case studies

Insurance Case Study: Canada Life


Founded in 1847, the Canada Life Assurance Company provides a wide range of insurance and wealth management products and services to individuals, families and business owners across Canada. Canada Life’s direct marketing business promotes life, accident, critical illness and related products to the customers and credit cardholders of clients such as Sears Financial, Canadian Tire and Hudson’s Bay Co. Through Canada Life, over one million Certificates of Insurance are in force.


In 2010, Canada Life acquired a new direct marketing client with a large customer credit card database. But the company discovered that leveraging the database to identify and quantify new insurance prospects was difficult: Canada Life lacked prior experience with the database, had limited ability to select records for a campaign and had no access to historical response data, customer profiles, segmentation strategies or targeting information. Before proceeding with a direct marketing program, Canada Life needed to better understand the new client’s customers, identify potential market segments and leverage its knowledge of existing Canada Life policyholders to better target its marketing to prospects within the new database. “We needed to create a methodology that would allow us to quantify the true ‘size of the prize,’” explains David Savournin, the Senior Marketing Manager of Direct Marketing at Canada Life. “And we needed a partner to do all this quickly.”


To help it value the database opportunity, Canada Life turned to Environics Analytics (EA) to gain a better understanding of its existing policyholders and compare them to the new database’s customers. After scoring every client record according to its PRIZMC2 segment, analysts created a product penetration index for each cluster. They then developed a data visualization platform to conduct a multivariate analysis of the new customer database to determine the drivers behind responsive customers—drivers like recency and frequency of client credit card usage. But unlike a static model, the visualization tool allowed analysts to continue exploring the data in real time with constant queries so it could extract new insights for reaching newly targeted prospects. Every month, Canada Life revised its marketing campaigns based on the changing insights and performance trends—findings delivered by the tool in a matter of minutes rather than the hours or days required for tabular reports. “The visualization tool allowed us to zero in on the people we wanted to concentrate on immediately,” says Savournin. “We could constantly look for new opportunities.”


With the segmentation and visualization results, Canada Life quickly built response models that allowed the company to quantify the size of the opportunity for converting client cardholders into insurance customers. And over the past year, the company launched a series of direct mail and telemarketing campaigns to the targeted cardholders that have proven remarkably successful. Between May 2010 and October 2011, Canada Life’s customer acquisition costs declined by 78 percent while its gross response rates increased by 93 percent. And with each campaign, Canada Life refines its targeting strategy. As Savournin observes, “Data visualization delivers measurable gain by providing an easy-to-use and intuitive means of communicating quantitative results, trends and areas of improvement.”