How AI Commerce Search works

This page introduces you to the many features that drive AI Commerce Search.

The AI Commerce Search engine

AI Commerce Search uses state-of-the-art AI and machine learning models to deliver its search capabilities. Google technology enables advanced query understanding and personalization, improving search results from the broadest queries.

The service uses user interaction and ranking models to meet specific business goals and optimize product ranking for increased conversions and sales, effectively matching product attributes with website content for relevant product discovery.

Guided search serves users an interactive search experience to refine and narrow broad search queries through dynamic filtering and product image tiles. The service also offers semantic and back-and-forth conversation to facilitate an interactive ecommerce experience in real-time.

The fully managed AI Commerce Search service lets you:

AI Commerce Search handles data processing to:

End-to-end search

The autocomplete search service provides comprehensive search and a personalized shopping experience.

Additional resources are available to help you integrate AI Commerce Search into your complete search flow:

Build your search interface

Refer to this documentation on each relevant page for instructions on how to integrate AI Commerce Search into your product search capabilities using any of these options:

  • The AI Commerce Search in Gemini Enterprise for Customer Experience console
  • The Merchandising console
  • The AI Commerce Search API

See the Reference guide for client libraries and REST and RPC resources.

Use AI Commerce Search for data insights and analytics

AI Commerce Search leverages user interaction and understands nuances behind customer behavior, context, and SKUs to optimize search results and deliver relevant recommendations, leading to possible improvements in click-through rate, search conversion and a drop in the No Results Found (NRF) rate. AI Commerce Search utilizes data for internal optimization and benefits customers by improving metrics.

Do more with your ecommerce data

After you upload product and user event data using AI Commerce Search, you can export that data into BigQuery to perform analytics, access Key Performance Indicator (KPI) dashboards, and generate sales forecasts. The first step is exporting your data into BigQuery. Once you have the data in BigQuery tables, you can input them into workflows that result in prebuilt Looker dashboards or sales forecasts using Vertex AI.

For more information, see the following topics: