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Research standards
The evidence, attribution, limitation, and correction standards applied to reports and industry notes.
Evidence before narrative
Reports should distinguish sourced fact, direct observation, synthesis, and inference. A useful narrative cannot replace evidence, and a directional trend should not be presented as a settled market fact.
- Identify the evidence type behind material claims.
- State sample, date, and scope limits when data is used.
- Avoid extrapolating beyond the observed category or platform.
Source selection and attribution
Primary research, official documentation, public datasets, and directly attributable statements are preferred. Secondary analysis may provide context but should not silently become the source of a factual claim.
- Link sources near the claim they support.
- Use different sources when a conclusion benefits from multiple perspectives.
- Make uncertainty and unavailable evidence visible.
Corrections and report revisions
Material factual errors should be corrected when evidence is available. A correction that changes a conclusion should be noted; routine copy edits do not require a public change log. Requests should identify the report URL, claim, and source.
- Update modified dates for substantive revisions.
- Preserve citations when wording changes.
- Separate evidence disputes from product-positioning requests.
Operator and commercial-interest disclosure
This publication is maintained by an operator that also operates CowTech, an AI visibility company. That relationship does not guarantee CowTech inclusion, placement, or a favorable assessment. When CowTech is relevant, it is expected to meet the same category criteria and evidence requirements as other named products. Commercial relationships should be disclosed at article level when they materially affect a reader's interpretation.