Positioning & Partitioning – A Replication & Extension
Anne Sharp, Byron Sharp and Natalie Redford
University of South Australia
Track 17 Continuation of the work of Ehrenberg and Bass
Abstract
The mainstream marketing literature accepts the existence of distinctive brand images which
position brands closer to some competitors than others. The closer two brands are perceived
to be positioned within a market, the more directly these brands are thought to compete, with
each sharing the same customer base. Initial empirical investigation of this issue has been
conducted in the context of department store shopping. The results indicated that perceptual
differences are not mirrored in patterns of sharing customers between brands. In this
instance, behaviours appeared to be driven more by physical location than image closeness.
This paper further builds on the empirical investigation, this time through examining a
context where location issues are controlled for. A chilled, non-alcoholic beverage market is
examined, where the range of brands was available in the majority of stores, but some
functional and perceptual differences did exist. Both customer perceptual data and
duplication of purchase data for the key brands in the market were examined. Comparisons
were made between a brand’s image positioning and any market partitioning in terms of
purchase patterns. Again, the results provide little evidence of the impact of brand image
differences on purchase behaviour. Rather, market partitions appear to be based on functional
differences between brands. This research provides further support for the initial findings in
this area.
The Purpose of this Study
The concept of brand image is one that is closely tied to differentiation. It is commonly
assumed that brands that share similar brand images are less differentiated from each other
than they are from other brands. The creation and maintenance of brand image is thus of
strategic importance, being a crucial aspect of a firm’s competitive strategy. Company
failures and great financial losses have been ascribed as consequences of getting a company’s
image positioning wrong (see Ries and Trout, 1986).
This idea of image-based differentiation states that, since brands differ in their positioning, so
too will consumers differ in their individual brand choice (Bass, Givon et al. 1984).
However, the idea of image differentiation leading to differences in a brand’s customer base
does not appear to be founded on a body of supporting empirical evidence. Andrew
Ehrenberg (1988) has been one of the few critics of the brand image concept arguing that,
since the observed differences between brands’ behavioural loyalty levels are systematically
linked to market share differentials, there is little evidence of the impact of distinctive brand
images (i.e. there are only smaller brands and bigger brands). In addition, an extensive
analysis of purchase data across varied consumer goods categories and multiple countries,
found that similar and dissimilar competitive brands are bought by much the same kinds of
customers (Hammond, Ehrenberg et al. 1996; Kennedy, Ehrenberg et al. 2000). That is, there
is no strong evidence of market segmentation between competitive brands, at least in the
consumer goods area. This does not, however, address the issue of market partitioning.
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While two brands may have customers that have common demographic characteristics (i.e.
belong to the same demographic segment) the brands may still be in different sub-markets of
the category. Work looking at market structure has indeed found that such market
partitioning exists (Rubinson, Vanhonacker et al. 1980; Grover and Srinivasan 1987) though
it tends to be due to major functional differences in product features/function rather than
image positioning (Uncles, Ehrenberg et al. 1995).
This paper sets out to further investigate this issue of brand image differences being mirrored
in brand usage patterns.
Methodology
The chosen category was iced coffee flavoured milk – a very popular category in the market
under study. There were five major brands produced by two companies. The brands (and
companies)- were: Farmers Union (Farmers Union), Dairy Vale (Dairy Vale), Max (Dairy
Vale), Feel Good (Farmers Union), and Take Care (Dairy Vale). These constituted the major
iced coffee brands in the market, with each having enough market share to be considered a
serious player. It was also widely thought that there was a fair deal of differentiation between
the 'brands' in this category, as reflected in their differing advertising.
The perceptual and behavioural data was collected from the same population of respondents
(people who drank iced coffee in the last month). This allowed for direct comparison of
perceptual data with behavioural data and removed sampling error. The behavioural data was
derived from 18 weeks of repeat-purchase data, collected through a panel of 247 respondents.
Data was collected on the purchasing behaviour of the different brands and purchase
frequency. This data included every purchase occasion and record of brands purchased.
Respondents were posted diaries in which to record their purchase behaviour. This data was
collected via weekly telephone interviews conducted by Interviewer Quality Control of
Australia (IQCA) accredited interviewers.
The panel data was used to look for any partitioning in behaviour, through examining
duplication of purchase between brands. That is, what proportion of buyers of brand ‘X’ are
also buyers of brand ‘Y’. Duplication of purchase statistics for each brand were compared to
the average level of duplication in the category and to the known empirical generalisation
derived from the ‘Duplication of Purchase Law’. Deviations from these benchmarks indicate
market partitioning.
