The Geography of
Brands
New Insights into the Local
Performance of Nationally
Distributed Brands
Research by
Sanjay K. Dhar and Jean-Pierre Dube
Sanjay K. Dhar is James H. Lorie Professor of
Marketing at the University of Chicago Graduate
School of Business.
Jean-Pierre Dube is professor of marketing and
Neubauer Family Faculty Fellow at the University of
Chicago Graduate School of Business.
Marketing research on the consumer packaged goods industry has traditionally focused on
how brands perform over time in a small number of geographic markets. New research
suggests that analyzing brand performance across markets�rather than simply over
time� may be a more fruitful approach.
In the consumer packaged goods (CPG) industry, the most widely used measure of brand
performance is brand market share�the unit sales of a brand divided by the unit sales of the
entire category.
Most research about purchase behavior and the effectiveness of marketing tools for CPG brands
is based on time-series studies, which typically use data covering a few weeks to a few years in
a particular geographic market. Until now, there has been relatively little research exploring the
geographic distribution of market shares in the CPG industry.
In the study �Consumer Packaged Goods in the United States: National Brands, Local
Branding,� University of Chicago Graduate School of Business professors Sanjay K. Dhar and
Jean-Pierre Dube, along with Bart J. Bronnenberg of UCLA, document several striking
geographic patterns in the performance of national brands using a large scanner database
spanning many CPG categories and U.S. regional markets.
The authors note that the geography of CPG industries is an understudied area with several
important potential directions for future research.
Dhar characterizes the study as descriptive research. Dube adds, �We began this study as an
exploration rather than a test. Finding a relatively large geographic component of brand shares
was surprising.�
The authors pooled market share information across time and geographic markets for the top
two leading national brands in 31 CPG categories. They find that the geographic component of
these data accounts for 92 percent of the variation in market shares. Furthermore, brand shares
appear to be stable over time within a market.
With only a few exceptions, researchers have previously been unable to collect truly long-run
information about brand performance; CPG data sources�at best�cover a couple of years in
any given market. In contrast, the geographic patterns appear to be a long-run phenomenon.
These data may present marketers with a rich new source of long-run marketing data with which
to study the long-run effects of marketing investments.
Across markets, the geographic variation in market shares, indices of brand quality perceptions,
and the identity of local brand-share leaders is so significant that it calls into question the
concept and relevance of a �national brand.� These findings also highlight problems in using
studies focusing on performance over time to determine the effectiveness of marketing tools
when the data focuses only on single markets. Since market share variation over time appears to
capture a minor component of overall variation, and it is difficult to obtain databases for long
time periods, inferences about the impact of marketing variables based on short time series of
market shares may be imprecise.
A Broad-Spectrum Approach
Dhar, Dube, and Bronnenberg used scanner data from AC Nielsen spanning 31 CPG categories
in the 50 largest Nielsendesignated Scantracks, each of which typically include a single
metropolitan area and its suburbs. The data was sampled at four-week intervals between June
1992 and May 1995. Categories spanned food products from bread and bakery to frozen
entrees/side dishes.
The authors investigated properties of CPG brand share data across brands, markets, and time,
as well as several marketing variables. They constructed a brand share measure based on
equivalent unit sales in each category/market/month. For each of the 31 categories, the data
covers two brands in 50 markets over 39 months.
The most notable feature of the market share data was the high level of geographic variation.
Regardless of the degree to which a product competed on the national level, the range and level
of variation in a brand�s share was very similar. This suggests that the high level of variation is
not simply due to brands avoiding certain markets.
After breaking down shares by time, market, and brand effects, as well as the interaction
between the market and the brand, the authors find that geographic variation explains
considerably more of the market share variance than variation across time. Furthermore, the
local market structure within a category varies considerably across geographic markets: one
brand may be very strong in one market and relatively weak in another.
