What should investors and consultants check when choosing an eCommerce pricing and assortment data provider?

• Brand to owner. Are brands resolved to the company that owns them, including private companies, with sub-brands and licensed lines handled? Without this you cannot see a company's full footprint.
• Point-in-time tickers. For listed owners, is the brand-to-ticker mapping dated, so acquisitions and disposals do not leak future information into a backtest?
• One category tree. Is every product placed in the same category structure at every retailer, or are you left with each retailer's own menus?
• Continuous history. How far back does the data go, and does it survive retailer website redesigns without breaks?
• Comparable prices. Can you measure price change on the same products over time (matched basis) and compare pack sizes per unit, so product mix does not distort the answer?
• Coverage that fits the question. Which retailers, markets and categories are covered, and from when? Ask for coverage for your own names, not a total count.
• Documented collection. Is collection limited to public information, with no personal data, and will the provider answer your due diligence questionnaire?
• Delivery. Can you take the data the way your team works: a data share, files, a portal or partner platforms?

1. 1Pick three brands you know well, including one private company, and check the provider finds every retailer that stocks them.
2. 2Take one listed company that made an acquisition and check the acquired brand maps to it only from the deal date.
3. 3Compare a category across two retailers and check the products line up in the same categories.
4. 4Ask for a price series on a matched basis and check it against a known price rise or tariff.

Data Purl resolves every brand to its owner, public or private, maps listed owners to tickers point-in-time, places every product in one tree of about 4,000 categories and keeps continuous history back to 2013 across 400+ retailers. Collection is limited to public product information. The methodology page documents each step.

• Brand-to-ticker mapping: Linking each consumer brand to the company that owns it and to that company's listed security, with ownership changes dated.
• Matched-SKU inflation (same-SKU price change): The price change of identical products observed in both periods, which isolates true price moves from changes in product mix.
• Markdown breadth: The share of each product's in-stock sizes and variants selling below full price, averaged across products so each product counts equally.
• Alternative data (shelf-side): Non-traditional data used in investment research; shelf-side data measures what is listed, at what price and availability, rather than what was bought.

How each measure is built: methodology.