Case Study

Federal Government Case Study: Royal Canadian Mint


The Royal Canadian Mint is the Crown Corporation responsible for the minting and distribution of Canada’s circulation coins. Recognized as one of the largest and most versatile mints in the world, it offers a wide range of branded investment, collectible and secure payment products and services.


Recently, the Mint wanted to better understand the behaviour of its numismatic collectible coin buyers. With an active consumer database that has tripled since 2010, the Mint needed to find new ways to manage its growth, understand changes in its composition and quickly take action based on the analysis. By identifying key characteristics of high-value new and existing customers, the Mint hoped to create custom models to develop effective up-sell and cross-sell strategies throughout the consumer lifecycle. 


Turning to a combination of internal data-mining approaches and tools from Environics Analytics, the Mint tested new strategies to cost effectively acquire first-time buyers and deepen relationships with existing customers. For its “$20 for $20” Polar Bear coin promotion, the Mint used PRIZM to analyze previous customers: what they’re like, how they think and where they live. When the analysis showed that high concentrations of first-time buyers lived in PRIZM lifestyle types like Pets & PCs (large, upscale suburban families) and Ontario Originals (older, lower-middle-class couples and families), the Mint sent unaddressed admail to postal walks home to those top-performing segments. In examining loyal customers—those who’d spent more than $1,000 in the past 12 months on coins—analysts developed a custom model to identify those who could spend more—and by how much—thereby qualifying them for more personalized attention from the Mint. The model relied on both internal and external data from EA, such as lifestyle types (PRIZM), demographics (DemoStats) and spending potential (WealthScapes). 


The data analytics helped the Mint in a number of ways: Response rates of prospects for “$20 for $20” coins increased significantly; the number of high-value customers grew considerably; and 140,000 new customers were added to the Mint’s $20-for-$20 series, thanks to the neighbourhood-based PRIZM segmentation system. In addition, the internal data model, which could predict customer behaviour at the individual level, allowed the Mint to identify 15 percent more prospects for major coin purchases—and predicted higher revenues over the next year.

These successful campaigns led to more strategic applications. The Mint now uses PRIZM data when selecting print and online media and choosing postal walks for unaddressed admail campaigns. It incorporates custom models to develop effective up-sell and cross-sell strategies. And rather than rely solely on surveys or progressive profiling techniques that take months to segment customers, the Mint uses lifestyle-based segmentation to quickly develop targeted marketing campaigns—reducing the analytical time from over six weeks to less than two. “The reduced analytical time creates less potential friction or ‘speed bumps’ for our customers,” says Bernie Schroeder, Senior Manager of Customer Strategy and Insight at the Royal Canadian Mint. “Solutions like PRIZM and custom modelling are tools you can use to extract the maximum value from the relationships you have with your customers.”