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Upgrade your CRM data strategies
By David McNamara
August
21, 2001
An underutilized customer relationship
management (CRM) system--or one that cannot match its
owner's expectations--will reflect poorly on both the
vendor who sold it and the IT manager who authorized
the purchase and installed it. Both the vendor and the
manager, however, can help successfully manage such
expectations (and add value to their respective roles)
by wisely counseling about the strategic context into
which a CRM system must function.
Simply put, the market includes plenty
of CRM products--embracing a variety of technical approaches--for
gathering data from each contact with a customer or
prospect. While each can support customer acquisition
and retention efforts, data collection cannot be an
end unto itself. In fact, a data strategy is needed
to target and keep the right types of customers.
For vendors and IT managers to help enterprise users,
this is an overview of how they can develop and implement
a data strategy to guide both the acquisition and retention
phases of a marketing campaign within which a CRM system
can be optimally flexed.
Supporting acquisition
The first goal in the acquisition phase
must be deciding which prospects most closely match
the profile of an "ideal" prospect. Cherry-pick
prospects and resist chasing those that don't meet acquisition
criteria. Keeping marketing efforts sharply focused
will cut costs and increase your CRM return on investment
(ROI).
Ongoing assessments of marketing campaigns must be made
to determine which are most effective in bringing in
new customers. An effective CRM system will assign each
contact to a specific marketing campaign, tagging the
data for continual analysis of marketing ROI and effectiveness
in identifying likely prospects. By tracking expenses
tied to leads generated, customers acquired, and potential
and realized revenue, campaigns can be shaped to individual
customers and prospects based on specific responses
or effectiveness rates.
The needs and interests of individuals, of course, can
be best understood by examining data from individual
prospects. But aggregate data can better forecast which
groupings or classes of would-be customers respond best
to marketing appeals. This broader view can efficiently
guide development of products or services to satisfy
specific target groups.
Guiding the strategy
To guide the development of an acquisition
data strategy, answer the following:
· What is the best source for customers?
· Were they referrals, or did they find you on their
own?
· Did they respond to direct marketing or external sources?
· On first contact, what information did they seek?
· Did the sale stem from self-service or assisted interaction?
· What was the ROI for the campaign?
Consider also the absence of certain inquiries. Why,
for example, are there no Web inquiries from prospects
already in the non-Web channel customer base? Analyzing
Web-based self-service usage (in other words, searching
knowledge base or initiating support cases) can uncover
customer interests and suggest process improvement.
Keep in mind that prospects may have far different information
and support needs than current customers. This can help
in fine-tuning an acquisition program to better respond
to those customers. Remember, first impressions come
but once. For instance, data may show that first-time
inquiries responded to within 30 minutes are twice as
likely to lead to a sale than those held to the next
day. Analyzing such factors can suggest areas for performance
improvement.
Coddling customers
Shifting from acquisition to retention
transfers the goals to a focus on establishing loyalty,
advancing the relationship, and building a sense of
community, participation, and affinity. The retention
data strategy, as with prospecting, also must be built
on determining which customers meet that ideal criteria.
Even minimal improvements in retention rates can lead
to big improvements in profitability and overall ROI.
With this in mind, look for factors that will feed back
into the acquisition cycle to trim marketing costs and/or
increase success rates. Analyze the trends in the length
of customer relationships to help determine if something
can be done to avert customer losses at critical points
along the way.
All organizations that regularly update customer data
should review and analyze it to pinpoint opportunities
to up-sell, cross-sell, and service sales. For example,
sales data can reveal which customers are due for product/service
upgrades or warranty extensions.
To guide development of a retention data strategy, answer
the following:
· What are the characteristics of the best customers?
· What keeps them loyal?
· What's the potential for developing similarly loyal
customers?
· What are the information and service needs of established
customers compared to those of prospects?
· What prospect information, if any, needs to be saved
once a relationship is established?
· Are there changes the organization should make as
the relationship evolves?
· Why were products returned?
· How many service calls did customers place and why?
· How were service calls resolved and how long did it
take?
· Why does one set of customers respond to opportunities
when another doesn't?
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This story originally appeared on
CNET Enterprise in January 2001. |
