The Evolution of Kit: Automating Marketing Using Machine Learning - Shopify
Mar 4, 2020

Summary
This post details the evolution of Kit from a rule-based system to an AI-driven recommendation engine. It describes the machine learning architecture for predicting marketing budget and likelihood of sales, utilizing regression and classification models trained on historical campaign data and store attributes. The system was migrated to Google Cloud Platform for training and prediction, with a real-time prediction architecture introduced to provide more dynamic recommendations, such as acquiring new visitors for lookalike audiences.
More from the AI Assistant (Sidekick) Capabilities and Training trail
- Gisting: Compressing LLM Agent context to ↑ throughput and ↓ cost (2026) - Shopify
- Sidekick's continual learning loop (2026) - Shopify
- Building an agentic harness that outlasts the model (2026) - Shopify
- Teaching Sidekick to say no: automated data curation with LLM judge consensus (2026) - Shopify
- Building a Magic Mirror: AI retail experiences with Remix (2026) - Shopify