Roaming Robots Reveal Real-time Retail Insights

by   |   June 20, 2016 2:02 pm   |   0 Comments

Peter Paul, principal scientist, PARC, A Xerox Company

Peter Paul, principal scientist, PARC, A Xerox Company

Retailers must constantly be at the top of their game and prepared to provide an excellent shopping experience to satisfy both new and loyal customers. New tools that collect unprecedented amounts of data can help them learn more than ever about how consumers shop.

For example, large retailers often find it a challenge to adjust their offerings and store layouts to satisfy local preferences. Video analytics can help streamline the creation of unique store profiles to understand traffic patterns throughout the store and determine optimal locations for merchandise, allowing retailers to deploy sale signage effectively and track and measure results accordingly.

Today, video data can be collected by robots that roam store aisles, scanning merchandise along the way. The robot travels around the store, capturing and processing information with a high-resolution set of cameras, recording where and how well the products are placed.

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In addition to aiding with individual store layouts, robotic automation can provide a full picture of which products are moving and which aren’t. Empty shelves are always an issue – they are a source of frustration for shoppers and mean lost sales for retailers. It can be especially agonizing when the product is in the store but hidden away in the back or misplaced due to retailer error or a customer moving it. It’s critical for retailers to keep sought-after products on the shelves. With automated video data collection, the retail workforce is empowered to act on the data faster to ensure that shelves are stocked and merchandise is in the correct location, making it easier for shoppers to find the items they are looking for and boosting sales.

Analytics robots moving through the aisles and collecting data also can ensure the accuracy of pricing labels. With a variety of items on sale every week, retailers have to get the pricing signage printed and on the shelves in time for the price change and then take it down at the right time, and analytics can help with this to ensure compliance.

A robot collects data about products on retail shelves. Click to enlarge.

A robot collects data about products on retail shelves. Click to enlarge.

Advanced analytics can be used to compare the number of shoppers moving through the store and the areas where they tend to congregate with the number of sales and which particular items are sold. Through this analysis, retailers can gain deeper insight into shoppers’ interests and decision making, enabling them to more effectively target merchandizing, signage, and promotions. And by monitoring wait times at checkout lines, retailers can determine the optimal employee schedules and react in real time, helping to eliminate long waits.

Improving the Customer Experience

In addition to optimizing store layouts and merchandise locations for retailers, these video data insights go a long way toward making their stores an attractive destination for shoppers. Stores are more than just places to purchase merchandise. They are places where friends and neighbors meet, where families can share bonding conversations during a shopping trip. Details like in-demand items being easy to find and neatly stocked, pricing labels that are accurate, and reasonable wait times at checkout all contribute to a positive overall shopping experience.

Thanks to advances in computer vision and video analytics, as well as human behavioral models, retailers can now measure sentiment, motivation, and satisfaction for shoppers and associates in real time. This creates opportunities for sales associates to recognize and help guests who have questions and want help at that time. In addition, such analytics can provide valuable feedback as to the effectiveness of associate intervention. Also, by measuring the number of shoppers and shopper engagement, the effectiveness of various point of sale, end-cap, and shelf displays can be tested. Are they attracting the desired attention? Do they inform shoppers sufficiently to affect buying behavior? Are guests happy with the prices they are finding? Are sales and product bundles easy to understand?

Of course, each of these questions informs the most important question: Will shoppers’ experience make them want to come back?

Ultimately, data analytics is beneficial to the retailer because the insights gleaned can increase operational efficiency and improve sales. However, what’s more is that these insights also are beneficial to consumers.

Principal Scientist Peter Paul is an area manager within the Video and Image Analytics Research Lab at PARC, a Xerox Company. He leads a Retail Innovations Research Program with heavy focus on Video Analytics applications.

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