In Search of the Perfect Store
AI-driven tools help CPGs get a clearer picture of retail realities
Creating the “perfect store” environment for their products via flawless retail execution has long been the ambition of consumer packaged goods manufacturers. Now, thanks to emerging technologies, the perfect store is much less a Holy Grail and more a legitimate goal within reach.
Facilitating all phases of retail execution, from planning and forecasting to tracking and reporting, these technologies can help turn things around for the 65% of CPG companies that say poor in-store execution and compliance cost them between 1% and 5% in annual sales, according to a survey by tech solution provider Trax Retail. A significant number of these tools incorporate artificial intelligence and its subfields, including computer vision (CV) and machine learning.
AI-driven retail execution solutions deliver “perfect store” potential by optimizing each store location for product assortment, placement, pricing, promotions and service frequency, according to Jim Holland, PepsiCo’s director of sales capability, sales transformation.
At a recent industry event, Holland discussed how PepsiCo’s use of a CV-equipped mobile app has enabled the direct-store-delivery giant’s field associates to use smartphone cameras to photograph products in-store. The technology automatically identifies every item in the picture frame by SKU number, automating the time-consuming and often error-prone manual methods of data collection for auditing and compliance reports.
Getting a Clearer Picture
Whether embedded in a mobile app or included as part of smart-shelf technology that is becoming increasingly available, CV essentially places expert “eyes” in stores to help measure retailer compliance and proper execution from the sales reps. The technology also measures share of shelf and out-of-stocks, sometimes with sophisticated sensors that can generate replenishment alerts for immediate fixes and help identify supply-and-demand patterns for longer-term improvements.
Once the CV and machine learning tools “see” and analyze the content within digital images, deep learning – another subset of AI – takes things a step further by making inferences and predictions, thereby converting shelf images into insights on brand- and category-level performance. Together, these technologies can best humans at identifying and classifying products even if the packaging has recently changed, the units are misaligned on the shelf or the store’s ambient conditions aren’t conducive to crisp photography.
Since several departments are involved in a CPG’s perfect store strategy, proper implementation depends on a cross-functional vision with easy-to-execute instructions for all stakeholders – namely, the merchandising, shopper marketing, sales operations and field sales teams. So ideal retail execution solutions consolidate the field data in a central location accessible to all. Data centralization is necessary not only for big data analytics (yet another AI application), but also for instant accessibility to the entire team to foster better, and faster, collaboration.
“Centralizing retail-execution data onto a single platform allows for process improvements by providing on-the-go access and instant availability to multiple relevant data points,” says Mat Brogie, chief executive officer of Repsly, which provides AI-driven solutions for retail execution teams. “Using this technology, cross-functional teams can detect problems right away and implement solutions in time to reduce losses and maximize returns.”
Something to Talk About
Other technologies on the horizon include voice recognition tools that will facilitate question-prompted setup supports. Managers can create custom question prompts to guide assemblers through the setup process of merchandising programs and product displays – a capability that is becoming more important as those programs increasingly incorporate a variety of shopper-facing technologies.
Elsewhere, new smart shelf technology can improve productivity and expedite stocking by using LED lighting to color-code different sections of the planogram during the process.
According to the aforementioned Trax Retail survey, 79% of CPGs either have in place or will adopt a “real-time, eyes-in-store solution” in the next three years. That level of clarity at the store level should not only drive benefits for CPGs and their retail partners, but ultimately could help drive a more compelling in-store experience that will reap rewards for shoppers as well.
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