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We need to talk about averages
They help us understand markets. They don’t always help us understand people.
Averages are one of the first things we learn about in statistics and, used well, they are incredibly useful. They help us summarise information, spot patterns and make sense of complex datasets. Without them, most research would be difficult to interpret.
The trouble starts when we begin to treat them as people.
Suppose the average person drinks two cups of coffee a day. That tells us something about coffee consumption across the population, but very little about any individual. Some people rarely drink coffee, while others get through several cups before breakfast. The average is simply a summary of all those different behaviours. It helps us understand the market as a whole, but not necessarily the people within it.
We find the same challenge in consumer research. There’s plenty of talk about the average customer or the average consumer, yet the people represented by that number frequently have very different motivations, needs and ways of making decisions. The average can be a helpful description of what happened across a market, but it is rarely an explanation of why it happened.
A similar problem appears in segmentation. It can be one of the most valuable tools available to marketers and researchers, but it is surprisingly easy to mistake description for understanding. Splitting consumers into smaller groups does not necessarily bring us any closer to explaining why they make the choices they do. Sometimes, all we have done is replace one average with several smaller ones.
That is why demographic differences should usually be the beginning of the conversation rather than the end of it. Knowing that younger consumers responded more positively than older consumers is interesting, but age itself is rarely the explanation. The more useful question is what younger consumers are doing, thinking or experiencing differently that produced that result. Unless we can answer that, we have learned relatively little about how to influence future behaviour.
In many categories, what people are trying to achieve matters far more than who they are. The same person buying a bottle of wine as a gift is making a different decision from when they are choosing one for a quiet evening at home. The person has not changed, but the task has. One purchase may be about making a good impression, another about choosing something familiar and another simply about getting good value. Looking only at demographics tells us very little about these differences.
This is where good segmentation earns its keep. It is not about producing more detailed descriptions of consumers or creating colourful personas. It is about identifying differences that give an organisation the opportunity to do something differently. If recognising a segment leads us to design a better product, communicate differently, remove a barrier to purchase or improve the customer experience, then the segmentation has proved its value. If it simply predicts that one group behaves differently from another, without changing the action we take, it is worth asking how much we have really learned.
None of this means we should stop using averages or abandon segmentation. Both remain essential. Averages help us understand markets, while segmentation helps us explore the differences within them. The challenge is recognising when an average is hiding something important, when a segment is revealing something meaningful and, perhaps most importantly, whether understanding that difference gives us the opportunity to make a better decision.
Perhaps that is the question worth asking before creating another segment. Have we simply found a group of people who behave differently, or have we discovered something that genuinely changes what we do?
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