Social class
Social class is another important segmentation variable. As we saw in Chapter 3, social class groupings are based primarily on occupation. However, people who hold similar occupations may have very dissimilar lifestyles, values and purchasing patterns. Nevertheless, research has found that social class has proved to be useful in discriminating between owning a dishwasher, having central heating and privatization share ownership, for example, and therefore should not be discounted as a segmentation variable. In addition, social classes tend to vary in their media consumption, meaning that these groups can be targeted effectively by advertisers. For example, tabloid newspapers tend to target working-class people, whereas traditional broadsheets see the middle and upper classes as their primary audience.
Geography
A
t
a very basic level, markets can be segmented on the basis of country,
regions within a country or on the basis of city size. More popular
in recent years has been the combination of geographic and
demographic variables into what are called geodemographics.
In
countries that produce population census data, the potential exists
for classifying consumers on the combined basis of location and
certain demographic (and socio-economic) information. Households are
classified into groups according to a wide range of factors depending
on what is asked on census returns. In the UK, variables such as
household size, number of cars, occupation, family size and ethnic
background are used to group small geographic areas (known as
enumeration districts) into segments that share similar
characteristics. Several companies produce analyses of this
information, for example Experian, but the best known is that
produced by CACI Market Analysis entitled ACORN (from its full title-
A Classification of Residential Neighbourhoods). The main ACORN
groupings and their characteristics are shown in Table 5.2.
Geodemographic information, like that in the ACORN groupings, has been used to select recipients of direct mail campaigns, to identify the best locations for stores and to find the best poster sites. This is possible because consumers in each group can be identified by means of their postcodes. Another area where census data are employed is in buying advertising spots on television. Agencies depend on information from viewership panels, which record their viewing habits so that advertisers can get an insight into who watches what. In the UK, census analyses are combined with viewership data via the postcodes of panelists. This means that advertisers who wish to reach a particular geodemographic group can discover the type of programme they prefer to watch and buy television spots accordingly.
A major strength of geodemographics is that it can link buyer behaviour to customer groups. Buying habits can be determined by means of large-scale syndicated surveys - for example, the TGI and MORI Financial Services- or from panel data (for example, the grocery and toiletries markets are covered by AGB's Superpanel). By 'geocoding' respondents, those ACORN groups most likely to purchase a product or brand can he determined. This can be useful for branch location since many service providers use a country-wide branch network and need to match the market segments to which they most appeal to the type of customer in their catchment area. The merchandise mix decisions of retailers can also be affected by customer profile data. Media selections can be made more precise by linking buying habits to geodemographic data.
In short, a wide range of variables can be used to segment consumer markets. Flexibility and creativity are the hallmarks of effective segmentation analysis. Often, a combination of variables will be used to identify groups of consumers that respond in the same way to marketing mix strategies. An example of a study that used a combination of variables to segment a market is given in e-Marketing 5.1. Variables such as age, socio-economic group, gender and lifestyle were used to segment users of the Internet.