AI Pet Product Recommendation Platform
Challenge
An Australian pet e-commerce brand needed to replace generic product recommendations with personalized suggestions based on each pet's breed, age, diet, allergies, lifestyle, and purchase behavior. Generic bestseller lists often failed to account for individual pet needs, while product matching and subscription box curation were handled manually. The business also lacked effective feedback loops and transparent recommendation logic, making it difficult to adapt suggestions as customer preferences and pet needs changed.
An Australian pet e-commerce brand needed to replace generic product recommendations with personalized suggestions based on each pet's breed, age, diet, allergies, lifestyle, and purchase behavior. Generic bestseller lists often failed to account for individual pet needs, while product matching and subscription box curation were handled manually. The business also lacked effective feedback loops and transparent recommendation logic, making it difficult to adapt suggestions as customer preferences and pet needs changed.
Solution
Starling Elevate developed an AI-powered pet product recommendation platform that analyzes detailed pet profiles and matches products according to breed, dietary requirements, allergies, lifestyle, and purchase history. The solution uses Claude on AWS Bedrock, machine learning models, and PostgreSQL to support product scoring and personalized recommendations. It includes AI-powered pet profile analysis, intelligent product matching, personalized product discovery, subscription box personalization, automated subscription workflows, customer behavior analysis, and continuous optimization based on feedback and order data.
Starling Elevate developed an AI-powered pet product recommendation platform that analyzes detailed pet profiles and matches products according to breed, dietary requirements, allergies, lifestyle, and purchase history. The solution uses Claude on AWS Bedrock, machine learning models, and PostgreSQL to support product scoring and personalized recommendations. It includes AI-powered pet profile analysis, intelligent product matching, personalized product discovery, subscription box personalization, automated subscription workflows, customer behavior analysis, and continuous optimization based on feedback and order data.
Results
The AI recommendation platform improved product discovery and customer engagement by matching products with individual pet profiles, dietary needs, allergies, lifestyle, and purchase history. It reduced manual product curation efforts and created a more relevant shopping journey for customers.
The AI recommendation platform improved product discovery and customer engagement by matching products with individual pet profiles, dietary needs, allergies, lifestyle, and purchase history. It reduced manual product curation efforts and created a more relevant shopping journey for customers.