Geography Reference
In-Depth Information
'struggling'. Thus all the shaded postal districts
are characterised as having the greatest
percentage of their populations within this
category. The map shows the cluster of such
postal areas surrounding the city centre (the
inner city) and a skewed pattern to the south and
east, which reflects the location of outer council
estates. Figure 42.2 shows the location of Kwik
Save stores and its market share within these
postal districts. Although there is not a direct
match between the patterns shown in Figure
42.1 and 42.2, Kwik Save seems to be well
represented in many areas of 'struggling' Leeds
(it is also represented in some of the more distant
suburban areas, where it has identified
geographical market gaps). However, within the
core cluster of 'struggling' Leeds, there does seem
to be a gap in Kwik Save's distribution network
to the south of the city centre. We will examine
the use of GIS to predict the impact of a new
store in this locality below.
Figure 42.3, by contrast, maps the distribution
of the most affluent 'GB Profiles' geodemographic
group in Leeds labelled 'prosperous'. Here we can
see a cluster of postal districts in the northern and
THE USE OF GEODEMOGRAPHICS AND
MODELS IN GROCERY RETAILING
Having discussed the basic principles of
geodemographics and spatial models, the aim in
this section is now to show how they can be
applied. The grocery sector will be used to
illustrate these techniques (see other illustrations
in Birkin
et al
. 1996). First, we will examine the
use of geodemographics and GIS in more detail.
In the previous section, we introduced the
idea that retailers such as Kwik Save, Aldi and
Netto would be most likely to target less affluent,
less mobile customers. Sainsbury and Tesco, on
the other hand, would be most likely to target
the more affluent consumer groups. In terms of
the ACORN classification shown in Table 42.2,
therefore, Kwik Save might target the 'striving',
while Sainsbury would look for areas containing
'thriving' residents. In the following example, we
draw upon a different geodemographic package,
a system called 'GB Profiles' developed at the
University of Leeds. Figure 42.1 maps the
distribution of postal districts in Leeds that have
been assigned the lowest affluence category,
Figure 42.1
Location of
'struggling' residents of
Leeds.
Source:
GB Profiles, School of
Geography, University of Leeds.
