Data Mining: A Strategic Plan
-By Rick Brough, director of consulting services
There is great advice out there about the how-to of
data mining. But there is precious little about the
DM'ers often launch a campaign under tight deadlines
and fail to think through how they’ll use customer
data to support it or measure the results. In
effect, they create more work and risk for
If only they focused on strategy as much as they do
on tactics. All would be well.
Where to start?
First, the marketer should streamline the
preparatory work for each campaign by building a
consistent method for identifying opportunities
within the customer base.
This builds efficiencies into the marketing process
and helps deliver relevant and consistent customer
experience across multiple channels, thereby
improving marketing efficiency and effectiveness.
The tools for tactical data mining are widely
available and generally reliable, making it easy to
apply them to one-off efforts. But there is no
software package to guide marketers through the
strategic approach; they have to step back and do
the thinking themselves or engage a partner who can
help guide them through the process.
What follows are the six stages in the hierarchy of
data analytics, and the value of each to a
well-rounded strategic approach:
Data access: This is the foundation on which
marketers build by collecting all pertinent
information about customers, including name,
address, demographic data, history of transactions,
product and service purchases, and responses to past
campaigns. Every business should earmark the
appropriate resources to ensure this data is as
accurate and up-to-date as possible.
Reporting/profiling: Key performance indicators are
developed and applied to track the performance of
customer relationship management (CRM) initiatives
over time and across customer segments. Here,
marketers can also track client migrations across
various segments, compare responders versus
non-responders, and gauge campaign response over
Current value: The underlying premise for CRM is
that not all customers provide equal value to an
organization. Therefore, the first step for any CRM
initiative is to measure customers by their value to
For example, 20% of clients might account for 80% of
a company’s business, and would be worth a lot of
the marketer’s time and money. Another 30% might be
designated as moderately valuable, but having the
potential to move up into the top 20%; they’d
require a different kind of pitch.
The last 50% could account for just 5% of the
company’s business; they are less committed,
motivated largely by price, and require still
another approach (or, maybe, none at all).
Segmentation: In this stage, marketers identify
prospects who share similar characteristics – who,
therefore, belong to one of several specific
This provides the opportunity to focus on the
highest-value segments and acquire new customers who
match the segments identified as most desirable. As
well, sales pitches can be custom-tailored to suit
each segment using what is known about those
segments. Customers can be segmented using many
But segments should focus on identifying customers
with similar product and service needs as implied
through neighborhood socio-demographic
characteristics, life stage, usage behavior, or
needs and attitudes as identified by market
Predictive analytics: Use this to predict each
customer’s likelihood to initiate a particular
activity in future based on their unique
characteristics and past behavior.
The benefits represent a “win-win” for the
organization and its customers, with marketing ROI
rising, and customers receiving more relevant offers
– the principle of “right message to the right
customer.” Predictive models are developed to assist
marketing at all stages of the customer lifecycle,
including acquisition, cross-sell and up-sell,
retention, and re-activation.
Potential value: This is assessed by combining each
customer’s current value with their potential to buy
more in the future. As with current value, potential
value creates an even clearer way to identify the
most valuable customers, the ones worth keeping.
It also helps to identify those less valuable
customers with potential for entering the
most-valuable category, and those low-value clients
on whom it may not be necessary to spend as much.
Database marketing strategic framework: Using these
six stages, marketers can develop a
database-marketing strategic framework that
differentiates customers based on the value they
currently contribute to an organization, their
product and service needs, and their potential
Each segment so identified should be assigned its
own distinct marketing objectives. And it is crucial
that these distinct objectives are understood across
all channels of an organization, including
marketing, sales, customer service, and operations,
so that all can work in support of them.
Additionally, a strategic approach to database
marketing can facilitate consistent communications
to the customer across multiple channels, including
Print, Web, e-mail, POS and others.
During a campaign, and at the end, it is crucial to
have key performance indicators to measure and track
results in a segment-specific way. What are the
criteria for success?
What will the organization regard as a minimum ROI?
These indicators will be invaluable in planning
subsequent campaigns, but they have to be developed
Finally, it is essential to devise ways to capture
all of the data, both raw and processed, which went
into a campaign and emerged from it. As with the
performance indicators, this data is essential for
crafting subsequent campaigns; rather than starting
from scratch with each campaign.
---Source: Multichannel Merchant List and Data Strategies Feb. 25, 2008 newsletter
(firstname.lastname@example.org). Rick Brough is director of consulting services
for Transcontinental Database Marketing. He can be reached at email@example.com.
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