Operational Intelligence for
Brick-and-Mortar Retailers

Providing a Personalized, In-Store Shopping Experience

Leveling the Playing Field with Online Competition

E-commerce has trained shoppers to expect the convenience and personalization of online shopping — daunting challenges for traditional brick-and-mortar retailers to match. While e-commerce sites track detailed information about logged-in shoppers, sales personnel in brick-and-mortar stores do not have ready access to this information.

ScaleOut’s in-memory computing technology provides the operational intelligence that retailers need to deliver a highly personalized shopping experience and compete effectively with e-commerce. By integrating real-time information from mobile apps, tagged merchandise, and point of sale terminals, they can provide instant feedback to sales staff and dramatically improve the shopping experience.

Enabling Personalized Selling

Operational intelligence analyzes both a customer’s historical profile and current shopping activities in real-time to provide compelling suggestions, such as matching the store’s current promotions and a shopper’s immediate interests.

Tracking Inventory in Real Time

Operational intelligence can combine real-time information from RFID merchandise tags with opt-in tracking of shopping activity to ensure that the right products and sizes always are at hand, while also minimizing inventory costs.

Operational Intelligence in Action: A Scenario

Operational intelligence enables impressive new capabilities for brick-and-mortar retailers. Here’s a sample scenario that demonstrates how it enhances the in-store shopping experience. It starts with the retailer offering an opt-in mobile app to its customers which signals to a back-office system when they arrive at the store. By analyzing each customer’s preferred brands and sizes based on their buying history, this system (described below) uses operational intelligence to send timely, targeted recommendations to the sales staff at the point of sale. This empowers the staff to provide a highly personalized shopping experience. In addition, RFID tags enable the system to track the location of products throughout the store so that sales staff can immediately retrieve needed merchandise from the stockroom.

This use of operational intelligence integrated with mobile and RFID technologies gives brick-and-mortar retailers a powerful new tool for personalizing the in-store shopping experience in a manner that cannot be matched by online shopping. It also enables them to minimize inventory costs with precise tracking similar to that used by large, e-commerce companies.

How In-Memory Computing Enables Operational Intelligence

ScaleOut’s in-memory computing technology gives retailers the ability to implement operational intelligence that tracks large numbers of both shoppers and RFID tags in real time and provides immediate, highly personalized feedback to sales personnel. The following diagram illustrates the flow of real-time activity information from the sales floor into ScaleOut StateServer Pro’s scalable, in-memory data grid. The grid maintains an in-memory model of active shoppers which is enriched with historical information about their preferences retrieved from disk. An integrated, in-memory compute engine analyzes shopping activity and creates real-time alerts and product recommendations for sales personnel, enabling them to create a highly personalized shopping experience.

Personalized Shopping

Using In-Memory Computing for Operational Intelligence

The in-memory data grid also tracks inventory as it moves within the store, ensuring precise inventory control and that needed products can be immediately located. The operational intelligence derived from RFID-based inventory tracking also gives retailers deep insights into the dynamics of their inventory. For example they can identify which products are selected but not purchased so that they can further refine recommendations, and they can use these insights to negotiate with their suppliers.

Integrating Operational Intelligence with Big Data

Over the last several years, brick-and-mortar retailers have adopted big data techniques to analyze large volumes of historical customer data held in their data warehouses. This has allowed them to detect significant shopping trends and create marketing programs that maximize revenue. For example, by clustering purchasing patterns both for shoppers with similar profiles and for related products, they can detect important trends that influence their overall strategies.

Although big data analyses typically require days or weeks to complete, the information harvested from them, such as special product pricing, can be fed into operational intelligence for immediate use. The in-memory data grid can retrieve this information from disk and integrate it into its real-time recommendations, thereby combining big data analysis with operational intelligence to give retailers yet another competitive edge.

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