The level of effectiveness
of any customer management programme can be dramatically increased
by "slicing and dicing" the customer base according
to different characteristics that relate to overall objectives.
This process is commonly referred to as segmentation.
Imonic have experienced many different situations
that required the use of various techniques. In business to
consumer work with a domestic supply company holding 5 million
customers, building customer databases, applying analytical
tools and then operationalising the outcomes was the name
of the game. The intention of course was to finely slice the
customer base so that actions could be tailored to each different
slice, hence accuracy was increased and waste reduced.
Much of our work however, is in the business-to-business
arena, with high value customers. Here the approach needs
to be very different. In some cases it can be a matter of
segmenting into slices of one or two customers per segment,
in order of value to the organisation, and thus creating a
customer league table. This approach is particularly relevant
to large clients that only have a handful of customers (e.g.
Aerospace and Military).
Criteria for segmentation can vary enormously
from client to client, dependent on sector and project objectives.
Imonic would advocate a simple approach to 'testing' initially.
This will identify key information which is required and what
is currently 'not available'. Take the matrix below (Fig 1).
This was used to identify and confirm 'key account' status
in a recent aerospace client.
Figure 1: Simple Key Customer Segmentation
the criteria or characteristics on which to segment can usually
be agreed very quickly by input from a cross section of the
management team. Next comes the 'weighting' of criteria; e.g.
is profitability more important than 'historical value', 'turnover',
or 'prestige'? If so, by what order of magnitude (20%, 50%
or 200%)? Point's totals are allocated to each criterion to
replicate the weighting levels.
Each criteria is further divided into 'bands'
e.g. if profitability is scored out of 10, you may have 2
points for breakeven, 5 points for a profit margin of 10%
or less, 7 points for 10-20% and 10 points for a customer
with above 20% profit margin.
Simply taking a selection of well-known
customers and applying the model to them can easily test the
One of our clients used a similar simple
approach which worked so well they integrated the model into
their ERP system, this then flagged any customer reaching
their pre-determined 'key account status'. This came from
the point's level the account had amassed via daily trading.
In some cases this identified new key accounts up to six months
earlier than they had been able to do previously. They could
then begin to apply individual customer focus and differentiation
much earlier - and of course before the account migrated.
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