Brick & Mortar Retail Drives into the Red Zone with Next-Gen Analytics
The following is a guest post from a Data Innovation Day partner.
After sweeping up the debris left by enthusiastic shoppers, brick and mortar retailers around the country are scoring their Black Friday. Traditionally, their measure of success has been a simple one: Did I sell more this Black Friday than I did last year? If so, time to dump the ceremonial Gatorade on the CEO.
But what does a year-over-year change in sales really tell retailers about the performance of their organization – its ability to draw customers into the store, offer a compelling in-store experience, and close a sale? Not much.
After all, macroeconomic factors like the unemployment rate or Superstorm Sandy greatly impact year-over-year sales across all retailers, regardless of how well or poorly they’re run. A big Black Friday could be a sign of organizational excellence – or just dumb luck.
The savviest brick and mortar retailers have adopted a new generation of analytics tools designed to give them a clearer picture of how they’re doing. For instance, retailers can use Euclid Analytics to compare the effectiveness of different window displays by looking at the percentage of passers-by who are drawn into the store, or track the performance of a direct mail campaign by measuring average visit frequency before and after the mailing. Feedback comes back in hours, not months, enabling retailers to quickly iterate and improve.
How does it work? The answer, not surprisingly, is Big Data. Retailers instrument their stores with sensors that collect information about what shoppers do in store before the point of sale. Next, shopper analytics tools turn these mountains of raw data into actionable metrics that can be used to identify best practices, fix underperforming operations, and optimize performance across the company.
So while it never hurts to be lucky, lucky and good is a combination that’s hard to beat.
Will Smith is CEO and Co-Founder of Euclid, which delivers breakthrough shopper analytics for offline retail.