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How Big Data Will Save the Physical Store

Reports of the physical retail store’s death have been greatly exaggerated. As a recent survey from the Cisco® Internet Business Solutions Group (IBSG) found, 93 percent of products sold in the United States are still bought in brick-and-mortar locations. And while technology has upended many product categories and more than a few individual retailers, it simultaneously creates opportunities for retailers to continue to make the store shopping experience both relevant and compelling. Big Data in the store is key to achieving this.

Big Data represents a convergence of emerging technologies that are creating vast new streams of information—along with the means to analyze them with near- or real-time efficiency. Though the torrent of raw information can seem overwhelming, once it is filtered and processed for its crucial, relevant insights, Big Data isn’t all that big. But the resulting profits and savings for physical retailers will be. In our paper “Surfing the Data Deluge: How Retailers Can Turn Big Data into Big Profits,” IBSG estimates a 54-percent after-tax profit gain for retailers once Big Data is implemented.

Three core sources of Big Data are video, social media, and mobile devices, all of which are key elements in the transformation of the in-store experience. Many existing retail business-intelligence strategies focus on influencing future shopping trips—perhaps analyzing a market basket after the fact, then planning a coupon or special offer. Big Data can go much further, impacting the in-store experience that customers are having today.

From a store-operations perspective, Big Data promises unprecedented sense-and-react capabilities. Wireless sensors and video cameras—from the parking lot to the checkout counter—can compile a much richer set of data and, when combined with external data streams such as social media, weather, or other events, can enable precise, instant predictions. These will anticipate where shoppers are going, what products need to be restocked, and which customers need assistance to convert a sale. Factors such as gender, age, buying history—even the posture, mood, and common behaviors demonstrating the indecision of a consumer—can all be channeled into real-time, predictive actions, while the shopper is in the store.

With the advent of the Internet of Everything, sensors will connect nearly every cart, freezer, shelf, screen, product, associate, and customer throughout the retail setting. Today, store-level inventories are often inaccurate, causing out-of-stocks. With Big Data, these will become almost nonexistent as shelves and back rooms are replenished with exactly what is needed in that local store at exactly the right time. If the dairy section will run out of milk in the next 30 minutes, for example, Big Data will “know,” and the store can react. And before a herd of shoppers is suddenly building up at the checkout counters, the staff will be automatically notified so more checkouts can be opened.

On the customer side, Big Data can create a new level of personalized interaction.  IBSG surveys found that 71 percent of shoppers want more digital information while in the store. Price transparency, digital access to remote experts, and targeted offers, which they routinely get online, can be enhanced with Big Data and delivered in-store via mobile devices and interactive screens. Some retailers, such as Target, already provide in-store Wi-Fi so consumers can use their smartphones for real-time, personalized interactions. Consumers that “opt-in” and allow in-store tracking receive valuable and personalized interactions. While many consumers are wary of “tracking,” delivering real value creates a trusted relationship that can overcome these concerns.

Big Data in the Retail Store

Big Data in the Retail Store

For Big Data to transform the store in real time, a wave of emerging technologies will need to converge. These will include pervasive sensors (the Internet of Everything) and real-time, localized, predictive analytics, including machines that “learn” from the data. In turn, this convergence will drive new approaches to traditional store processes, including stocking, ordering, cashiering, and providing customer assistance.

The result will be new benchmarks for retail success—taking the traditional axiom of “right product, right place, right time, and right price” to unprecedented levels—and a physical store shopping experience that keeps the foot traffic flowing and the registers ringing. For more insights on Big Data, please read our report: Surfing the Data Deluge: How Retailers Can Turn Big Data into Big Profits.

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3 Comments.


  1. Interesting ideas. The convergence of data from different sources is interesting. We do need advanced analytics to combine the observations and turn them into inferences.

    Cheers

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  2. Big Data can show brick and mortar business exactly how their customers act in-store. This would be especially valuable to a clothing store or grocer–keep an eye on every single product as it comes in and goes out the door. Set alerts so you never run out. Forecast and plan for supply needs.

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  3. April 15, 2013 at 10:03 pm

    Huge opportunity with big data to do more dynamic pricing in store, as usage patterns can be detected for consumption of competing products, with real time changes to adjust to these changing market conditions. The nuggets of wisdom will need to be gleaned from the vast amount of “fuzzy data” that is not relevant or even “harmful” to the analysis being conducted. Totally agree with your points, Big Data has huge implications for retail!

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