Revolutionizing retail merchandising with smart technology
PepsiCo, one of the largest food and beverage companies in the world, takes a deeply customer-centric approach to in-store merchandising and accessibility. Producing iconic brands such as Pepsi, Lay’s, and Gatorade, which are enjoyed by consumers a billion times a day, makes strategic product displays, share of shelf, and optimal stock levels extremely important for optimal customer experiences. PepsiCo understands that meeting and exceeding these customer experience objectives means leveraging advanced artificial intelligence and analytics to drive informed strategies and decision-making.
That’s why PepsiCo embarked on a transformation journey in 2021, seeking an innovative PepsiCo Shelf Intelligence solution to revolutionize its retail operations.
Collaborating with technology leaders Grid Dynamics and Smartlook, PepsiCo needed to overcome the limitations of traditional retail shelf intelligence approaches, automate the merchandising process, and optimize the cost of ownership. The case study shows how they tackled it with edge AI and computer vision to audit shelves in seconds, guide merchandisers in real time, and capture trusted data for decisions.
Download the full case study for the architecture, results, and rollout playbook.
What’s inside
- A mobile-first, on-device recognition engine that identifies SKUs and price tags, compares to planograms, and prompts corrective actions.
- A deep learning pipeline that blends object detection and OCR to map prices to products with high accuracy.
- Feature set built for retail operations: retail space audits, shelf share analysis, price monitoring, POPM checks, automated reporting, and on-shelf availability.
- Outcomes and benchmarks related to cost savings and operational efficiency, recognition accuracy and performance, integration and security, and technical improvements.
Get the full case study to see how the PepsiCo Shelf Intelligence solution turned shelf vision into measurable revenue impact, and how to replicate it at enterprise scale.
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