Quick Overview
Bayer Australia combined Google Trends, weather, and climate data with Google Cloud’s machine learning technology to predict health trends, such as flu outbreaks, and target marketing efforts more effectively.
Bayer Australia
Company Size
~100,000 employees (Bayer global)
Revenue Range
~$50B annual revenue (Bayer global)
Primary Challenge
Predicting health trends to enable timely, targeted marketing campaigns
Key Metrics
\- Predicted 50% surge in flu cases with high accuracy\- Enabled more effective, timely marketing
The Problem
Traditional marketing relied on historical sales data and intuition, missing real-time health trend shifts.
The Solution
Integrated Google Cloud ML with real-time search, weather, and climate data to forecast flu outbreaks and optimize marketing timing and targeting.
Results
\- Successfully predicted flu surges\- Improved targeting and ROI of marketing campaigns\- Enabled proactive, data-driven marketing
Details
Industry
Healthcare & Medical
Departments
Marketing & Content
Data & Analytics
Use Cases
Data Analysis
Predictive Modeling
Campaign Management
Tags
Machine Learning
Predictive Modeling
Enhanced Decision-Making
Marketing Teams
AI Tools Used
No items found.
Sources
https://www.thinkwithgoogle.com/marketing-strategies/automation/machine-learning-predictions/https://www.vktr.com/ai-disruption/5-ai-case-studies-in-marketing/
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