How Hibbett Eliminated Out-Of-Stock Roadblocks With Similar Recommendations
Hibbett · United States
Leading athletic-inspired fashion retailer Hibbett drove conversion by 2.4x by integrating Syte's out-of-stock suggestions, using Syte's visual-AI-powered product discovery solution to recommend similar items when a product is unavailable.
Overview
Leading athletic-inspired fashion retailer Hibbett drove conversion by 2.4x by integrating Syte's out-of-stock suggestions, using Syte's visual-AI-powered product discovery solution to recommend similar items when a product is unavailable.
The challenge
During the pandemic, various supply chain challenges led to out-of-stock scenarios for many retailers, including Hibbett. Because the bulk of Hibbett's sales come from footwear, when a specific size is sold out, recommending complementary products available in a customer's size is key. Prior attempts at offering product recommendations on the Hibbett website didn't go far enough to connect shoppers with relevant similar pieces.
The solution
Hibbett implemented Syte's Visual Discovery offering on its website and app, addressing out-of-stock challenges by suggesting similar pieces to shoppers through recommendation carousels and Syte's Discovery Button. Following A/B tests of Syte's features in different placements on product detail and listing pages, Hibbett found the winning position of the Discovery Button on the PDP -- with the prompt 'Out of Your Size? See Similar Items' -- directly below the sizing area. The technology was then also added to the Hibbett app.
Reported business value
Shoppers who used Syte solutions showed a 2.4x higher conversion rate, a 162% uplift in average revenue per user, and a 9.1% increase in average order value, compared to non-Syte shoppers on the website.
Sources
Open any source and check the claim yourself — that is the point of the register.
Other retail entries in the register.
Furniture.com Transforms Online Search with Databricks
Furniture.com unifies over 60 retail partners and 1.5 million SKUs on the Databricks Data + AI Platform, using Delta Lake, MLflow and Unity Catalog to run its ML lifecycle. Its Find It AI product-discovery tool uses generative AI to create a synthetic image representing shopper intent, then matches it against the product catalog for image-based search. A Collections model uses LLMs to automatically group related products, finding more than 16,000 collections across 50+ partners with no human intervention. Users who interact with Find It AI show a click-through rate 8x higher than baseline and a return rate 3.2x higher than baseline.
How Walmart Achieved Enterprise Transformation Through Digital Experience Innovation
Working with implementation partner Nativa on LivePerson's technology, Walmart customized and integrated conversational technology into its WhatsApp channel, including a FAQ-Transactional Bot to streamline searches, inquiries and purchases. The solution delivered a 60% increase in productivity and a 10 percentage point improvement in CSAT/NPS, along with operational savings through automated customer service processes.
Zalando enhancies customer engagement and operational efficiency with Mistral
Zalando, a European e-commerce platform, integrated Mistral models hosted on AWS Bedrock into its platform to add natural language processing and machine learning capabilities. The integration supports personalized recommendations, improved customer service and streamlined operations for the retailer's shopping experience.
McGee & Co uses Syte's visual AI to connect shoppers with complementary home decor pieces
Furniture and home decor retailer McGee & Co implemented Syte's visual search and AI tagging technology to tie products together, helping customers who find an item like an end table or couch also discover the complementary pieces from the same collection. Josh Batchelor, VP of Technology at McGee & Co, said the goal was to make sure shoppers are served complementary pieces when they need them.
Was this helpful?
Your feedback helps us improve our use case database