tracking, ethnography and all the rest can fit as important tools into any of the three models. However, by starting from an understanding of how the consumer thinks – informed by behavioural economics research – you’ll have a more powerful and effective way to use those tools and achieve business results for your clients.

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

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One thought on “What to do with decision theories?

  1. Because you are working with a brand, you have access to a lot of choice data.
    Out of that data, you need to reconstruct some decision rules. Rules that if you knew, would help you in marketing.
    Without imposing or finding a pattern in the data, you cannot give recommendations.

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