Perceptual mapping and the construction of a brand image maps using Correspondence
Analysis were used to examine the level of image-differentiation. Free association was used
with consumers to identify relevant brand image attributes for the category and brands. The
particular association technique adopted was successive word association, where the
respondent is asked to list all words or thoughts that occur after being exposed to the given
cue. This was done with a convenience sample of 30 people.
Respondents were asked which attributes they associated with each brand using the "pick
any" method that has been shown to produce image scores in line with other scale-type
measures (Barnard and Ehrenberg 1990; Driesener and Romaniuk 2002).
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Table 1: Image attributes for brands
a fattening brand
appeals to men
a working class brand
a rich/sweet brand
a XXX (local area) brand
a traditional/old fashioned
brand
an unpopular brand
a brand for fat/ugly people
a premium quality brand
a healthy brand
very fresh
a brand for yuppies
a high caffeine brand
a new brand
a nutritious brand
a brand for women
a brand for beautiful people
a tough brand
a low fat/calorie brand
a brand for children
a popular brand
a good hangover cure
a minor brand
The perceptual data was then compared with behavioural data on duplication of purchase
between brands. The greater duplication of purchase levels should occur between brands that
have similar ‘positions’ in the consumers’ minds, if brand image and purchase behaviour are
linked.
Results: The Mapping of Brand Images
The correspondence map displayed excellent association between capturing the totality of the
data and a two dimensional plot (goodnesss of fit = 0.83). A CGS plot (see Carroll, Green et
al. 1987) rather than a French plot was also used in this analysis for ease of visual
interpretation. Also informed commentators felt the map validly captured the brands image
positioning which was underpinned by some functional differences.
tough
men
Max
low fat
healthy
working class
new
FG
TC
nutritious
minor brand
women
beautiful people
unpopular
hangover cure
hi caffeine
FU
ugly people
fresh
popular
yuppie brand
fattening
Sth Australian
DV
childrens brand
traditional
premium brand
sweet
Figure 1: Perceptual map of iced coffee brands
The perceptual map suggests three partitions in the market; Take Care and Feel Good plot
close together near the dimension of healthy, low fat and female oriented. Indeed these two
brands are the two low-fat milk iced coffees on the market. On this functional aspect, they
are highly differentiated from the other brands.
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The second partition sees Max clearly positioned as a brand for working class males and
being a high caffeine coffee. Farmers Union is closest to Max, and is seen as ‘popular’ and is
indeed the brand leader. However, it really stands on its own, not positioned on any definitive
image aspect apart from being the most popular. And when the popular/unpopular variables
are removed from the analysis there is no change in the Farmers Union position relative to
other brands. Again we would draw the conclusion that Farmers Union is seen as the
epitome of iced coffee rather than a brand positioned for any distinctive part of the market.
Dairy Vale is positioned near the premium/traditional axis and near ‘sweeter’.
Results: Duplication of Purchase Patterns
In order to see if partitioning is occurring in the industry, it is necessary to know what levels
of brand duplication should be normally expected for each brand in each industry, given its
level of market share. These benchmarks are provided by the Duplication of Purchase Law
and are captured within the Dirichlet model of repeat-purchase patterns (Goodhardt,
Ehrenberg et al. 1984; Ehrenberg 1988; Uncles, Ehrenberg et al. 1995). The Dirichlet is
widely supported, having been tested for over 30 years and across European, US, Asian and
Australasian markets (Uncles, Ehrenberg et al. 1995)
The dominant factor in such purchase duplications is simply each brand’s penetration. This
relationship with the overall brand penetrations is called the Duplication of Purchase Law.
This law says that the proportion of customers of brand X who also buy brand Y is
proportional to brand Y’s penetration in the population as a whole. Calculating the
duplication coefficient D as Av.Duplication/Av.Penetration is a simplification but one which
works well in practice, at least for brands with penetration less than 50%, which is true for all
brands in this market.
bx
y
≈ Db x
Where b is the brand’s penetration and D is the Duplication of Purchase coefficient
Some clusters of brands or “submarkets” with higher duplications can also arise (Ehrenberg,
Uncles et al. 2003 (forthcoming)), these are revealed as deviations from the Duplication of
Purchase Law. This phenomenon is called market partitioning.
Table 2 summarises the duplication patterns seen between the brands. The way the data is
presented makes it easy to see particularly high or low duplications between pairs of brands
(Goodhardt 1972). The diagonal element of the table should constitute 100% in each cell buyers of Brand A also buying Brand A. The table is best interpreted by reading down each
column.
