A CRM System Needs A Data Strategy

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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.


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.

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