Companies use demographic,
psychographic and product segmentation schemes to help execute a
variety of business activities. For example, a marketing
communications team may segment a market by region to help
execute a mailing campaign. A finance department may use a
segmentation scheme such as vertical industry to report sales
figures. But when it comes to innovation, the goal of
segmentation is to discover segments of customers who have
different unmet needs. Finding these unique segments of
opportunity – if they exist – can transform an entire industry
as evidenced by companies such as e-Trade and Curves.
For the purpose of innovation, then, it makes sense to use unmet
needs as the bases around which to segment the market. Many of
you may be thinking – “wasn’t this the idea behind needs-based
segmentation? We tried that 20 years ago and it did not work.”
Well, I tried needs-based segmentation back in my days at IBM as
well and I finally concluded it did not work for 2 reasons – and
correcting these oversights has dramatically evolved the
practice of segmentation.
First – just what a customer need is was poorly defined until
recently and most needs-based segmentation studies ended up
using many types of inputs for segmentation – not only needs. In
order to discover segments of opportunity, a customer need must
be defined as a metric that is used to measure the successful
execution of a given job, and these desired outcome statements –
which adhere to a strict set of rules for structure, content and
format – must be used as the inputs for segmentation. Precision
in the inputs is the first key to success.
Second, to find a segment of the population that has an unmet
need, a company must agree on what “unmet” means. This too was
not well defined until recently. An unmet need in the
outcome-driven paradigm – is defined as a desired outcome that
is important and not well satisfied. We have devised what we
call the opportunity algorithm to mathematically calculate an
opportunity score for an outcome. The more important and less
satisfied an outcome is, the greater the opportunity is for
value creation. Using the opportunity score as the value around
which to segment a market is the second secret to a successful
segmentation.
Keep in mind, we are not suggesting that a company abandon the
use of other segmentation schemes – many serve a valid purpose.
But when it comes to segmenting a market for the purpose of
innovation, using desired outcomes as the input and the
opportunity score in the clustering formula reveals what
marketing organizations have wanted to discover for years –
segments of customers with different unmet needs.
