3.1 Common Methods of Segmentation: Behavioral, Demographic, Psychographic
Behavioral Segmentation
Behavioral segmentation aims to group consumers based on their actions, which are far easier to track in the digital age than ever before.
A common type of behavioral segmentation involves the use of Recency, Frequency, Monetary (RFM) variables. Such a model can separate customers into various groups, based on how recently they have made a purchase from the company, how often they have purchased within some designated timeframe, and how much they have spent in total across that period.
Some customers may visit a company’s website often, but only rarely make purchases. Others may be characterized as “infrequent but decisive” – they do not visit the page often, but when they do, they quickly make a purchase. Others may tend to make large purchases near the start of a month, but never at other times. In each of these cases, a company may find that tailored marketing messages are an effective way to reach these groups.
Demographic Segmentation
Demographic variables can include features such as age, gender, ethnicity, location, education level, marital status, and region.
The logic of demographic segmentation is that consumers grouped by some of the aforementioned variables are likely to have interests and tastes that align with those of other members of their groups.
For instance, highly-educated women in their 40s, living in the Northeastern part of the United States, are unlikely to chew tobacco. A company selling chewing tobacco may, therefore, decide to completely ignore this demographic group, focusing its energy and marketing spend on other groups more likely to use the product.
The first type of clustering algorithm that we will explore in this chapter is k-means, for which only numeric variables can be used in the modeling process. However, there are other methods for segmentation that enable the use of categorical variables as inputs.
Psychographic Segmentation
Psychographic differences among consumers are related to consumers’ belief systems and perceptions of themselves.
For instance, some people place considerable importance on buying “green” or eco-friendly products. This self-image could impact their purchase decisions as well as their consumption habits.
Other consumers may perceive themselves to be serious athletes. Marketers can appeal to this by offering products like “high performance t-shirts” or drinks that promise rapid recovery after grueling workouts. What, exactly, qualifies a t-shirt as “high performance?” And what suggests that one combination of water, sugar, and B vitamins is better than another as a post-workout elixir?
Psychographic distinctions can sometimes be assessed via purchase history (e.g. does this person belong to a gym and purchase Lululemon yoga pants?) or via surveys (e.g. how much importance do you place on sustainable product packaging, on a scale from 1 to 5)?
Marketing messages frequently appeal to consumers’ aspirations and self-images, whether subtly or overtly. When messages appeal to the faster, stronger, nobler, healthier, and wealthier versions of our current selves, they tend to resonate well – as they should!