Introduction
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, 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 (i.e., 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?
CRM
Platform Choices
Which CRM platform is chosen will affect a company's ability to collect,
analyze and use data. A balanced solution will provide both the functionality
and the agility needed to address changing marketplace demands.
An ideal solution should be easily deployed and cost-effective
through its life cycle.
Beyond
the CRM tool, it is advantageous to store all customer information in
a single place - rather than spread among marketing, sales or support
databases, depending on which channel they used most recently. Universal
access, where anyone in the organization can look at the same data, presents
all departments a unified face of each customer. Likewise, customers should
see but one, branded company regardless of how they made contact.
To
reflect a company's unique business outlook and preferences, the CRM solution
should be customizable and easy to reconfigure. Only useful types
of information should be tracked, with tracking of irrelevant data halted.
Essentially, it must be able to accommodate new requirements as a company's
needs evolve.
Meantime,
many companies are taking advantage of Internet-based technology to outsource
customized relationship-management services. Most application service
providers (ASPs) can give prospects and customers self-service tools and
information-request forms. High-end ASPs can host CRM solutions that also
include management and administrative tools to monitor application usage
and guarantee levels of service.
Conclusion
Developing an effective data strategy for the CRM process can make optimal
use of the information needed to better run a company. Success is ultimately
based on decisions about both who is pursued and who is wooed for retention
as customers. A CRM solution should have the tools and flexibility to
support that ongoing mission.
Intelligent
data analysis can show if marketing activities fit customer acquisition
and retention goals. It can direct both the speed and the quality of response
to inquiries and shape product and service offerings. Most importantly,
a well-considered data strategy - effectively applied, in concert with
an appropriate CRM system - will enable exercise efficient selectivity
in acquiring and retaining customers.
About
The Author
David McNamara is vice president of sales and marketing at Neteos,
Inc., www.neteos.com. He has a broad background in software product sales
and marketing with more than 20 years' experience in marketing software
solutions and services through diverse channels of distribution. Earlier
he held key management positions at Security-7 Software Inc., The BISYS
Group, Network Defenders Inc. and Motorola. He holds a bachelor of science
degree in electrical engineering from the University of Rhode Island.
He
can be reached at davemc@neteos.com
or 781-466-0100.