Had ousted J.C. Penney CEO, Ron Johnson, figured out a way to give customers what they wanted – a stellar in-store experience – he might still be at the helm of the brick-and-mortar retail giant.
But Johnson didn’t give customers what they wanted, he gave them what he thought they wanted, causing them to abandon the sinking retail ship in droves, and costing him his job.
The lesson to be learned from the J.C. Penney debacle is that to survive, brick-and-mortar retailers must create in-store customer experiences that set them apart from their online competitors – or face extinction, according to an article in Forbes.
“. . . [F]or retailers, competing based on price, location and even product is no longer sufficient,” Larry Freed, CEO of customer experience analytics company ForeSee, tells Forbes. “The way they’ll win is by providing a superior customer experience – which is proven to be an accurate predictor of financial performance.”
And the way to do that is with predictive analytics, not trial and error, he adds.
Not only is trial and error costly and time consuming, it’s not a very reliable way to evaluate the success or failure of a particular change that’s made in the store, Freed says.
Retailers can also use predictive analytics to make sense of the data coming into the company from every channel – physical stores, web and mobile – he says.
“Consumers have changed a lot, [but] retailers have been slow to react to the multi-channel consumer,” Freed notes.
Here’s a look at how ForeSee has used predictive analytics to help Hickory Farms, Perry Ellis and the NFLShop.com increase their ROI and make their customers happy.
The first thing ForeSee did was help Hickory Farms, which sells food gifts in over 700 Hickory Farms stores, online and at other US retailers, identify and analyze what e-commerce shoppers were researching on the web and “where they should improve the experience that would drive the right behavior,” Freed says.
Then using predictive analytics, Hickory Farms uncovered a new sales opportunity for new items based on the customers’ online behaviors. The retailer also added merchandise that customers wanted but that Hickory Farms wasn’t carrying in its physical stores.
The result: Hickory Farms generated more than $600,000 in additional sales from new products this past holiday season, Freed says.
ForeSee and predictive analytics helped retailer Perry Ellis International measure the value of the ways the company’s sales associates interacted with customers like greeting them at a store entrance or helping them in fitting rooms by recommending related fashion items, according to Forbes.
ForeSee used predictive analytics to predict that shoppers who received such attention from store associates would potentially spend about 50% more on Perry Ellis merchandise than consumers who weren’t given the same attention, Freed notes.
During the holiday season, NFLShop.com, the official store of the National Football League, learned that the female consumers who visited the site weren’t happy with their shopping experiences, according to Forbes.
Initially, the online retailer assumed that the women were shopping for holiday gifts for the men in their lives, but predictive analytics proved that to be a false assumption, Freed tells Forbes.
Rather, data from ForeSee indicated that women were logging on to NFLShop.com to buy merchandise for themselves.
After getting that information, NFLShop.com sent its catalog out to more women, launched a television ad campaign targeting women and added merchandise such as jerseys made especially for women, according to the article.
As a result, NFLShop.com’s year-over-year online sales rose by 25%.
“They identified an unmet opportunity – not by trial and error, but by using analytics,” Freed notes.
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Spotfire Blogging Team