Data Quality The Foundation for Effective CRM
A growing number of trade press articles and industry analyst research have documented that the return on investment from CRM initiatives and other customer-facing systems has been limited by poor data. In November 2001, Gartner Group published a seminal piece of research on the relationship between data quality and CRM. The principal finding:
"High-quality, well-integrated customer data is the cornerstone of a successful CRM effort. It is also the key to achieving several critical benefits—such as eliminating excess operational costs caused by redundant data, and enhancing revenue through improved customer targeting and retention."
The rapid growth and adoption of CRM is focusing increasing attention on customer data. The number of businesses worldwide implementing such systems, with the associated multimillion-dollar expenditures, continues to grow. With such extensive resource allocations, business executives are under tremendous pressure to realize a return on investment from these expenditures.
To be effective, CRM systems must have at their core accurate, complete and integrated data. The decision-making processes of the enterprise are only as good as the information on which they are based. There is a monumental shift accompanying the growth of CRM—corporate data is being transformed from an IT cost burden to a unique, competitive asset that marketing management is attempting to harness.
The Value of Integrated Data
To obtain return from CRM investments, you must develop and maintain an accurate, single-customer view. Having this vantage provides a cross-enterprise view of the products and services being used by each customer. Gartner Group posits that despite substantial CRM investments, less than 10 percent of enterprises have a single, company-wide view of their customers—a critical stepping stone toward customer loyalty.
The vast majority of businesses have access to variables such as purchase history and lifetime value, offering them timely information about their customer relationships. However, these measures are only useful if they're obtained from reliable and integrated data. For instance, if a business isn't merging customer purchase history from all sales channels such as retail outlets, call centers and Web sites, an enterprise purchase history measure is of little use and can adversely impact future business decisions, such as the development of targeted offers.
Since businesses understand it costs more to acquire new customers than it does to retain existing ones, it pays to introduce current customers to additional products and services. Data quality makes the transformation from new customer to best customer much easier by, among other things, consolidating purchase history.
For example, if a consumer buys a pair of khakis in a company's store, some polo shirts from its Web site, and a pair of loafers via mail order, an offer for casual pants is likely to generate a higher response rate than an offer for a $900 suit. Without a single customer view, however, a call center representative could offer the customer the same pair of khakis he just purchased in the store—at a significant discount. It's no mystery why retention, loyalty and satisfaction rates will increase when offers are generated for goods and services that resonate with customers.
Using solutions that provide an accurate, single customer view also enables you to focus resources on the most profitable customers. With increased intelligence, organizations can more effectively develop and introduce targeted cross-selling and upselling offers that strengthen the bottom line. For instance, by taking measures to identify unique customers across operational divisions, you can avoid the costs and damaged brand image associated with marketing to "John Smith," "John S. Smith" and "J. Smith"—all of whom reside at 123 Main Street in Atlanta, GA.
Data quality also significantly reduces operational costs. Practices such as verifying address data ensures goods and services are delivered quickly and accurately, which is necessary to maintain customer satisfaction. If a company's customer service representatives are entering information into a CRM system that lacks address verification technology, shipments can be improperly delivered due to inaccurate addresses. Incorrectly addressed packages also are penalized by major carriers—even if only the ZIP code is inaccurate—and this can have a costly impact on inventory and supply chain management.
Data quality is an ongoing undertaking. You must ensure the quality of existing as well as new customer data. More than 40 million Americans move each year. To make certain all communications reach customers, businesses that are aggregating customer information in a centralized repository should use solutions that offer the most recent postal change of address information—to maintain the relationships they've worked so hard to cultivate.
Not only should you verify and consolidate customer data, you should also enrich that information with demographic and geographic data. In addition to comprehensive firmagraphic data such as number of employees and revenue for business-to-business marketing, there also is a variety of demographic and lifestyle intelligence that can provide greater insight into a customer or prospect.
For instance, if our casual menswear consumer resides in an affluent area, an offer for Ralph Lauren polo shirts will most likely be better received than one for a non-branded shirt. Adding geographic intelligence to your customer file also is of great value. And if you know where the customer is located geographically, it is easier to direct that individual to the correct store. Developing marketing offers based on this type of intelligence leverages your understanding of the customer.
To maximize the ROI from CRM investment, ensure the accuracy of your customer data. A CRM solution is only as good as the quality of the customer data that feeds it.
David Peikin is corporate communications manager for Group 1 Software, a Lanham, MD-based CRM software
solutions provider. He can be reached at (301) 918-0818, or e-mail: firstname.lastname@example.org.