Demography refers to the vital and measurable statistics of a population. Demographics help to locate a target market. It is the most accessible and cost free way to identify a target market, indeed most secondary data including census data, are expressed in demographic terms. Demographics are easier to measure than other segmentation variables.
The major disadvantage of demographic segmentation is that it tends to be one dimensional and does not differentiate among brands. These variables are often used in combination to fine-tune a market segment; they are also used to form composite variables to measure such sociocultural constructs as family life cycle and social class.
Demographic variables reveal ongoing trends such as shifts in age, sex, and income distribution.
Age: Product needs often vary with consumer age; marketers have found age to be particularly useful demographic variable to distinguish segments. Many marketers have carved themselves a niche in the marketplace by concentrating on a specific age segment.
Sex: Gender has always been distinguishing segmentation variable. Women have traditionally been the main users of such products as hair coloring and cosmetics, and men the main users of tools and electronics. In recent years however, sex roles have blurred, and gender is no longer an accurate way to distinguish consumers in some product categories.
Marital Status: Traditionally the family has been the focus of most marketing efforts and for many products and services, the household continues to be the relevant consuming unit. Marketers are interested in the number and kinds of household that own and/or buy certain products.
Income, Education and Occupation: Income has long been an important variable for distinguishing market segments. Marketers usually are interested in affluent consumers. The major problem of segmenting the market on the basis of income alone is that income simply indicates the ability to pay for a product, while the actual choice may be based on personal lifestyle, taste, and values-variable which are largely determined by education and occupation. Education, occupation and income tend to be closely correlated in almost a cause-and -effect relationship. High-level occupation usually require advanced educational training.