Company
The Home Depot Canada is the largest retailer in Canada for do-it-yourselfers, as well as home improvement, construction and building maintenance professionals. They stock more than 300,000 home improvement products, tailored to the communities they serve.
Contobox™ is a leader in eCommerce technology. Brands use the Contobox platform to reach shoppers with convenient, personalized recommendations and messaging that drives sales, across any format or device. Our Shopper Intelligence scores interest in products based on user engagement and purchase trends using predictive intelligence to recommend products. This fuels our Enhanced Creative with personalized and shoppable features across the customer journey.
Goals
With the explosion of retail online sales due to the pandemic, The Home Depot’s need to modernize their prospecting campaigns became impossible to ignore.
For years they have been perfecting their data-driven marketing strategies, personalizing the customer journey for high-interest audience retargeting campaigns. The Home Depot looked to translate this success into personalized prospecting campaigns. Leading to the question – How do you personalize ads for people who’ve never made a purchase, or visited your website?
To deliver performance display campaigns that drive online sales without PII or cookies, The Home Depot would need to predict what products an unknown prospect would be most interested in. Home Depot’s data team uses big data to inform future campaigns but for this to work it would require a real-time solution to model and train algorithms while the data was fresh to capitalize on consumer micro-trends.
Challenges
As a retailer with over 300k products Home Depot had two key challenges: Firstly, matching the prospect with the right products, and secondly displaying products at scale in ads with the correct local availability and pricing.
To determine the right products, The Home Depot used the predictive intelligence of Contobox’s Customer Data Platform to power their prospecting campaign. The platform’s shopper intelligence engine analyzed successful customer journeys and contextual influence factors. This data included sales, promotions, products, SKUs and website engagement data cross-referenced with location, time and weather data.
Product recommendations were done in real-time with display ads connected to Home Depot’s eCommerce API to dynamically serve up-to-date pricing, promos, and ratings alongside every product. The ads included an interactive carousel with 5 products and add-to-cart functionality transforming each impression into a storefront personalized for every shopper. Machine learning kept improving the recommendations and ROAS as the campaign went on.
Results
The results proved the power of the Home Depot’s customer journey-driven tech stack. The common industry return on ad spend target for campaigns is two dollars returned for every one dollar spent. The campaign outperformed this industry average by forty-five times.
Overall, the campaign delivered a year-over-year increase in return on ad spend of 867% over 2020 (which had been a record breaking year for The Home Depot), with the desktop portion of the campaign seeing a 560% year-over-year increase in return on ad spend.
Home Depot saw its biggest increase with audiences on mobile. Fueling the campaign’s dynamic prospecting with sales data helped the brand generate a 1,461% year-over-year increase in return on ad spend. Proving that with the right technology and 1st party commerce data you can unlock superior performance from your prospecting campaigns.
Creative
