Normalized claim
SKU daily updates: 7,000,000 SKUs/day increase
SKU daily updates grew from 100K to +7M
Grupo Casas Bahia case study: AI for retail search and recommendations
Use case typeShopping recommendationsUpdated Jun 13, 2026
Grupo Casas Bahia, an omnichannel retail conglomerate in Brazil, expanded its marketplace from thousands to millions of items and needed a more resilient search and recommendations layer. The company adopted Google Cloud Retail Search and Recommendations AI under Retail API to improve catalog updates, search relevance, and recommendation quality across its ecommerce brands.
- Organization
- Grupo Casas Bahia
- Industry
- Retail
- Location
- Brazil
- Published
- June 2026
Reported outcomes
Search-driven user conversion: +58%
Revenue & growth
SKU daily updates: 7,000,000 SKUs/dayClick-through rate: +28%Bounce rate: −4%Catalog loading time: 4–24 hoursIncome per app user: +28%
Catalog median for revenue & growth deployments: +40% across 67 reported metrics. Compare benchmarks →
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Search-driven user conversion: 58% increase
User conversion from search increased by 58%
Normalized claim
Click-through rate: 28% increase
Click-through rate (CTR) rose 28%
Normalized claim
Bounce rate: 4% decrease
Bounce rate dropped by 4%
Normalized claim
Catalog loading time: 4-24 hours decrease
Total catalog loading time reduced from 24 to 4 hours
Normalized claim
Income per app user: 28% increase
28% higher income per app user
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Grupo Casas Bahia
- Provider
- GCP
- Maturity
- PoC
- Linked source
- Google Cloud Customer Story
Grupo Casas Bahia ran a proof of concept with Google Cloud and chose Retail API for its three ecommerce brands
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 3
- 1Retail search optimization
- 2Product recommendations
- 3Ecommerce personalization
- Grupo Casas Bahia ran a proof of concept with Google Cloud and chose Retail API for its three ecommerce brands.
- It used Retail Search for internal search features and Recommendations AI for user-specific product recommendations.
- The solution learned from user trends to optimize sort order and improve search relevance over time.
- Click-through rate rose 28%.
- Bounce rate dropped by 4%.
- Income grew 28% per app user.
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: Jun 6, 2026Publisher: Google CloudEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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