Retail Shelf Intelligence - Validate SKU Price and Stock Data
The original article described broad CPG analytics and made unsupported claims about automatic extraction, layout adaptation and retailer coverage. This revision narrows the task to validated product observations and corrects the API parameter names to browser and proxy_country. Download the reproducibility packet.
A retail price observation needs a product identity, the selected variant and pack size, the offer being quoted, and evidence for its availability. Otherwise, a cheaper subscription offer or a smaller pack can look like a price drop. A failed page can look like an out-of-stock product if the collector treats every missing value as a stock signal.
This walkthrough builds a small source-specific Python collector for repeated SKU observations. It keeps unknown availability, rejected fields and acquisition failures distinct from explicit out-of-stock evidence. The runnable controls use a fictional tea family with two selected weight packs. A separate direct retail observation and optional managed retrieval are recorded separately. Completeness refers to those selected offers, not a retailer’s full inventory.