Saving brick-and-mortar retail

The opportunities for retailers to tap big data are vast, as long as they avoid notable pitfalls.

“Big data will save brick-and-mortar retail,” claims Paul Schottmiller, a senior partner for Cisco® Consulting Services’ retail practice.

It’s a bold statement, but industry experts are bullish on the transformative prospects of in-store and online data. Retail success has always been achieved by getting the right product to the right customer at the right time, location, and price. And yet, retail has historically been a time-delayed business, with critical decisions made from outdated information.

“Retailers have always been forced to evaluate the past to inform the present and future. Last month’s inventory levels, last quarter’s marketing campaigns, last year’s holiday season. Even coupons are based on previous shopping trips,” Schottmiller explains. “But the industry is evolving. More than ever, retailers have the ability to gather information in real time, and influence the in-store experience as it is happening.”

What does this mean in dollars and cents? According to Cisco Consulting Services, retailers can realize an estimated 54 percent after-tax profit gain once big data analytics are adopted.1

The rise of sensors
The increase in retail opportunities is directly aligned with an increase in data sources:

  • In-store sensors, such as video cameras, Wi-Fi, and weight-sensing shelves
  • Location-based applications on smartphones
  • Social media and website data

“Big data is helping retailers shift from a review-and-revise model to a real-time, sense-and-respond model,” says Shaun Kirby, director of innovations architecture for Cisco Consulting Services. “But that’s only the first step. Once their capabilities become more sophisticated, they will be able to predict customers’ needs and desires as well as market and operating conditions, and prepare in advance.”

Sensors, in particular, are speeding up retail analyses and decision making.

  • Video cameras can give a wealth of information about foot traffic, behavioral patterns, inventory levels, safety incidents, and theft.
  • More advanced video analytics can detect a consumer’s demographics and biometrics; even hand gestures, eyeball movement, and emotions.

“Sensors are everywhere, but they are mostly siloed,” says Kirby. “The greatest value is found when multiple data sources are combined and analyzed, also known as ‘sensor fusion.’ This is when limited data sets of limited value can become truly transformative.”  

With more data and better analyses, retailers can:

  • Eliminate long lines and out-of-stock situations
  • Interact with consumers in real time, delivering targeted coupons, incentives, and expertise at the critical moment when a purchase is being considered
  • Make adjustments to inventory levels, product placements, labor resources, and customer services with greater speed and specificity

Whatever the use case, big data is helping retailers close traditional latency gaps, allowing them to improve their operations and enhance the customer experience faster than ever before.

Avoiding the “creepy factor”
While big data spells big opportunity, it can also present risk. As retailers learn more about consumers and collect personal details—including who and where they are and how they behave—they must straddle a fine line between insight and privacy, value and intrusion.

“Retailers need to avoid the ‘creepy factor’ at all costs,” warns Schottmiller. “Location matters and price matters, but brand image is huge. Once that image is tarnished or becomes untrustworthy, it can be a long recovery process.”

To stay on the right side of the fine line, retailers need to deliver two things:

  • Transparency
  • Value

“Transparency promotes trust, value promotes desire. Retailers must do both,” says Schottmiller. “Being secretive may allow retailers to fly under the radar for a while, but if those secrets are exposed, retailers will lose brand equity and customers.”

Being open and honest about the data being collected and how it is being used can help allay consumer fears over privacy. Many banks and big box retailers, for example, show their surveillance feeds at the front door, helping customers be aware of the feeds and understand their primary purpose is security related.

Retailers must also deliver value if they want consumers to readily accept their big data tactics. Having customers opt-in to programs is one way to foster transparency and deliver value.

“Customers will give up a measure of privacy if they get something in return,” Schottmiller explains. “But they don’t like too much noise, so the offers and services must be truly valuable. It’s a give-and-take proposition.”

1 “Surfing the Data Deluge: How Retailers Can Turn Big Data into Big Profits,” Cisco Internet Business Solutions Group, August 2012.

More information

Watch videos from Intel® about how retailers are using big data to generate profit, and what is unfolding for the future of shopping.