datawebotWorking with ecommerce data, in depth.
Long-form articles on matching, pricing, research and catalog work: how each job is done, where the data comes from and what to check before you rely on it.
Ecommerce analytics tools: 16 picks, sorted by the job they do
Ecommerce analytics tools do four jobs: store analytics, marketplace research, competitor price tracking and data APIs. Pick the job first, then the tool.
Ecommerce market research: how to use marketplace data
How to use marketplace listings for ecommerce market research: what the data can answer, a step-by-step method, the checks to run, and its honest limits.
Price intelligence and digital shelf analytics: what they measure and how to get the data
Price intelligence tracks competitor prices and promotions. Digital shelf analytics tracks how products appear online. Metrics, data and build vs buy.
Product data enrichment: how to fix incomplete product catalogs
Product data enrichment fills missing or wrong catalog fields like GTIN, brand, size and color from verified sources. Fields, sources, workflow, AI risks.
Product matching: how to match the same SKU across stores and marketplaces
Product matching links listings of the same item across stores. Why it is hard, the main methods, how to measure match quality, and a practical workflow.
What is a minimum advertised price, and how do you monitor it?
What a minimum advertised price is, how it differs from MSRP and resale price maintenance, and how MAP monitoring finds and documents violations.