Normalized claim
Accuracy: 10 x increase
Demand forecasting became 10x more efficient with accuracy improving to 90%.
Super-Pharm optimizes ecommerce demand forecasting and merchandising with Vertex AI on Google Cloud
Use case typeDemand forecastingUpdated Jun 13, 2026
Super-Pharm, Israel’s leading pharmacy and beauty retailer, faced challenges in demand forecasting and inventory management due to limitations of on-premise infrastructure. The company migrated to Google Cloud and used Vertex AI for machine learning-powered demand forecasting improving accuracy from 50% to 90%. They automated product categorization using Gemini AI to optimize the ecommerce marketplace website. Improvements include 10x efficiency in demand forecasting, better inventory allocation, enhanced ecommerce user experience, and modernization of IT infrastructure. Partner WideOps supported cloud migration and Intellerts helped with AI system design and implementation.
- Organization
- Super-Pharm
- Industry
- Retail
- Location
- Israel
- Published
- March 2024
Reported outcomes
10x
accuracyQuality & accuracy
+90%accuracy
Strategic outcomes
Better decisions & insightImproved demand forecasting accuracyCustomer experience & trustImproved inventory allocation for faster deliveriesCustomer experience & trustEnhanced ecommerce user experienceEmployee experienceModernized infrastructure to attract talent
Catalog median for quality & accuracy deployments: +41% across 63 reported metrics. Compare benchmarks →
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Accuracy: 90% increase
Demand forecasting became 10x more efficient with accuracy improving to 90%.
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Super-Pharm
- Provider
- GCP
- Maturity
- Production
- Linked source
- Google Cloud Customer Stories
Modernized IT infrastructure attracting new talent and improving operational efficiency
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 4
- 1Demand Forecasting
- 2Inventory Optimization
- 3Ecommerce Personalization
- Inaccurate demand forecasting and inefficient inventory management leading to revenue loss and poor customer experience.
- Legacy on-premise systems lacked capacity and agility for large data volumes and complex analytics.
- Need to modernize IT infrastructure for competitive advantage and recruitment appeal.
- Migrated data and systems to Google Cloud.
- Leveraged Vertex AI with AutoML for demand forecasting models, improving accuracy and speed.
- Used BigQuery for data analytics and Gemini AI for automated product categorization on ecommerce platform.
- Partnered with WideOps for cloud migration and Intellerts for technical AI expertise.
Technologies
- Demand forecasting became 10x more efficient with accuracy improving to 90%.
- Improved inventory allocation for faster deliveries and better customer satisfaction.
- Enhanced ecommerce site user experience using AI-driven recommendations.
- Modernized IT infrastructure attracting new talent and improving operational efficiency.
Architecture
Uses Vertex AI AutoML for demand forecasting, BigQuery for analytics, Gemini AI for automated product categorization, and Google Cloud infrastructure supporting ecommerce and inventory.
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: Mar 1, 2024Publisher: Google Cloud Customer StoriesEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
Explore related AI use cases
Customer evidence
Provider evidence
Browse the catalog
Was this useful?
Community
Comments
No published comments yet.