Retail Execution

2 Use Cases for Image Recognition in Retail Execution

Image recognition (IR) technology is revolutionizing the FMCG industry, especially in the realms of retail execution and compliance reporting. This technology allows for real-time analysis of the retail environment, offering insights that were previously difficult or time-consuming to obtain. Let’s explore two key use cases of IR technology that highlight its potential to transform in-store strategies: the “Space to Sales” analysis and the “My Perfect Store” program.

Editor’s Note: Contributing author is Dan Ray, Director of Customer Success at Wiser Solutions.

1. Space to Sales Analysis

The “Space to Sales” use case involves using image recognition to capture Share of Shelf (SOS) metrics instantly. A field rep can walk into a store, take a photo of the shelves, and the IR technology will analyze the image to determine the number of products on the shelf, brand presence, and prevalence. This data is then compared to category-level or regional sales data to identify the current SOS and the sales potential in the region. For instance, if a sparkling water brand accounts for 40 percent of category sales in the area but only occupies 25 percent of the shelf space in a store, the brand, as well as the store itself, is not maximizing its sales potential. The IR system can quantify this discrepancy and suggest that increasing the brand’s shelf space could lead to higher sales for the entire category within the store, and particularly for the under-shelved brand.

To put it simply, image recognition enables reps to instantly identify which of their own products are being under-shelved relative to their share of category sales, and identify which of their competitor products are be over-shelved relative to their share of category sales. The incorporation of sales data then gives the rep an estimate of the sales increase for the store that would happen by swapping out the over-shelved products, and swapping in the under-shelved products.

This actionable insight is valuable not only for immediate adjustments by the field rep but also for strategic discussions at the headquarters, potentially influencing negotiations with retail buyers.

2. My Perfect Store Program

The “My Perfect Store” program represents a strategic initiative aimed at optimizing a brand’s presence in retail stores to match an ideal setup that maximizes sales and brand visibility. Unlike compliance reporting, which checks for the presence or absence of expected items and setups, “My Perfect Store” focuses on what the optimal retail space would look like for a brand’s products. The ultimate goal is to establish a national (or global) strategy beyond standard compliance.

The challenge here is establishing a universal benchmark for what constitutes a “perfect store,” as store layouts, planograms, and market expectations can vary widely. Moreover, it is difficult to get and maintain accurate measurements, and it is too much overhead for in-store reps to collect and analyze required information.

Image recognition technology significantly aids in overcoming this challenge by allowing field reps to quickly capture a comprehensive view of the store’s setup. With IR, a rep can take photos that analyze and compare a majority of the necessary metrics against the “perfect store” benchmarks. This not only helps in identifying areas where a store falls short of these ideals but also highlights key opportunities for improvement. For brands willing to invest in this approach, IR technology provides a way to efficiently gauge how closely each store aligns with the “perfect store” model, pinpointing specific areas for enhancement.

Conclusion

Image recognition technology offers powerful tools for FMCG brands to refine their in-store strategies. Through “Space to Sales” analysis, brands can directly link shelf space allocation with sales potential, providing a clear path to optimized product placement.

The “My Perfect Store” program, on the other hand, uses IR to streamline the measurement of store compliance against ideal brand standards, highlighting discrepancies and opportunities for improvement. Both use cases underscore the technology’s value in enhancing retail execution, enabling brands to make data-driven decisions that boost sales and improve retail partnerships.

By harnessing IR, FMCG brands can navigate the complexities of retail environments more effectively, tailoring their strategies to meet and exceed both their own and their retail partners’ expectations.

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Better decisions can only come from better data.

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