Charles Schwab & Co. said a pilot program to retain affluent customers has saved it an estimated $200 million of assets it otherwise might have lost, and it is now rolling out the program nationwide.
The goal of the data base marketing program is to determine how likely it is that a customer with more than $500,000 of assets deposited would switch institutions. With 5.5 million accounts, Schwab has $408 billion of assets under management.
In May 1997, Schwab's data base marketing group and field organization constructed a model to detect signs of attrition among wealthy customers. In a pilot test begun in August of that year, telemarketing teams began calling customers thought likely to leave.
Those who confirmed they were thinking of leaving but were retained were counted toward the total of saved assets. Schwab's ability to identify and retain those customers was then analyzed against control groups.
Schwab expanded the test regionally late last year and recently began rolling out the program nationally. David Chambers, director of data base marketing at Schwab, called the results of the regional test "very positive." He described the program in a speech he gave last month at a New York City conference on customer relationship management sponsored by Business Strategy Network.
Mr. Chambers stressed the importance of gaining the input and participation of a direct sales force when introducing a technology tool such as a retention model. Technology can be unwelcome to a sales force, he said.
"We told them that this does not replace their efforts but gives them a tool to make better use of their time in contacting those people who don't come into the office," he said.
Often the sales force knows better than headquarters the status of particular customers, he added. In many instances, the field staff gave answers about customers that the model could not, he said. For example, field representatives could say when customers left Schwab due to divorce or death.
Project managers from the field take key roles in retention programs but need data base marketing support, Mr. Chambers said.
Data base marketing, which involves cleansing, segmenting, and modeling data, often suffers from a lack of definition. And top executives often underestimate the difficulty of developing data base marketing systems, Mr. Chambers said.