Alloy.ai

Alloy.ai — Retail sell-through and on-shelf availability panel for consumer goods. Alloy ingests granular point-of-sale and inventory feeds from 450+ retailers, e-commerce sites, distributors and 3PLs and normalizes them into SKU-by-location-by-day records, then derives in-stock status, lost-sales valuation, phantom inventory (system on-hand versus on-shelf reality) and promotion lift. The latent asset is a cross-retailer, store-level unit-movement and availability panel covering the same SKU across competing chains - close to a census of physical retail demand below the level syndicated meas…

Alloy.ai offers (Alternative, Supply Chain, Price) — Very large: 450+ retailer, e-commerce, distributor and 3PL feeds at store x SKU x day granularity. A single national grocery chain is on the order of 2,000 stores x 20,000 branded SKUs, so even a partial network implies billions of sell-through observations per year. The distinctive quantity is breadth of the same SKU observed across competing retailers, which measured panels only approximate..

Real-time consumer demand nowcasting and regional availability and inflation indicators; out-of-stock and lost-sales benchmarking as a revenue-at-risk signal for the public companies that own those brands; demand-forecast and replenishment model training on true sell-through ground truth; promotion-lift and causal-incrementality model development; retail media category-penetration modeling; distribution-gap and market-share analytics; reinforcement-learning environments for ordering policy; validation sets for measured market-research panels that are modeled rather than observed.

The data is with 10 years of history.

Coverage spans US; Application Software, Food Retail; alternative, supply_chain, price; equities.

The supplier's own access route is a conversation with the supplier. Request a sample through Brickroad to start.