Commerce Data Concepts

Commerce intelligence is the layer above price monitoring: an index of what exists, who sells it, at what, and what that means.

A percentile against a product's own history is a defensible measure of discount depth; percent-off a reference price is not.

How cross-seller product matching works, the three ways it fails, and why published match confidence matters.

How product identifiers relate, why check digits matter, and what to do when there is no identifier at all.

Why every price should carry its origin and a confidence weight, and what goes wrong when it does not.

How AI agents are changing online purchasing, and which protocols matter for making a catalogue legible to them.

How to design Model Context Protocol tools for commerce so agents answer questions instead of stitching fragments.

Idempotency keys, signature versioning, retry ladders and replay — the four things that separate usable webhooks from a support burden.

Why an append-only observation model beats mutable current-price rows, and what that unlocks.

Refresh cadence should be driven by observed volatility and by what a source costs to read — not by a fixed nightly schedule.

Comparing prices across pack sizes requires normalising to a common unit — and treating pack size as part of identity.

Durable, namespaced memory lets an agent carry preferences and constraints between sessions instead of re-interviewing the user.

What price history data is, why it cannot be backfilled, and how to get it through an API instead of building collection yourself.

An honest comparison of running your own price collection against using an API, including the costs that only appear in month three.

The architecture behind a working price comparison site: canonical products, landed cost, per-seller history and published match confidence.

The mechanics behind reliable price drop alerts: standing conditions, change detection, signed delivery and why context makes them worth opening.

How to monitor competitor pricing without drowning in noise: pick the competitive set, react to events, and require confidence before acting.

The difference between competitor-driven dynamic pricing and personalised pricing from consumer data — and why the distinction now matters legally.

What minimum advertised price policies are, how violations are detected, and why evidence matters more than detection.

How marketplace buy-box ownership works, why it flips, and what a seller change signals before the price move that follows.

Shipping, handling and thresholds mean sticker price comparisons are frequently wrong. Landed cost is the number that decides purchases.

How merchant product feeds work, what fields matter, and why feeds are becoming the primary way catalogues reach machines.

The questions that actually separate commerce data vendors: coverage definition, freshness, match quality, provenance and export.

The mechanics of agent-driven purchasing: how agents find products, evaluate price, and what makes a catalogue legible to them.