Ask a junior analyst where they research and you get a list of websites. Ask a senior one and you get a hierarchy. The difference matters because sources are not interchangeable: each sits at a different distance from the underlying fact, and that distance determines how much weight a claim built on it can bear. This checklist organizes the full secondary research arsenal, free and paid, into five reliability tiers. The rule that makes it a system rather than a list: start at the top and descend only for what the tier above cannot answer. Most weak research is not built on bad sources; it is built on tier 4 answers to tier 1 questions.
The tiers map directly onto the Fact vs. Inference Ladder. Tier 1 material can support Verified Fact claims. Everything below it enters your report as a Reported Claim at best, until corroborated.
Tier 1: Primary disclosures. The company speaking under obligation
These are statements made under legal, regulatory, or contractual compulsion, which is what makes them the bedrock. Cost: almost all free.
Regulatory filings (SEC EDGAR, Companies House, local registries). What they answer: revenue, margins, segments, risk factors, ownership, executive pay. The trap: the MD&A section is management's narrative wearing a filing's credibility; separate the audited numbers from the framing around them.
Earnings call transcripts (company IR pages, free aggregators). What they answer: strategy language, guidance, and, most valuably, the Q&A, where executives answer questions they did not script. The trap: prepared remarks are positioning; treat every adjective as a Reported Claim.
Patents (USPTO, Espacenet, Google Patents). What they answer: where R&D money actually went, often 18 months before products ship. The trap: filing volume is not strategy; companies patent defensively and abandon freely. Look for citation clusters and continuation patterns, not counts.
Court and regulatory proceedings (PACER, competition authority decisions). What they answer: contract terms, supplier relationships, and internal documents that surface in discovery; some of the richest CI material in existence. The trap: litigation documents contain adversarial framing; the exhibits are gold, the pleadings are argument.
Trade and customs data (import/export records, paid via Panjiva or ImportGenius). What they answer: who ships what to whom, in what volumes; physical reality that marketing cannot spin. The trap: coverage varies sharply by country and mode of transport.
Job postings and procurement notices (company career pages, government tender portals). What they answer: capability building before it is announced; a company hiring 14 field technicians in one region is telling you its plans. The trap: postings signal intent, not execution; roles get posted and never filled.
Tier 2: Specialist data and research. People paid to be right about one thing
Named analysts, visible methodologies, franchises staked on a specific coverage area. Cost: mostly paid, and mostly worth it when the coverage matches your question.
Specialist research houses (Dell'Oro for network infrastructure, IDC and Gartner for enterprise tech, IHS Markit for industrials, Wood Mackenzie for energy). What they answer: market sizes, shares, and forecasts with a stated scope. The trap: even good houses define markets differently; never mix two houses' numbers in one calculation without reconciling scopes.
Financial data platforms (Capital IQ, Bloomberg, FactSet, Refinitiv). What they answer: comparables, ownership, transactions, estimates, all normalized and fast. The trap: the normalization itself; a platform's "EBITDA" may not be the filing's EBITDA. Spot-check against the source document before a number becomes load-bearing.
Private market databases (PitchBook, Crunchbase, Tracxn). What they answer: funding, valuations, investor networks for companies that file nothing. The trap: self-reported and stale data; a two-year-old headcount figure presented as current.
Industry associations and trade bodies. What they answer: production statistics, capacity data, standards activity; often the only volume data in unglamorous B2B markets. The trap: associations exist to advocate for their members; their totals are solid, their outlooks are lobbying.
Tier 3: Quality journalism and informed commentary
Professional accountability without regulatory compulsion. Cost: subscriptions, cheap relative to value.
Wire services and financial press (Reuters, Bloomberg News, FT, WSJ). What they answer: events, deals, executive moves, with editorial verification behind them. The trap: "people familiar with the matter" is a Reported Claim by construction; the outlet's credibility does not promote the anonymous source's claim to fact.
Trade press (the two or three publications every industry insider actually reads). What they answer: operational detail and personnel moves the financial press ignores. The trap: small outlets depend on vendor advertising and access; watch for coverage that never criticizes anyone.
Sell-side research. What they answer: deep company models, channel checks, management access. The trap: structural bias is well documented; use the data and the questions analysts ask, discount the ratings and the price targets.
Expert networks (GLG, AlphaSights, Guidepoint). Technically primary conversation, priced like a luxury good. What they answer: the texture no document contains; how deals really get won, why customers really churn. The trap: one expert is one anecdote wearing authority; treat every call as Single-Source Inference until a second, independent expert corroborates.
Tier 4: Crowd and social signal. High volume, low individual reliability
Nobody here is accountable for accuracy, but the aggregate patterns are real. Cost: free.
Employee review sites (Glassdoor, Blind). What they answer: morale trajectories, reorganizations, leadership problems, months before they surface elsewhere. The trap: selection bias is extreme; read the trend across fifty reviews, never the content of five.
Product review platforms (G2, Capterra, app stores, Amazon reviews for physical goods). What they answer: why customers actually churn, feature gaps, pricing friction. The trap: vendors seed positive reviews; weight the negative and neutral ones, which nobody pays for.
Forums and communities (Reddit, Stack Overflow, industry Discords, LinkedIn commentary). What they answer: practitioner sentiment, early product problems, hiring market chatter. The trap: a loud thread is not a trend; five posts can be one motivated person.
Tier 4 material enters reports only as corroboration or as an early-warning flag for something to verify upstream. It never stands alone under a conclusion.
Tier 5: Commodity content. The tier you name so you can refuse it
SEO-optimized market reports from template factories, aggregator articles rewriting other articles, AI-generated industry summaries. The tell, as the 48-hour market sizing demonstrated: precise-looking numbers, invisible methodology, and estimates that disagree by 2x across publishers without explanation. Cost: cheap, which is the problem. Legitimate uses: discovering what vocabulary an industry uses, finding names of players to research properly, and nothing else. No number from tier 5 ever enters a model.
Running the stack
Three habits turn the tiers into practice. First, match the tier to the claim: a Verified Fact label requires tier 1; a market size deserves tier 2 plus your own bottom-up check; tier 4 alone never supports anything above Single-Source Inference. Second, descend deliberately: when you catch yourself citing a tier 3 article for a number that lives in a tier 1 filing, go get the filing; it takes ten more minutes and removes one layer of retelling. Third, log the tier with the source: a source list annotated by tier lets any reviewer audit your evidence mix in thirty seconds, the same way the Ladder lets them audit your labels.
The stack will not make research faster. It makes it defensible, and defensible is what survives the meeting.