Retail
Turning Big Data & Gen AI into Personalized Grocery Experiences
Client
Major Canadian Retail Conglomerate
Industry
Retail & Consumer Goods
Services
Gen AI
Duration
Enterprise Grade
Executive Summary
Engineering resilience through Major Canadian Retail Conglomerate's transformation.
The client sought to transform its massive customer-dataset via its loyalty program into truly personalized shopping experiences, predicting what each customer would buy and when. The retailer transitioned from static homepage content to real-time, adaptive variants driven by Gen AI.
The Personalization Challenge
- Leverage massive loyalty program data for individual personalization at scale.
- Move beyond generic segmentation to predictive, 1:1 customer experiences.
- Integrate realtime generative content without compromising site performance.
- Ensure privacy and data security while utilizing customer purchase history.
AI-Driven Personalization Engine
- Built a data pipeline using BigQuery to aggregate and analyze customer behavior.
- Implemented GenAI models on Azure/OpenAI to generate personalized product copy.
- Developed a real-time recommendation engine serving dynamic content via React.
- Established automated feedback loops to continuously refine model accuracy.
Measurable Outcomes
Engagement Metrics
3x
Increase in click-through rates (CTR) on personalized homepage banners.
15%
Uplift in average basket size for customers engaging with AI recommendations.
Hyper-Personalization at Scale
By combining big data with Generative AI, the retailer successfully delivered unique shopping experiences to millions of users, significantly boosting engagement and revenue per visit.
Technical Stack
BigQueryGoogle Cloud PlatformOpenAIReact
Core Disciplines
RetailGenAIPersonalization
