Retailing 793
premium position. For fashion and other
design-led retailers, the ability to co-ordinate
aspects of product and store design is another
significant motive.
The implications for manufacturers, how-
ever, have been serious, with retailers able to
switch sources of own brands, if prices or
specifications cannot be agreed. Some manu-
facturers have learnt to coexist as largely
anonymous suppliers of major retailers, freed
of most marketing expenditures but with
extreme dependence upon the retailer(s). Some
major brand manufacturers such as Heinz,
along with Kellogg’s, held out for many years
against producing retailers’ own brands; how-
ever, Heinz now adopts a ‘mixed branding’
policy. This has the advantages of maximizing
plant utilization and maintaining influence, if
not control, over product differentiation. The
old adage ‘if you can’t beat them, join them’
also holds true.
The evolution of own brands has
demanded the development of skills in design
and product testing, previously in the domain
of the manufacturer. Leading grocers now
employ large teams of food scientists to help
develop, specify and test product character-
istics. Consumer tests are also of critical impor-
tance, to ensure that the effect on image is the
right direction. Retailers must also monitor
possible consumer resistance to own brands, if
their predominance in displays is creating the
impression of a restriction of choice.
Retail pricing
One of the most complex areas of retail decision
making is that of pricing. Whereas a manu-
facturer may have 50–100 items to price, a
superstore or department store retailer may be
responsible for 1000 times more SKUs (stock-
keeping units). Added to this complexity is the
fact that chain store retailers operate in many
different geographical markets. Figure 30.8
summarizes the main dimensions of retail
pricing: developments within each are con-
sidered briefly.
The ‘comparative dimension’ represents
the many differences in price between those of
the retailer and those of direct and indirect,
local and national competitors. This comprises
a vast number of price comparisons, far more
than can be collected to inform each pricing
decision. The information industry has respon-
ded with a range of pricing data, some compris-
ing a pooling of retailers’ own scanner data,
others deriving information from the purchase
records of large panels of consumers. In some
sectors, such as clothing retailing, much com-
parative data on prices and markdowns are still
obtained by auditors visiting a sample of stores
at regular intervals. Many retailers price differ-
ent parts of their range to compete for different
market segments, so the positioning may vary
according to the product prices that are
compared.
The ‘geographical dimension’ reflects the
fact that all retailing is local retailing, for chain
stores and independents alike. Many chains
that initially charged uniform prices in all their
locations have shifted progressively towards
greater local adaptation, reflecting better the
local market conditions. Some use relatively
crude stratifications of locations, others now try
to tailor more precisely their product/price mix
to each locality. Again, the external information
from GIS, combined with internal EPoS data at
store level, provide the basis for cost-effective
local pricing, referred to as ‘price flexing’ by the
Competition Commission (2000).
The ‘assortment’ dimension of retail pric-
ing concerns the thousands of decisions
between prices of categories and items within
the range. Decisions based upon crude mark-
up rules are giving way to more intricate
approaches, information again being the cata-
lyst. EPoS provides great scope to experiment
with price, controlling the inputs (prices) and
monitoring the outputs (sales) precisely. Assort-
ment pricing decisions should also be informed
by research into consumers’ awareness of items
prices (McGoldrick et al., 2000). Through this
type of research, the ‘leader line’ pricing tech-
nique was evolved. Within this approach, the