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Table 2: Duplication of Purchase
% ever
bought
% who then bought
Farmers
Union
Buyers of…
Dairy Vale
Take Care
Max
Feel Good
21
8
6
5
5
5
5
0
20
Farmers Union
31
Dairy Vale
15
43
Take Care
5
52
16
Max
4
45
20
0
Feel Good
3
53
27
33
0
Average
12
48
21
12
3
8
Expected. Dupe
49
24
8
6
5
MAD
-1
-3
4
-3
3
0
From Table 2, we can see that the top three brands share their customers the most, as would
be expected. As an example of how to read the table, 21% of people who purchased Farmers
Union, also purchased Dairy Vale and 43% of Dairy Vale purchasers also purchased Farmers
Union. This is the expected pattern, that big brands (in this case Farmers Union) share their
customers less (ie have lower DoPs) than smaller brands (in this case Dairy Vale).
The table reveals that most deviations from the average DoP are minor, as shown by the Mean
Average Deviation, with the exception of Feel Good and Take Care. These two brands have
deviations from the expected duplications of +15 and +25 respectively. Clearly, these two
brands are sharing their customers to a far greater degree than predicted by the Duplication of
Purchase law. This partition can be best ascribed to not just perceptual similarities between
the brands, but also their real functional differences. Both these brands are the only low fat
(diet) iced coffee brands with no sugar on the market. It appears to be this functional
difference that is driving the partition, rather than just the brands’ perceptual similarities.
Interestingly, brands that are positioned perceptually further apart, such as Max and Dairy
Vale, do not share their customers to a markedly less extent than expected. This would again
support the idea that functional differences, rather than perceptual ones, drive the deviations
from expected DoP patterns.
Overall then, the major pattern shown by the DoP table reveals that repeat-buying is largely
due to how big the brand is (market share), rather than a particular positioning of the brand.
Any partitions are due to major functional differences between brands as found by Uncles
Ehrenberg et al (1995).
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Conclusion
The results of this study provide further empirical evidence that perceptual differences
between brands do not automatically translate into differences in buying behaviour.
However, brands that are positioned closely together and that have functional differences
from the other brands in the market, do appear to have higher sharing of customers than
predicted by the Duplication of Purchase law. More replication is needed to see if instances
can be found where perceptual differences alone are enough to cause such deviations.
References
Barnard, N. R. and A. S. C. Ehrenberg (1990). "Robust Measures of Consumer Brand
Beliefs." Journal of Marketing Research 27(November): 477-4874.
Bass, F. M., M. M. Givon, et al. (1984). "An Investigation Into the Order of the Brand Choice
Process." Marketing Science 3(4, Fall): 267-287.
Carroll, J. D., P. E. Green, et al. (1987). "Comparing Interpoint Distances in Correspondence
Analysis: A Clarification." Journal of Marketing Research 24(November): 445-450.
Driesener, C. and J. Romaniuk (2002). A Comparison of Perceptual Mapping using Ranking,
Rating and Pick any Technique. ANZMAC, Mebourne.
Ehrenberg, A. S. C. (1988). Repeat-buying: facts, theory and applications. London, Oxford
University Press.
Ehrenberg, A. S. C., M. D. Uncles, et al. (2003 (forthcoming)). "Understanding Brand
Performance Measures: Using Dirichlet Benchmarks." Journal of Business Research.
Goodhardt, G. J. (1972). Loyalty Reports - A Coded Example. ESOMAR Seminar "Panels",
Amsterdam, The Netherlands, European Society for Opinion and Marketing Research.
Goodhardt, G. J., A. S. C. Ehrenberg, et al. (1984). "The Dirichlet: A Comprehensive Model
of Buying Behaviour." Journal of the Royal Statistical Society 147(part 5): 621-655.
Grover, R. and V. Srinivasan (1987). "A Simultaneous Approach to Market Segmentation and
Market Structuring." Journal of Marketing Research 24(May): 139-153.
Hammond, K., A. S. C. Ehrenberg, et al. (1996). "Market Segmentation for Competitive
Brands." European Journal of Marketing 30(No. 12): 39-49.
Kennedy, R., A. Ehrenberg, et al. (2000). Competitive Brands' User-Profiles Hardly Differ.
Market Research Society Conference (UK), Brighton, England, Market Research Society
(UK).
Ries, A. and J. Trout (1986). Positioning: The Battle for Your Mind. New York, McGraw
Hill Inc.
2551
Rubinson, J. R., W. R. Vanhonacker, et al. (1980). "On 'A Parsimonious Description of the
Hendry System'." Management Science 26(2, February): 215-226.
Uncles, M., A. Ehrenberg, et al. (1995). "Patterns of Buyer Behavior: Regularities, Models,
and Extensions." Marketing Science 14(No. 3, Part 2 of 2): G61-G70.
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