How Competitive Intelligence Product Teams Use Industrial Gases Data

Competitive intel product teams arrive in this industry with a specific handicap: the producers that dominate Europe - Air Liquide, Air Products, Linde and Messer, all named in EIGA Member Companies Directory - publish almost nothing quantified between annual reports. So CI teams build the picture from records a rival cannot edit: rosters, branch counts, facility filings, price indexes and trade flows.

Datadory pools 17 datasets for the industry - 8 primary and 9 related - and 12 of the 17 are entirely free. The direct persona fit is deliberately thin: our tagging assigns only two primary datasets an explicit competitive-intel use case, data.europa.eu for tracking what member states publish on gas infrastructure and supply, and eGon for benchmarking scenario demand assumptions. The gases-specific layer sits in the related pool instead: EIGA's statistics booklet and directories, the Compressed Gas Association roster, EPA emissions records, the Airgas locator, Cognite's plant feed and the BLS producer price index.

Distribution footprint needs a different record. The Airgas store and branch locator exposes roughly 900 US retail locations as crawlable HTML with address, phone, hours, coordinates and service lines; its sitemap lists about 824 individual location pages out of 926 total URLs. Because that sitemap declares daily change frequency, a weekly crawl is enough to catch new branch openings - often the earliest public trace of a territory push by the largest US gas distributor.

For plant operations rather than structure, Cognite Open Industrial Data - Valhall Gas Treatment Plant opens up one real asset - the Valhall PH platform's first-stage gas treatment and compression system in the North Sea - as hundreds of thousands of time-series datapoints across thousands of tags, plus the asset tree, documents and P&IDs, event records and 3D models. CI teams use it to prototype the telemetry-based benchmarks they would want against a competitor's fleet, without waiting for proprietary data access.

Eurostat International Trade in Goods (Comext) carries monthly intra- and extra-EU flows by CN8 product code back to January 1988, filterable by reporting country, partner and flow direction. It scores 9 out of 10 on quality - tied with the Fed's G.17 at the top of this slice - ships through an official API plus JSON, CSV, TSV and SDMX-ML files, and re-uses free under commercial delivery terms 4.0 attribution. For CI work the tell is a shift in partner mix: when one producer's home country starts shipping rising volumes of gas-related CN8 lines to a new market, the trade record shows it months before a strategy note does.

Two practical caveats keep the signal honest. Comext revises data and staggers releases - some intra-EU detail lands later than extra-EU figures, about 46 days versus roughly 2.5 months - so set alert thresholds after the intra-EU publication lag. And for the Indian market, IndiaMART B2B Marketplace offers tens of millions of live listings across 200,000-plus supplier catalogs as a realtime read on who is selling what, but its terms prohibit systematic retrieval without written permission from IndiaMART InterMESH Ltd., so it stays a manual spot-check surface rather than an automated feed.

Attribution is the core CI discipline, and the Federal Reserve's Industrial Production & Capacity Utilization (G.17) does the separating: its full historical database reaches 1919, with monthly indexes by market group and NAICS industry - machinery at NAICS 333 - plus capacity utilization and diffusion tables served as TXT, HTML, PDF and XML from December 1997, and releases back to April 1990 available through FRASER. When G.17 machinery production falls, a distributor's soft quarter reads as market, not mismanagement.

Against that baseline, the stack below is ranked by how directly each record answers a competitive question, weighted toward what a CI product team can legally automate: