If you’ve been visiting my site regularly you’ve no doubt come across the word ‘psychographics’ a few times. Not everyone is familiar with this term, so to save myself (and you) from having to explain the word every time I use it I’ve added this reference page.
What are psychographics?
To describe the characteristics of a particular group we’re used to the idea of using demographic data such as age, gender, education level or location. This information helps us to give the group some defining features that allow us to compare it to other groups, to work out if other people or populations are part of the group or to focus marketing activities on the right people.
For example: the group ‘night clubbers’ has the demographic characteristics of being mostly under 25, evenly split between males and females and mostly single.
In this case we’ve identified a particular group based on a known behaviour (going to night clubs) and made some generalisations about the typical demographic characteristics of the group as a whole.
But demographic data can also be used to segment a particular group into subgroups to help us understand variations in behaviour or outcomes within the larger group. This can be done in a number of ways, including simply splitting the group in terms of one variable (for example, into male and female night clubbers) or by using statistical techniques to look for clusters of demographic factors that, when they occur together, tend to correspond to a certain ‘target’ behaviour or other variable of interest to the researcher.
So, let’s say we want to split the night clubbers group into segments that correspond to their scores on a variable about how often they go clubbing. Using a statistical cluster analysis we can find out how the main group can be segmented into subgroups made up of people that tend to frequent nightclubs at a similar regularity. So it might turn out that the subgroup that goes clubbing 2-3 times per week are best defined as predominantly female, low income students, and under the age of 23; the group who go less than once per month might turn out to be predominantly male, high income and over the age of 30.
Demographics can be an excellent way of describing and segmenting populations, but because they only look at relatively objective factors they can miss out on a lot of rich and important detail about what makes people tick. It’s all very well saying people under 40 are more likely to buy an ipod than those over 40, but surely we’d have a much better predictor of purchase if we split a group by factors like whether or not they are big music fans or technophobes (for which age might be an imperfect proxy). This is where psychographics comes in.
Psychographics takes the study of groups into new areas: interests, attitudes, opinions, motivations, values, personality and lifestyle choices. It enables us to describe and segment populations by the way they think rather than by demographic factors, which is often very useful to market researchers looking to develop a detailed picture of existing or potential customers.
A simple example of a psychographic segmentation is a political opinion poll. Here a population is divided up according to an opinion or intention: who will you vote for?
In combination, psychographics and demographics can provide a powerful way of defining groups and predicting behaviour. In my research I am using both types of data to help create a set of profiles of different types of runner based on their relationship to the sport. Each profile will have a different combination of factors (e.g. values, attitudes, motivations, age, gender, socioeconomic status) that correspond to – and help explain – the ways they practice their sport.