Unlocking Tech Innovation in Retail Execution

Retail execution is becoming more automated with the advancement of tools like image recognition. No longer do field representatives have to rely on manual, time-intensive processes. However, these tech implementations require investment, including tech stack integration, workforce onboarding, and technology maintenance.In this chat, Sara Clarkson, president and CEO of Marketsupport Canada, and Matthew Brogie, CEO of Repsly, dive into best practices for overcoming these challenges and share how image recognition is helping to unlock next-level innovation in the CPG and retail space. Clarkson leads Marketsupport in Canada, which provides resources to brands, manufacturers, and retailers. She works with a number of different CPG brands and retailers, providing them with support services across Canada. Brogie leads Repsly, a retail execution platform used by brands and merchandising service organizations like Marketsupport to drive efficiency in the field. They provide insights into how brands and merchandising organizations can optimize how their products are sold on the shelf. Brogie and Clarkson spoke on the evolution of retail execution, which has led to the adoption of image recognition. At first, the technology was difficult to reach, but with time, image processing costs have been reduced and AI training has only improved in accuracy.Adoption hasn’t always been easy. It can be difficult to communicate the value, and Clarkson suggests having a compelling case study on hand to show stakeholders what the actual impact might be. Onboarding is another complex step, says Brogie. Getting up and running involves navigating metadata and accessing the right information for the right use case. Training AI, while getting easier and faster, still requires heavy maintenance, particularly for companies with hundreds of SKUs that also need to train image recognition for seasonal packaging, new products, etc. Much of the information comes from retailer POS data, and being able to hand that off to representatives can make a significant difference out in the field. It creates efficiencies on the floor and also helps the retailers in the back-end, they say. Regarding ROI, companies need to determine what type of model they’re pursuing and how they’re going to measure value. A straightforward use case might mean a rep walks into a store, takes a photo, and then goes about their business. However, adding in things like A/B testing, analysis of higher value tasks and locations, APL compliance gaps, planogram compliance gaps, and display compliance gaps introduces several moving parts and requires a heavier measurement tactic.The key is beginning with small, manageable benchmarks, say Brogie and Clarkson. For example, reps can recreate planograms on the shelf when they’re finished taking a photo, and the photo captures their accuracy, identifying any anomalies, to ensure they reach their threshold or KPI, such as 95% compliance. According to Brogie, these technologies will only continue to become more affordable, making it a valuable long-term strategy. Image recognition is going to make more data available at a lower cost. Through data integration advancements, insights are coming through much faster and more accurately with increased accessibility for field representatives. Now there’s also the capability for AI-powered automatic feedback, making the data much more actionable.

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