What is demographic segmentation?
This approach to segmentation is dividing the market into segments based upon demographic variables, such as age, gender, life stage, family size, income, and so on.
Demographics are observable characteristics of the population, often collected on a regular basis for a government census.
Why use demographic segmentation?
There are several advantages in using demographic variables for segmentation purposes, these include:
- It is generally easily available through government sources
- It is quite low cost or sometimes free to attain
- The data may cover the entire population, especially if it has been obtained through government census
- The final segment design is quite clear to staff – people can easily understand what a young family segment looks like, but may have some difficulty visualizing psychographic segments
- Demographic segmentation is helpful in a retail environment, as the target market can be easily identified from sight – or can be easily identified through a couple of questions in a call center environment
As a result of these above factors, demographic segmentation is often used in business practice.
Why NOT use demographic segmentation?
Demographic segmentation is often considered to be a weaker approach to understanding the target market. This is because the underlying assumption with demographic segmentation is that people within the same population characteristics will share similar needs.
This will hold true for some products/markets but is unlikely to be applicable across a broad range of markets.
For example, while people in their late teens and early 20s tend to be heavy users of universities and colleges (that is, the prime target market), their needs education and social needs differ on campus.
In this example, there would be some students who prefer to attend classes and actively engage in discussions, whereas there are other students who prefer to study from textbooks and online.
Indeed, even at a broader sense, there are students pursuing studies for a specific career, others looking for general education and skills, and even others who are mainly at university for the social and lifestyle elements.
This means that with demographic segmentation we get a clear description of the segment, but it is often too broad and lacks insight to clearly identify their core underlying needs.
This limitation of demographic segmentation has been known for a considerable period of time, according to Hayley (1968) “A number of studies have revealed that demographic variables such as age, sex, income and occupation are poor predictors of behavior, and as such are of limited value in the formulation of market segmentation studies.”
How to use demographic variables?
However, psychographic and/or behavioral and/or benefit segmentation would generally be the preferred approach in a business environment, supported by demographic variables to help describe the final segments.
Key demographic variables
Gender segmentation is widely used in areas of fashion and clothing, cosmetics and beauty products, health services, and even some food and beverage items. This is because many cultures have distinct differences between gender roles, which necessitate the purchase of different items.
This would be most easily observable in the areas of fashion, where retailers have men’s and women’s sections with an array of different merchandise on offer. The same would apply in beauty and toiletry products, where there would be separate product offerings by gender.
Age segmentation is a very commonly use demographic variable, which has the underlying premise that needs change over time for all consumers.
As shown in the following diagram, age segmentation relies upon people in the same age group having similar needs.
In this example for a fitness center, younger people are more focused on the benefit of physical appearance, middle-aged people are more focused on stress relief or a break from their busy lives, and older people are there for health and therapy benefits.
Therefore, a fitness facility that has defined its target market based on an age group segmentation, would then rely upon the benefits listed in the diagram to help design their marketing mix.
Life stage, or family life cycle stage, is another demographic variable that can be used. It assumes that people go through a series of predictable life stages.
Let’s take the family life cycle as an example, typically people will progress through the following stages:
- Young single
- Young married = no children
- Married = young children = full nest 1
- Married = older children = full nest 2
- Older married = children left home = empty nest
- Older single (sole survivor)
In some countries, the above family life cycle represents a very traditional approach. Obviously in today’s more diverse world with de facto relationships, multiple marriages, blended families, same-sex couples, and so on – this progression of family life stage is certainly not as common and structures as it has been on the past.
However, there is an underlying that as the person progresses into different life stages, they have needs for new products. Clearly, the addition of children into the household creates the need for a lot of new products, such as food, health, furniture, clothing for children.
Likewise, moving from a single person into a married relationship changes the purchasing dynamics for both parties.
Another demographic variable is effective in some industries is income segmentation, where consumers are classified on the basis of high, medium and low income.
Income levels clearly change the ability of the person to afford certain products, as well as generating the needy in some consumers to demonstrate their success and lifestyle visibly through conspicuous consumption.
Again however, like with the other demographic variables, there is an implied difference in needs at different income levels, which may not hold true across the segments.
For example, a young single person and an older retired person may be classified to the same income segment, but it is likely that their needs are quite different.