Case Study: AI-Driven Grocery Price Prediction Engine for U.S. Retailers

Introduction

While real-time pricing insights provide a snapshot of today, the future of retail success lies in predicting what happens tomorrow. Prices on platforms like Walmart, Target, and Amazon Fresh change frequently due to stock fluctuations, competitor moves, and demand surges. Being reactive is not enough.

Actowiz Solutions collaborated with a national grocery brand in the U.S. to build an AI-driven price prediction model powered by data extracted via grocery APIs and real-time scraping.

Client Objectives

• Forecast price changes for top 300 SKUs over the next 7 and 14 days.
• Identify volatility patterns in product categories.
• Help marketing and revenue teams pre-plan campaigns based on upcoming price trends.
• Reduce reaction time to market shifts.

Core Challenges

• High variability in price data by location and time.
• Promotions and stockouts causing noisy signals.
• Need for scalable, accurate, explainable models.

Business Impact

🔹 87% Model Accuracy

• Validated against 30-day actual price logs.

🔹 Campaign Pre-Planning

• 10-day promotional plans now aligned with expected price movement.

🔹 Optimized Pricing Strategy

• Forecast data fed into internal pricing tools for smarter margin management.

🔹 Alert System Enabled

• Early warnings for sudden forecasted hikes/drops triggered pre-emptive actions.

Client Testimonial

"With Actowiz’s forecast model, we now predict the market—not just react to it. It’s changed how we approach pricing entirely.

— Pricing Director, National Grocery Brand USA

Conclusion

Predictive pricing is the future. With its AI-powered grocery price prediction engine, Actowiz Solutions enabled this U.S. client to act ahead of competitors. The result? Better campaign planning, higher margins, and a proactive pricing team.