How We Partnered with Bayer to Leverage Machine Learning & Optimize Pricing Analytics
AI-Enabled Pricing Tool Drives Profitability Growth
At a glance
CLIENT
Bayer
SERVICES
- Artificial Intelligence
- Strategy
- Data & Analytics
INDUSTRIES
- Life Sciences & Healthcare
- Consumer
Pricing strategy has long relied on oversimplified, static models, but artificial intelligence (AI) is a game changer. We partnered with Bayer to develop a smart pricing tool using machine learning to deliver insights about how a price change could impact sales and volume transfer across all brands, internal and external.
The Price of Change
Amid economic pressure, consumers and retailers are more price conscious than ever. This trend, combined with the explosion of data, means that competition is growing and becoming more sophisticated.
Bayer, a global leader in consumer health, wanted to better leverage its data around price elasticity to drive growth in the context of smart brand positioning.
Together, Bayer and EPAM built an AI-powered tool that uses machine learning to assess pricing effects across its over-the-counter products in the consumer health industry.
The result is better analytics and better ways of working. The tool has helped upskill net revenue managers (NRM) and brand managers significantly, leading to multi-million Euro impact.
BY THE NUMBERS
Up to €20-30M
Incremental yearly profit, based on the first global MVP
€10M+
Estimated revenue gain from POC
10x
Estimated time savings on analytics
35+ countries
Using tool for price optimization
PRICE OPTIMIZATION
Designing the Future: A Holistic AI-driven Category Model
For many retail and consumer health companies, pricing remains largely a manual process, relying on static, oversimplified models, which do not capture the full complexity of market dynamics. In addition, methods might differ between markets and categories, limiting the ability to grow global capability.
Today, better data combined with AI offers the opportunity to reimagine decision-making. To that end, Bayer aimed to develop a more comprehensive tool to standardize pricing analytics across geographies and to democratize access to granular analytics. An AI-driven pricing tool is a timely response to existing macro challenges:
Consumers becoming more value-conscious and price-sensitive
Increasingly sophisticated competition
Growing negotiation power from retailers and pharmacies
Generally tighter margins and budgets in a more complex market
SOLUTION HIGHLIGHTS
Using AI to Build a Smarter Pricing Tool
EPAM supported Bayer across the entire initiative — from strategic vision and design to actual delivery — making sure every step was aligned with Bayer's overarching business objectives. Together, we made the solution real by crafting a holistic AI-driven model that can:
-
Predict sales more accurately
-
Consider complex interdependencies across brand, sub-brand and product levels
-
Measure elasticities across brands and total category effects, both within Bayer and externally
-
Accurately track volume transfers among products
-
Reveal how price changes for one product could impact sales of other products
-
Deliver "what-if" scenario planning capabilities to assess potential market impacts
Bayer’s brand managers and business analysts now have data-driven insights, strengthened by confidence scores, available to guide smarter pricing decisions.
FUTURE FOCUSED
Staying Ahead of the Competition
With the help of AI, what was a manual, time-intensive process can now be streamlined. With access to data-driven insights, Bayer can make faster, consumer-focused decisions and achieve smarter, revenue- and profit-optimizing pricing strategies, while simultaneously considering brand priorities. The tool allows for far superior analytics, powering improved pricing management processes and better ways of working. We are proud of our partnership with Bayer, using AI to drive value and stay ahead of the competition.
TECH STACK
PARTNER WITH US
Find out how AI and machine learning can reimagine your ways of working.