Business Impacts
Enhanced Click-Through Rate (CTR) in search results
Elevated Shopping Experience through Personalization
Improved Relevance of Search Results
Customer Key Facts
- Country : India
- Industry : Fashion
- About : Zaamo is an Indian retail brand that enables influencers and content creators to bespoke clothing collections and customers to shop from Zaamo's website and app platforms.
Enhancing Zaamo’s search and recommendations
Zaamo employed a rule-based recommendation algorithm and a text-based search engine to provide product recommendations to its customer base. Acknowledging the ever-evolving landscape of AI-driven solutions, Zaamo sought to enhance its capabilities through the adoption of Google’s advanced Discovery AI technology. This strategic move was intended to leverage Google’s Retail Search and Recommendations AI functionalities, promising a tangible uptick in customer satisfaction and product relevance for Zaamo.
Challenges
- Limited availability of user events data, a critical component for deriving valuable insights and elevating the customer experience
- Dependence on a single product catalog data source, potentially constraining the diversity and accuracy of product recommendations
- Mapping user events with requisite parameters necessitates a systematic approach and data integration efforts to enhance the quality of recommendations
- Irrelevant product recommendations and limited search functionalities for end-users, resulting in a decline in overall customer satisfaction
Technologies Used
Google Big Query
Google Retail Search
Google Cloud functions
Google Recommendations AI
Google BigQuery Data Transfer Service
Google Cloud Scheduler
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
