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Manufacturing / Beverage
Azure Databricks, Azure Machine Learning, Azure Data Ingestion
Enhanced accuracy, engagement, forecasting, and decision-making through optimized models and dashboards.
AB-InBev is a leading beverage company. It leverages advanced technologies and data-driven strategies to optimize its operations, enhance customer engagement, and deliver superior products. By doing so, AB-InBev positions itself as a leader in the competitive global market, driving growth and ensuring long-term sustainability.
Improvement in Sales Forecast Accuracy
Increase in Model Accuracy
Increase in Customer Engagement
AB-InBev faced challenges in optimizing its rewards system, managing data from multiple sources, and developing automated challenge recommendations. They wanted a scalable, cost-efficient solution to enhance ROI and decision-making.
• Developed data pipelines to integrate and clean data from Snowflake, SQL Server, and SharePoint.
• Performed feature engineering and model tuning to enhance prediction accuracy.
• Created and optimized a custom challenge assignment model using business rules.
• Integrated models with AB-InBev’s BEES application via KPI endpoints.
• Implemented precise BMI calculations for rewards and challenges.
Improved model accuracy by 15%, boosted customer engagement by 25%, and increased sales forecasting precision by 30%, with interactive dashboards enhancing decision-making efficiency.
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