Applied AI in retail, e-commerce and CRM — each article built from a real operating problem: the traditional approach, the AI-assisted approach, the results, and the lessons. Practical enough to implement the same week. New pieces publish on LinkedIn and are archived here.
Forecasting used to be a guessing game of last year’s numbers plus a rough uplift. AI for guidance, Python for execution, and monthly data made rolling 12-month SKU forecasts realistic.
Read the article →Classifying 8,500+ products with tags that go beyond the obvious — built in days with AI, a Python script and an API key, and without any data leaving the system.
Read the article →Thousands of SKUs sat online with vague copy and no keyword alignment. Rather than hiring writers, I started with a prompt — and generated SEO-ready descriptions for 5,000+ products in days.
Read the article →Hundreds of messy free-text survey responses used to end up on a slide, never activated. A privacy-first Customer Voice Analyzer turned 1,500 open-ended answers into a sourcing plan.
Read the article →Once a catalog crosses five digits, the product hierarchy starts to strain. A four-step, AI-assisted framework turned weeks of subjective debate into days of structured decisions.
Read the article →Across platform evaluations at Levi Strauss, ASICS and Phoon Huat, AI became a quiet partner — bringing structure to the RFP journey and creating space for better conversations.
Read the article →The real power of AI comes not from asking a question, but from asking a better one — bringing a consultant’s habit of clarity, context and structure to everyday retail work.
Read the article →