At Thursday’s CMA Analytics conference, Canadian Tire‘s Sean Stokes gave a glimpse of what it looks like when a retailer uses data to drive every part of its business, from product development to merchandising and marketing.
The objective? Grow Canadian Tire’s in-store sales and brand metrics during the winter holiday season, its most busy time of year.
Stokes, who is the associate vice-president of customer analytics for Canadian Tire, said the company used data to help formulate an idea to boost national sales, and then devise the means to carry it out. And it all revolved around Christmas lights.
“Christmas might be a business where Canadian Tire already has significnat market share and significant growth, but we think there’s opportunity to grow even more,” he said. “How do we figure out what it is within Christmas that’s driving growth — or can drive growth?”
The company mined through its trove of in-store and online purchase records, financial data from its branded credit cards as well as partner data, to figure out what high-value customers were buying and which items were most often being paired with other items. They wanted to know: what product had the highest propensity to drive overall sales, not just in related categories, but throughout the entire store?
It wasn’t windshield wiper fluid or snow shovels that turned out to be the biggest driver of sales — it was Christmas lights. “Christmas lights were really the key to driving the overall Christmas business, and getting that customer engagement that we needed,” Stokes said.
Having discovered where the opportunity lay, Canadian Tire set out to improve its Noma-brand Christmas lights, relaunch them and draw customers into the store to buy them. The first step was getting more data: painstaking market research into what customers disliked about Noma lights, and how they could be redeveloped for greater appeal. The biggest pain point was putting them up, specifically trying to find ways to clip the lights to eavestroughs without hammering nails or breaking the brittle clips.
The company brought in a design partner to develop several dozen new ideas for the fixture, and finally settled on its rotating quick clip design. Then Canadian Tire took it to 15,000 product testers across Canada to collect even more data.
The tester data wasn’t just for putting the finishing touches on the product — it was also about developing the insights Canadian Tire would later use in its marketing campaigns. That’s one of the keys to the success of its “Tested for Life in Canada” campaigns, Stokes said — the products actually were tested, and the product ads highlight real features that testers liked about them. That wouldn’t have been possible without shared data insights between the marketing and product testing teams.
The new Noma Christmas lights hit the shelves in November 2013 with an omnichannel campaign. The TV spot was a simple product demonstration, comparing the new clip lights with standard ones — showing how the quick clips helped one dad save enough time to put together a flashy, music-synced display.
“You wouldn’t assume there’s a bunch of analytics behind it, but there is. We had a specific target customer in mind, and through our Tested for Life program we could highlight some key things that were important to those target customers.”
The in-store sales results were “fantastic,” he said. Sales exceeded forecasts, especially in the high-value customer segment, and the Noma brand saw substantial lift in awareness, purchase consideration and quality perception.
The key to the whole enterprise, he said, was having an executive team that understood the importance of customer analytics and embraced it at every step of the way.
Executive leadership ensured the entire organization was aligned on a single strategy, and it guaranteed the investment in infrastructure and data science talent needed to make data-driven marketing possible.
“You need that senior leadership support, because if you don’t have it at [the analysis] stage, you’ll have decisions made in your company based on personal bias or politics,” he said. “We’ve been lucky in that even when some of the analytics don’t jive with what some of the senior marketers are thinking, they’re willing to take a second look and go in a different direction.”
