Consumer products are often viewed as
combinations of components drawn from categories such
as features, benefits, and imageries. Successful marketing
of brands depends on skill in choosing these combinations.
The staggering number of combinations that can result
from even a relatively small number of components is not
always appreciated. For example, with only 60 components
in these combinations, there are over a quintillion (1018) of
them - if there was one penny for every combination, the
pennies would cover the surface of the earth twice if laid
out side by side! Nevertheless, there are techniques available
to consider these astronomically large numbers of
alternative combinations to find the single best combination
or a small group of actionable alternatives.
Although regression-based techniques such as conjoint
analysis are useful in situations where the numbers of
components are relatively small, such tools are not well-suited
to handling problems of the larger type described
above. Fortunately, these problems can be analyzed using
techniques from the mathematical field of graph theory.
Graph theory has grown substantially because of its applications
to internet search, social networking, and national
security. The purpose of this report is to demonstrate the
use of graph theory to optimize products built around sparkling
fruit juice beverages.
This technical report appears as:
Ennis, D. M. and Ennis, J. M. (2013). How to Find Optimal Combinations of Brand Components. IFPress, 16(4) 3-4.
Download this technical report here:
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