case studies

Insurance Case Study: Erie Mutual Insurance Company


Founded in 1871, Erie Mutual currently serves more than 3,300 policyholders in the Haldimand-Niagara Region of Ontario with its team of sales agents, underwriters and loss prevention officers. As one of 44 mutual insurance companies operating in the province, it has grown and prospered over the years by offering a full line of farm, home, auto and personal liability insurance.


After years of relying on word-of-mouth, Erie Mutual’s sales agents were struggling to develop new business. Surveys showed that although claims and policyholder experience was rated high, brand awareness was low. The industry was changing, with increased regulatory pressures and low-price competition from big direct writers—not to mention new digital sales channels. While other insurance companies were moving to the web and downsizing their sales force, Erie Mutual wanted to increase its agent network to deepen its relationship with policyholders—despite a lack of customer information.


To become more customer-centric, Erie Mutual turned to data analytics and Environics Analytics in December 2012. Researchers began by analyzing Erie Mutual’s active customers with PRIZMC2, a segmentation system that classifies Canadians into 66 lifestyle types based on their predominant demographics, behaviour and attitudes. The detailed customer segments helped Erie Mutual understand the market size, learn more about their policyholders beyond their buying habits and gain insights to guide marketing campaigns. Data-based maps showed the areas in Haldimand-Niagara where Erie Mutual would likely find prospects. And that information helped determine the right media mix and the best way to communicate the unique Mutual value proposition. The results helped sales agents identify customers for cross-selling products and rank postal codes for targeting promising prospects.


Armed with this data, Erie Mutual’s marketing team communicated their enhanced understanding of their customers across the company—to sales agents, claims people, even board members. The PRIZM-based data helped Erie Mutual develop a 2014 sales and marketing plan to identify new prospects, target its messages and increase its brand awareness. The company posted billboards in strategic locations in the Niagara region, displayed digital out-of-home screens in a popular regional mall and dispatched mail solicitations to postal codes with high concentrations of prospects—making sure to follow up those cards with personal contacts. And in a burst of outside-the-box thinking, marketers wrapped their fleet of loss-prevention vehicles with brand advertising to capture the attention of customers-on-the-go.

The new campaign paid off. Revenue from new business climbed 40 percent—nearly twice last year’s growth rate—with an uptick in the number of new policyholders. “We’re benefitting from sending out a targeted message rather than a shotgun message,” says John Dunton, the president and CEO of Erie Mutual. And Dunton is enthusiastic about other initiatives coming in 2014: the launch of a loyalty program, several customer appreciation events and a social media campaign. For a company once considered “so last century,” Erie Mutual is now dedicated to forward-thinking, data-driven analytics to grow its customer-centric business in a rapidly changing industry.