What are the limitations of focusing on a single market when analyzing national brands? First,
focusing on a single market ignores the cross-market dimension in the CPG industry, and thus
does not focus on explaining the largest source of variation in the market-level performance of
national CPG brands. Second, a major goal of quantitative marketing research is to determine
the effects of a firm�s marketing investments. If variation in brand performance across markets
is related to such investments, focusing on a single market may lead to misleading estimates of
these effects.
Studying variations in market shares across markets, rather than focusing on movement over
time, may be more informative about the long-run effects of marketing investments, advertising,
and distribution. These findings may impact strategic marketing decisions regarding the product,
such as local positioning and branding.
What is the Relevance of a �National Brand�?
For brands that garnered the largest shares of a category�s national market, the authors
observed considerable regional variation in market share, perceived quality, and share
dominance. In specific Scantrack markets, the authors find a large disparity between a brand�s
national share and its local share.
The authors expanded the set of brands they studied to include all local share leaders across
categories in order to investigate whether a national brand�defined as a brand with distribution
in all 50 Scantrack markets�has inherent advantages in terms of local performance.
They find that when a national brand leads in a market, it tends to lead with 12 more market
share points than a local or regional brand. The authors did not observe meaningful inherent
national brand effects.
Can the national performance of a brand predict how the brand will perform in local markets?
The authors suggest that a single geographic market provides only limited information about a
brand�s overall performance. Furthermore, within local markets, there is a stronger tendency
for one brand to dominate in terms of shares.
Focusing on either the national market or a single geographic market may not only limit the
information about a brand�s performance, it also may limit the information about the category
as a whole. For example, while the national market for coffee appears to be dominated by two
firms, in most local markets there is one dominant firm.
In addition to scanner data, the authors used information on perceived brand quality collected by
Young and Rubicam Associates for its Brand Asset Valuator Database to study geographic
patterns in quality perceptions of the same brand. The quality perception data showed
comparable levels of variation as the market share data. The clear lack of consistent quality
perception across markets further erodes the concept of a national brand.
The authors suggest that future research could benefit from a better theoretical and empirical
understanding of the sources of these local share differences.
Future Research
�The purpose of our study is not to provide answers, but rather to suggest several potential
directions for new research based on descriptive findings,� says Dhar.
Dhar, Dube, and Bronnenberg write, �Insofar as geography leads to different conclusions
regarding the effectiveness of marketing variables, it could suggest that we still have much to
learn.�
In a follow-up study, �Market Structure and the Geographic Distribution of Brand Shares in
Consumer Package Goods Industries,� Dhar, Dube, and Bronnenberg explore some of the
potential underlying economic forces related to branding and brand advertising that generated
these striking patterns. They utilize the geographic data to document a strong relationship
between market shares and advertising across geographic areas. This finding challenges the
results of prior research�based on single-market time series data�that routinely provided
results favoring promotional tactics, such as price-cutting, over advertising strategies.
In the geographic dimension, the authors find very little correlation between promotional
activity and brand market shares, suggesting that promotions only have short-term effects.
Advertising appears to have longer-lasting effects, possibly through its ability to build a lasting
brand �goodwill� stock and to bolster brand perceptions within a market.
In two industries, ground coffee and mayonnaise, the authors also find evidence of a strong
�early-mover� effect. For the top two brands in each market, controlling for the identity of the
first entrant in each geographic market captures more than 50 percent of the geographic
variation in market shares. This result is particularly striking in the coffee category, where
brands were rolled out as early as the mid 1900s. The early-entry effect also explains a large
component of the advertising variation across markets.
In the second study, the authors also examine several alternative explanations for the underlying
sources of the geographic patterns. In particular, they look at proximity to production facilities
(i.e., potential cost advantages), relationships with large retailers, and even local parentcompany
effects. However, none of these alternative sources appears to explain the geographic variation
in brand shares.
The authors hope that future research will focus on broader marketing databases spanning wider
geographic scope and longer time horizons. Experimenting with cross-sectional geographic data
and contrasting findings with single market time-series data may be a novel way to advance
current knowledge about marketing effectiveness. Ultimately, establishing theories to
understand the patterns documented in the study should be a fruitful new research area for
quantitative marketers.