GCPExploringEvidence: Medium65/100

Merck Life Science: Vertex AI + BigQuery product recommendations and supply-chain ML

Use case typePredictive decision supportUpdated Jun 13, 2026

Life Science business of Merck KGaA Darmstadt, Germany moved its data stack to Google Cloud to improve insights for product discovery and supply-chain planning. The company combined ERP and Google Analytics data in BigQuery, then used Vertex AI to build buy-it-again and personalized product recommendation models, similar-product comparison grids, and supply-demand forecasting models. The article also says Merck Life Science is exploring generative AI dashboards to explain demand spikes and summarize customer feedback.

Organization
Merck Life Science
Industry
Pharma
Location
Germany
Published
February 2025

Reported outcomes

Impact: +400%

Other quantified impact

Impact: +650%
Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Quantified impact: 400% increase

Google Cloud Customer StoryFeb 21, 2025Customer storyInferred claimMedium evidence strength

Product-comparison page traffic increased by 400%.

Normalized claim

Quantified impact: 650% increase

Google Cloud Customer StoryFeb 21, 2025Customer storyInferred claimMedium evidence strength

Looker ecommerce dashboard traffic increased by 650% in two years.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
Customer
Merck Life Science
Provider
GCP
Maturity
Exploring

The article also says Merck Life Science is exploring generative AI dashboards to explain demand spikes and summarize customer feedback

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 4

  • 1Product recommendation
  • 2Supply chain optimization
  • 3Predictive analytics
  • Migrated the data stack to Google Cloud.
  • Combined ERP and web analytics data in BigQuery for near-real-time insights.
  • Built buy-it-again and personalized product recommendation models in Vertex AI.
  • Used algorithms to highlight differences in product-comparison grids.
  • Built machine-learning models in Vertex AI to support supply-demand forecasting and anomaly analysis.
  • Used Looker dashboards to democratize access to business data across departments.
  • Explored generative AI dashboards for demand-surge explanations and customer review summarization.
Technologies
BigQueryVertex AILookerGoogle Analytics
  • Product-comparison page traffic increased by 400%.
  • Looker ecommerce dashboard traffic increased by 650% in two years.
  • The company said product recommendations are a huge revenue driver.
  • The supply-chain models help meet fluctuating demand and reduce inefficiencies.
Sources & evidence1
Evidence: Medium65/100Evidence strength
  • Customer explicitly identified
  • Deployment status explicitly supported
  • Primary source available
  • Quantified outcome available
  • Technical implementation details available
Type: Customer StoryPublished: Feb 21, 2025Publisher: Google CloudEvidence: PrimaryConfidence: High
Primary source

AI-generated summary. Verify important details with the linked sources before relying on this case.

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