Data Quality Pays
The following example shows the value of high-quality data in providing accurate customer information. A mid-sized West Coast bank wanted to acquire the 61 branches that two merging regional banks were required to sell by federal regulators. The mid-sized bank performed data quality processing on the customer files of the merging banks. By finding the duplicate customers and determining a true customer count, the bank was able to negotiate a better price and aggressively market to those customers, who may have chosen to go to the new merged bank. The immediate ROI was a savings of several million dollars in the price paid for the branches, and the bank retained a high number of the customers.
Match Accuracy is Key for success
Getting accurate customer information takes more than data cleansing. It requires a data quality solution with powerful matching—with nearly 100-percent accuracy—that can find all the data and relationships relevant to a customer. The optimal data quality solution will:
• Investigate data thoroughly—to find, exhibit and understand the hidden relationships, structures and rules;
• Create the consistency necessary to achieve the highest match rate by normalizing and standardizing the data; and
• Match data across records—even non-exact matching records (because normalizing can't eliminate all data issues)—to ensure complete, nearly 100 percent visibility on customers and their relationships for customer intelligence.
Why is this level of match accuracy and data quality necessary? Because data quality pays. Only the best matching will yield accurate, consolidated customer views and true customer intelligence. Information that is only 85-percent to 90 percent accurate is misinformation. For every 100 customers, it can result in 10 to 15 missed opportunities and, possibly, lost sales and customers.
Obtaining high-quality data that reveal all the company's relationships with customers is the first step in understanding, improving and leveraging those relationships. It's the foundation for creating customer satisfaction and loyalty and for gaining the full ROI from CRM initiatives.