Baby Boomer Segmentation:

Windshield vs. rear-view mirror
The C.O.D.E. methodology puts marketers in the driver’s
seat, steering brands and products by looking through the
windshield instead of the rear-view mirror. This approach
focuses action on stores that show growth opportunity, and
suggests maintenance level support for those with lower
growth potential.
Execution opportunity gaps materialize based on the yinyang
interaction of two opposing forces: demand drivers
and demand inhibitors. Demand drivers include activities
such as promotions, cross merchandising and correct shelving.
Demand inhibitors include competition, out-of-stocks
(OOS), distribution voids, and incorrect shelving or space
allocation.
Case in point
In a typical promotion scenario, 16% of stores won’t have
available space, 22% won’t display the promotion signage,
33% will put up the displays too late and 42% won’t have
the skilled labor to execute the promotion. Opportunity
gapping identifies problem stores—those that should have
sold more based on the consumer fit and performance of
similar stores.
Promotions can then be adjusted to focus resources on areas
with the highest potential upside. In essence, opportunity
gapping acts like a forward-looking diagnosis that determines
if the financial upside return from a promotion is
worth the effort of store checks, additional labor, or the
promotion itself.
“Retailers and manufacturers are becoming
more precise in their targeting of consumer
segments and wish to optimize store
conditions at the local level.”
–Paris Gogos, Director
ACNielsen Retail Execution Services
Step 3: Dynamic clustering
Clustering, or localization, as the Harvard Business Review
calls it, is the cornerstone of scalability. More than a capability,
clustering has become an operating necessity in
today’s fragmented marketplace.
Retailers and manufacturers are increasingly moving to
micro views of their business to identify opportunities
associated with the demand drivers and demand inhibitors
unique to each store. This is most clearly seen in the growing
number of retailers adopting local or neighborhood
marketing initiatives. Most recently, Wal-Mart announced
they were dropping their one-size-fits-all approach to stores.
Similarly, manufacturers are becoming more precise in targeting
of consumer segments, and wish to optimize store
conditions at the local level.
Clustering attributes
While there is a virtually limitless set of criteria upon which
clusters can be based, most fall into four major groupings:
1. Consumer Attributes. These may be as simple as
grouping stores based on a common trait like ethnicity,
affluence of the shopper, or a volume-predictive measure
of consumer fit.
2. Organizational Attributes. These may include DSD sales
routes, warehouse locations, regions or districts, or
specific shelving sets.
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