What challenges did THE ICONIC face before AI implementation?

Existing models struggled with growing inventory and data volumes. Query times increased and data had to be connected across separate sources, creating friction in operations.

What was the impact of the AI solution?

Served two million active customers with over 20 million monthly visits. Reduced waiting time for analysis from minutes to seconds.

Rank#1,374of 3,449

Source

GCPEvidence: Medium50/100

THE ICONIC: Multimodal search and Gemini metadata tagging on Vertex AI for fashion ecommerce

Use case typeSearch modernizationUpdated Jun 3, 2026

THE ICONIC is Australia and New Zealand's leading fashion and lifestyle platform. It used Google Cloud data and AI services to improve search and discovery, connect data across sources, and deliver more relevant recommendations and image-based browsing.

Organization: THE ICONIC
Industry: Retail
Location: Australia
Published: June 2026

Reported outcomes

20,000,000 visits/month

monthly website and app visitsOther quantified impact

99%analysis waiting time2,000,000 customersactive customers

Strategic outcomes

Customer experience & trustImproved search and discovery experienceCustomer experience & trustFewer zero-result searches through similar and trending item recommendationsCompetitive differentiationDifferentiated against other ecommerce sites

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Analysis waiting time: 99%

Google Cloud Customer StoriesJun 3, 2026Customer storyInferred claimMedium evidence strength

"cutting down waiting time from minutes to seconds"

Normalized claim

Active customers: 2,000,000 customers

Google Cloud Customer StoriesJun 3, 2026Customer storyExplicit claimMedium evidence strength

"two million active customers"

Normalized claim

Monthly website and app visits: 20,000,000 visits/month

Google Cloud Customer StoriesJun 3, 2026Customer storyExplicit claimMedium evidence strength

"We have over 20 million monthly visits to our website and app"

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: THE ICONIC
Provider: GCP
Maturity: Unknown
Linked source: Google Cloud Customer Stories

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 3 of 3

1Search modernization
2Shopping recommendations
3Multimodal analytics

Existing models struggled with growing inventory and data volumes.
Query times increased and data had to be connected across separate sources, creating friction in operations.

Centralized data in BigQuery and used Vertex AI for multimodal search and recommendation.
Applied Gemini for image metadata tagging and tag generation.
Used multimodal search to recommend items by theme or intent and to break images into browseable pieces for Snap-to-Shop.

Technologies

BigQuery Vertex AI Gemini Google Kubernetes Engine Google Workspace

Served two million active customers with over 20 million monthly visits.
Reduced waiting time for analysis from minutes to seconds.

Architecture

THE ICONIC centralized and governed data in BigQuery, enabling real-time analytics and concurrent data streaming. Vertex AI multimodal search recommend items by theme or intent, including similar and trending products when a brand is out of stock. Gemini extracts image metadata and adds tags to expand search coverage, and Snap-to-Shop breaks images into browsable pieces.

Sources & evidence1

Evidence: Medium50/100Evidence strength