Articles
Beyond Product Planning: Store Planning and
Clustering
(Part III of a series) (cont.)
Store
Clustering
Store clustering shrinks the size of the
store-planning task by categorizing stores into
groups, or clusters, based on common
characteristics or attributes. For example, you
can cluster stores by performance, such as
volume; or by location, such as warm weather vs.
cold; strip vs. mall; downtown vs. suburbs; or
by target customer,
such as resort, retirement, ethnicity; or
by store size
and layout.
Store clusters provide the basis for
developing customized store assortments and
addressing micro marketing.
How
Are Store Planning and Clustering Done?
Basically there are
two approaches to developing the store plan
—“passive
and active.”
“Passive”
store planning carries that name because the
planner is less involved.
That is, the plan is generated
automatically.
It is based on algorithms or defined
mathematics, using data from historical
performance, forecasts, and chain-level
merchandise plans.
Many allocation systems have built-in
algorithms to develop store plans from
merchandise plans.
It is possible for a planner to review
system output and alter it if necessary,
but direct involvement is much less than
in the active method.
In
“active”
store planning, the store planner participates
more fully (or actively) in developing and
reviewing the plan, as in building the
chain-level merchandise plan.
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