When people buy a new home, get married, or go through any major life event, a new mattress often accompanies the change. Fueled by the increased activity in the real estate market and the recovering economy, the mattress business has been booming. So in 2014, many mattress companies expanded, increasing the number of brick-and-mortar locations across the U.S.
Even though revenue was up across the top ten U.S. retailers, the inﬂux of new stores drove down the average revenue-per-store by 8% per location. But a curious thing happened at Sit ‘n Sleep, Southern California’s largest mattress retailer. With its 33 locations, Sit n’ Sleep saw an 11% average gain per store, 18% above the per-store average of the remaining top ten retailers in the country.
Larry Miller, owner of Sit ‘n Sleep, works tirelessly to keep his stores competitive. In 2014, with the help of his agency of record, Wingman Advertising, he rolled out an upgraded website and added more promotional events, including the 2-Millionth Mattress Sale, to its calendar. What else could account for a massive 18% lift over the other top ten retailers? Wingman Advertising’s analytics platform.
Over the past few years, Wingman has seen a sea change in consumer purchase behaviors. “Previously, it would be typical for a consumer to drive to a mattress store early in their decision-making process,” says Steve Dubane, Principal at Wingman Advertising.” But now, they do most of their research online via mobile phones and tablets before coming to the store to make their purchases. And the research bears that out.” According to Adweek, “81% of shoppers research online before buying,” although “54% of shoppers want to actually see the product before purchase.” There’s even a growing trend towards buying mattresses online. In 2014, Sit ‘n Sleep saw an uptick of 60% over the previous year and 2015 is already looking to double that.
Wingman examines the pre-purchase shopping patterns that take place on our clients websites. For Sit ‘n Sleep, Wingman identified a key consumer behavior which had an 88% correlation to sales at the store level. Identifying this pattern allowed Wingman and Sit ‘n Sleep to easily calculate its value in terms of sales and how much they should pay for it.
To optimize Sit ‘n Sleep’s multi-million-dollar media budget, Wingman created a attribution model that tracks radio and TV spot times to individuals performing this key behavior. Because online shopping almost always precedes driving to a store, Wingman sees upticks in Web traffic to specific radio and TV airings. Wingman compares those spikes to see which broadcast spots yielded the most beneficial online traffic based on the identified key behavior.
According to Dubane, “We looked at Internet activity with highest propensity to purchase and optimized our online and broadcast channels accordingly. This strategy helped Wingman eliminate under- performing media channels and specific outlets and reallocate budget to top performers.
This new cross-channel optimization model gave Wingman and Sit ‘n Sleep a clearer look at how their media dollars worked. Previously, the only numbers Sit ‘n Sleep mustered to judge advertising to retail efficacy was customer-reported data acquired at point of sale which was rarely actionable. This new optimization model allowed Wingman to create new, direct-response-style analytics for traditional brand and price-point-driven retail marketing. This analytics upgrade, alongside Sit ‘n Sleep’s more aggressive marketing strategy, impacted revenue substantially and helped it eclipse the competition in sales-per-location in a growth year.