Solution

Quantiphi harnessed Google Discovery AI standards to meticulously engineer the data, establishing a standardized schema that seamlessly integrates with Google’s Retail Search and Recommendations AI
Quantiphi imported Zaamo’s data into the Retail Search and Recommendations AI console, ensuring that all relevant data was readily accessible and primed for in-depth analysis
Leveraging the wealth of product catalog data from Google Merchant Center and the invaluable user events data sourced from Google Analytics 4 (GA4), Quantiphi diligently ensured the meticulous analysis and transformation of both datasets to meet the prerequisites for implementing Discovery AI in the context of Retail Search and Recommendation AI
Quantiphi empowered Zaamo’s web application with a suite of Google Retail Search features, encompassing Intelligent Search, Dynamic Faceting, Pagination, Filtering, and Ordering
Additionally, Quantiphi equipped Zaamo’s web app with Google Recommendations AI capabilities, including the recommendation of Similar Items, “Others You May Like,” and “Recommended for You” products

Results

Elevated user experience through personalization by enhancing search relevancy and optimizing product recommendations
Improved relevance of search results, guaranteeing users access to accurate and helpful information for their search queries
Optimized shopping experience through personalization by tailoring user experiences within Zaamo’s web application