What is the purpose of customer insight research? From its definition, insight means trying to apprehend the true nature of a thing, especially through intuitive understanding. It is this intuitive understanding that demands multiple methods to produce good insights, which, typically, say more about the target than about the product or service; more about the category than the brand; and reveal more about how people feel than what they think.
As part of revealing them, typically there are three stages that research goes through: namely, describing, explaining and predicting. Or, to put it another way, what has happened in the past, why is it happening in the present, and when will it happen again?
In the past, customer research would usually start with an observation that A positively affects B, so we conclude that we will need to do more of A if we want more of B. While there is merit in exploring how strong this effect might be and how much it costs to increase B by improving A, which gives us cost-effectiveness, it leaves other insight questions unanswered. The "who" and "what" questions don't tell us "why" and "what if", which is where real customer insight comes from.
At present, there is more focus placed on understanding why A affects B. For example, by using psychologist Daniel Kahneman's ideas about the predominance of "System One" thinking in humans, which is highly sensitive to environmental cues and signs of danger, simplifies to jump to conclusions and is subject to irrational bias, we can begin to answer this question.
Triangulation, which suggests that you need to use at least three different but complementary methods to best understand any customer behaviour, helps in this process. The complementary multi-methods might be accompanied shopping, interviews and questionnaires, because any measurement method has its strengths and weaknesses.
But why focus on the why? Well, if we understand why A affects B, that explanation can be used for other phenomenon and situations, and how generalisable and predictable the effect is likely to be. There is, in fact, a journal dedicated to this, called Empirical Generalizations in Marketing.
In the prediction of behaviour, marketing will become more complicated, predicting more unique treatments across multiple touchpoints over sequential waves of campaign activity. Real-time experience tracking enables companies to assess and respond - in real time - to customers' reactions to branding campaigns and promotions, as well as purchasing of products. It can also play a central role in allowing customers to help design their own experiences. With multiple insight methodologies, which look at what, why and when it will happen again, we are nearly in a position not only to describe and explain, but also to predict customer behaviour accurately.
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