Merchant taxonomies describe how retailers shelve products. Search language describes how shoppers think. Where the two disagree, you'll find assortment, naming and SEO decisions waiting to be made.
Monitoring systems live or die on a human variable: whether the people they serve believe them. Notes on building that trust — provenance, humility, and the art of the visible caveat.
Organizations drown in signals and starve for decisions. A practical taxonomy for classifying market signals by decision relevance — and for building the escalation paths that make monitoring pay for itself.
The last mile of market intelligence is unglamorous and decisive: how data actually reaches the systems where decisions happen. Delivery design notes for API, warehouse and hybrid patterns.
A competitor price change is a message — but most teams decode it with incomplete context. A working framework for turning price observations into evidence you can defend in a pricing review.
Category-level dashboards tell you the market moved. Attribute-level data tells you how, where, and what to do about it. Inside the discipline of turning messy public catalogs into product understanding.
Market intelligence has quietly changed shape: from quarterly reports assembled by hand to continuous programs built on structured public-web data. Here's what that change actually looks like in practice.
Public-web pipelines fail in boring ways: a layout changes, an encoding breaks, a rate limit appears. Engineering for those failures — detectably, recoverably — is what separates a dataset from a science project.
Elasticity models trained on your own history answer a different question than the one you're asking. Why competitive context belongs in the model — and how to put it there honestly.
Search data is the largest honest survey ever fielded — if you read it correctly. Aggregate signals, seasonal ghosts, and the difference between interest and intent.
