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
+58%
search-driven user conversionRevenue & growth
7,000,000 SKUs/daySKU daily updates+28%click-through rate−4%bounce rate4 hourscatalog loading time+28%income per app user
Strategic outcomes
Scale & capacityScaled catalog update capacitySpeed & agilityReduced catalog loading timeCustomer experience & trustImproved search-driven conversionCustomer experience & trustImproved search relevance and recommendations
Catalog median for revenue & growth deployments: +34% across 150 reported metrics. Compare benchmarks →
Primary read
Use case focus
Showing 3 of 3
- 1Retail search optimization
- 2Product recommendations
- 3Ecommerce personalization
- Marketplace expansion increased catalog scale from thousands to millions of items, making prior search and recommendation solutions less resilient, slower, and less accurate.
- The company needed faster catalog updates, better result quality, and improved conversion as third-party seller volume grew.
- 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.
- SKU daily updates increased from 100K to more than 7M.
- Total catalog loading time dropped from 24 hours to 4 hours.
- Search-driven user conversion increased by 58%.
- Click-through rate rose 28%.
- Bounce rate dropped by 4%.
- Income grew 28% per app user.
Sources & evidence1
Groundedness: 5/5Type: 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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