What challenges did Etsy sellers face before AI implementation?

Scaling personalized shopping experiences for nearly 90 million shoppers given a vast and changing inventory of more than 130 million items. Improving buyer intent understanding and SEO to better match buyers with relevant items.

What was the impact of the AI solution?

Achieved an 80x increase in item listings per theme through AI-powered curation. Generated nearly 90 million personalized shopping experiences for individual buyers. Increased SEO-driven visits by 5% and conversions by 3%. Enabled fast, scalable, and affordable AI-driven personalization at an unmatched scale in e-commerce.

Source

GCP

Etsy personalizes shopper experiences with Vertex AI, BigQuery, and Gemini on Google Cloud

Use case typeCustomer targetingUpdated Jun 13, 2026

Etsy is a global e-commerce marketplace with over 130 million items from more than 5 million sellers, serving nearly 90 million shoppers worldwide. The business challenge was to scale personalized shopping experiences given the vast and dynamic inventory, while enhancing understanding of buyer intent and improving SEO. Etsy created foundational datasets with Gemini models and leveraged Google Cloud AI technologies such as Vertex AI and BigQuery to deeply understand inventory, customer intent, and individual buyer preferences. They employed multimodal AI using images, videos, and text for enhanced search and discovery, and AI to personalize item recommendations and improve SEO-driven visits. The results included an 80x increase in item listings per theme, a 5% increase in SEO-driven visits, a 3% lift in conversion rates, and nearly 90 million personalized shopping experiences generated.

Organization: Etsy sellers
Industry: Retail
Location: United States

Reported outcomes

+5%

quantified impactRevenue & growth

80xquantified impact+3%quantified impact

Strategic outcomes

New product / capabilityScaled personalized shopping experiencesNew product / capabilityEnhanced search and discovery capabilitiesBetter decisions & insightImproved understanding of buyer intentCustomer experience & trustImproved SEO-driven shopping visibility

Catalog median for revenue & growth deployments: +34% across 150 reported metrics. Compare benchmarks →

Primary read

Use case focus

Showing 2 of 2

1Personalization
2Search & Discovery

Scaling personalized shopping experiences for nearly 90 million shoppers given a vast and changing inventory of more than 130 million items.
Improving buyer intent understanding and SEO to better match buyers with relevant items.

Built foundational datasets using Gemini models.
Used Vertex AI and BigQuery to analyze and understand inventory characteristics and customer intent.
Applied multimodal AI on images, videos, and text to enhance search and discovery capabilities.
Personalized item recommendations at scale to offer tailored shopping experiences.
Improved SEO by enhancing alt text generation for listings using Gemini models.

Technologies

Vertex AI BigQuery Gemini

Achieved an 80x increase in item listings per theme through AI-powered curation.
Generated nearly 90 million personalized shopping experiences for individual buyers.
Increased SEO-driven visits by 5% and conversions by 3%.
Enabled fast, scalable, and affordable AI-driven personalization at an unmatched scale in e-commerce.

Sources & evidence1

Groundedness: 5/5

Primary source

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