Temple and Webster increases engagement by 13% with Marqo's AI-powered recommendations
Company Overview
Temple & Webster is Australia’s leading online retailer for furniture, home décor, and home improvement products. With over 200,000 SKUs spanning indoor and outdoor furniture, lighting, rugs, and appliances, the platform serves hundreds of thousands of customers annually across Australia.
As a pure-play eCommerce business, Temple & Webster’s on-site search and discovery experience is central to customer engagement, product discovery, and transaction conversion — particularly for high-consideration, style-driven purchases like furniture.
Challenge
With a growing catalog and rising expectations for personalized shopping experiences, Temple & Webster needed a better way to help customers discover aesthetically complementary products. Their legacy recommendation system was falling short in several key areas:
Inability to suggest visually harmonious items across categories. For example, pairing a Scandinavian Sofa with a matching Coffee Table or Rug.
Recommendations lacked awareness of design principles like color, material, or era mixing.
Missed opportunities to drive cross-category inspiration and bundle discovery limiting basket size and user satisfaction
Generic, rules-based algorithms failed to engage users browsing for style cohesion
The business needed a smarter, more flexible product discovery solution to increase add-to-cart rates, average order value, and reduce abandonment.
Solution
Temple & Webster partnered with Marqo to elevate their recommendation experience using AI-native, multimodal vector search built for visual merchandising. Within weeks:
Marqo powered a new recommendations engine that understands visual aesthetics
Pairing items based on color, material, and design language — not just metadata
Vision transformers were used to analyze product imagery and embed visual meaning
Enabling suggestions like "rugs that complement this velvet sofa" or "lamps that match this sideboard"
Complementary recommendations boosted engagement and time on site
Helping shoppers build room looks — not just fill carts
Results
After a production A/B test involving 10% of website traffic, Temple and Webster achieved a substantial improvement in key business metrics and customer experience:
13%↑
13% increase in engagement rate on recommendations for product listings pages.
Higher relevance, improved user experience
Marqo's results are image driven and aesthetically complimentary to the product shown in the product display page, improving look and feel
What This Means
For a visually driven eCommerce brand like Temple & Webster, where style coordination and design intent drive purchasing behavior, rule-based recommendation engines simply weren’t enough.
By implementing Marqo’s AI-native visual recommendation engine, the company:
Transformed product discovery into a style-led, inspirational journey
Increased shopper engagement by 13%
Unlocked new upsell and bundle opportunities across product categories
Future-proofed merchandising with adaptive, AI-driven recommendations
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