AI in Retail: From Recommendation Engines to Store Operations

Retail is one of the highest-ROI industries for AI investment. From personalised recommendations to supply chain optimisation, the applications are diverse and the returns measurable. Here's where we're seeing the biggest impact.

Recommendation Engines: The Proven Winner

Personalised product recommendations drive 35% of Amazon's revenue. For smaller retailers, collaborative filtering and content-based models can deliver significant uplift with relatively modest investment.

The key is moving beyond "customers who bought X also bought Y" to session-aware models that understand browsing intent in real time.

Demand Forecasting: Cutting Inventory Waste

Overstocking and stockouts cost retailers 3.5% of revenue annually. ML-based demand forecasting — incorporating seasonality, promotions, weather, and competitor pricing — reduces forecast error by 20-30% compared to statistical methods.

Visual Commerce

Computer vision is transforming product discovery. Visual search (upload a photo, find similar products) and virtual try-on (AR for clothing and accessories) reduce returns and increase conversion. We've built these systems for fashion and home goods retailers.

AI-Powered Customer Service

LLM-based chatbots now handle 70%+ of tier-1 customer service queries — order status, returns, product questions — without human intervention. The key is integration with backend order management systems.