Cost Reduction Gets a Dutch Touch With Data Mining
Dutch insurance company FBTO Verzekeringen has 500,000 customers and underwrites more than one million car, health, home, and life insurance policies. It uses only direct channels to market its products, interacting with customers through direct mail, the call center, and the Internet.
FBTO used to send out only mass mailings and found that because marketing campaigns were not targeted at the people most likely to respond, there was a relatively low conversion rate of mailings to actual sales. "We had a feeling we could improve our results on direct mail by improving our analysis capabilities," says Jeroen Pronk, database marketing manager at FBTO. "Our main goal was cost reduction and we were looking for ways to do more campaigns in the same amount of time."
The company selected SPSS PredictiveMarketing, which uses predictive analytics to identify customers who are more likely to purchase certain financial products. "[FBTO] tackled in a relatively easy way who bought before, who likely would respond, and cut out people who wouldn't," says Colin Shearer, vice president of product marketing for SPSS. "[FBTO] reduced the cost of campaign spending by 35 percent--they got rid of that waste."
As an initial test, the insurance company took six campaigns and ran them simultaneously--half with the traditional marketing efforts and half with the campaign optimization model. The optimized set resulted in 29 percent higher profit. "We were really surprised the way such an amount of money [was] saved by implementing a data mining tool," Pronk says. "SPSS had the most open architecture so in the future we [will] be able to use the analysis in different channels."
By deploying a campaign optimization tool, FBTO:
reduced campaign costs by 35 percent in the first year;
saw a 29 percent profit improvement; and
increased conversion rates by 40 percent.