090°Open data
Open datasets, fully documented — searchable here, and readable by any LLM.
1 datasets
US Retail Kind-of-Business Sales Intelligence (derived)
Monthly US retail-sales intelligence at kind-of-business grain from the U.S. Census Bureau's Monthly Retail Trade Survey (12 FRED MRTSSM*USS series: NAICS 441, 442, 443, 444, 445, 446, 447, 448, 451, 452, 453, 454; millions of dollars, seasonally adjusted, 1992-01 ->). Each category-month row carries the sales level, its share of combined kind-of-business sales, month-on-month / year-on-year / 3-month-annualized momentum, YoY acceleration, a documented 0-100 category momentum score (50% winsorized YoY + 30% 3-month annualized + 20% MoM, min-maxed within each month) with deterministic rank and c1-c4 tiers, trailing-12-month record-high and contraction flags, plus month-level context (combined sales, total YoY, breadth of categories growing YoY, the month's top category, and the nonstore/e-commerce-adjacent share). An online shop joins monthly category sales to its own revenue on (date, category_code) for demand benchmarking; a sales team joins category momentum to pipeline value on date. Method: keyless FRED fredgraph.csv fetches with 0.3s polite pacing; a trailing-36-month verbatim transcription is embedded for offline safety; the transform is pure pandas in map_schema with no imputation (early-window momentum cells are honest nulls). Caveats: shares are shares of the 12 published kinds (which sum to combined retail-trade sales by construction), not of a separately published total; official e-commerce is quarterly (see companion dataset ecommerce_penetration) — the monthly nonstore share is the closest monthly proxy.
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