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Field Agent Canada — Crowdsourced in-store retail audit corpus: high-resolution shelf, endcap and display photographs captured by a network of over 330,000 on-demand shoppers, each geotagged and time-stamped to a specific store, bay and SKU set, paired with structured audit responses — price capture, facing and share-of-shelf counts, planogram compliance verdicts, out-of-stock and phantom-inventory flags, and promotional-display execution. Follow-up verification photos on the same stores create before/after pairs on merchandising fixes. The latent asset is the labeled shelf-image corpus itsel…
Crowdsourced in-store retail audit corpus: high-resolution shelf, endcap and display photographs captured by a network of over 330,000 on-demand shoppers, each geotagged and time-stamped to a specific store, bay and SKU set, paired with structured audit responses — price capture, facing and share-of-shelf counts, planogram compliance verdicts, out-of-stock and phantom-inventory flags, and promotional-display execution. Follow-up verification photos on the same stores create before/after pairs on merchandising fixes. The latent asset is the labeled shelf-image corpus itself: store, date and bay-identified retail imagery with SKU detection and price ground truth, which is far harder to assemble than the report layer sold on top of it.
Scale Very large for a national footprintFrom 15 yearsCoverage Industrials
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Field Agent Canada — Crowdsourced in-store retail audit corpus: high-resolution shelf, endcap and display photographs captured by a network of over 330,000 on-demand shoppers, each geotagged and time-stamped to a specific store, bay and SKU set, paired with structured audit responses — price capture, facing and share-of-shelf counts, planogram compliance verdicts, out-of-stock and phantom-inventory flags, and promotional-display execution. Follow-up verification photos on the same stores create before/after pairs on merchandising fixes. The latent asset is the labeled shelf-image corpus itsel…
Field Agent Canada offers (Alternative, Geospatial, Supply Chain) — Very large for a national footprint — the page cites auditing 1,000 stores in 24 hours, and a typical audit captures multiple bay and display photographs per store, implying roughly 10^4 to 10^5 images per large client program and plausibly 10^6 to 10^7 images annually across the Canadian book; no aggregate count is published.
Training and benchmarking shelf-level product detection and segmentation models on real planograms rather than studio catalog images; retail price-reading optical character recognition across banners, shelf-edge labels and promotional tags; out-of-stock and shelf-availability classifiers; visual search and product-identification models robust to facings, packaging variants and occlusion; store-level image retrieval; agentic retail-execution models that detect a violation and route a fix; longitudinal retail pricing studies
The data is with 15 years of history.
Coverage spans Other, US; Research & Security Services; alternative, geospatial, supply_chain; equities.
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