A Leading Seafood Processing and Retail Company Optimized Pricing Strategies with AI-Driven Forecasting Using Google BigQuery, Vertex AI, and Looker
Overview
A major player in seafood processing and retail, faced pricing challenges due to external factors such as market demand and weather conditions. Relying on manual, experience-based pricing methods led to inconsistent pricing and missed revenue opportunities. Partnering with Applexus, the company implemented a data-driven approach using AI and ML to optimize pricing strategies.
Major benefits realized by our client
- Automated Pricing Processes: Reduced manual decision-making, enabling dynamic pricing adjustments.
- Improved Profitability: Optimized pricing strategies in response to market fluctuations and external factors.
- Enhanced Pricing Transparency: Allowed for data-driven decision-making across the enterprise with better visibility into pricing structures.
How We Did It
- Data Harmonization: Integrated SAP and non-SAP data sources, including external data such as weather patterns.
- Centralized Data Repository: Leveraged Google BigQuery as a central data repository, ingesting SAP data for unified insights.
- Machine Learning Models: Developed AI-driven price forecasting using Google’s Vertex AI, analyzing historical sales, POS data, and external market conditions.
- Real-Time Analytics: Implemented visualization dashboards using Google Looker to identify pricing patterns and trends.
Client
Food & Beverage Processing
Solution
Google BigQuery, Vertex AI, SAP Datasphere, Looker Analytics
At a glance
By deploying an AI-driven pricing model, the client now has an automated, data-driven pricing strategy that adapts to market conditions in real-time. This transformation has led to improved profitability, enhanced pricing consistency, and increased transparency in decision-making across products and regions.
