About Brandvane
Research standards for AI visibility reporting.
Brandvane is an independently operated SEO research and AI visibility product for small businesses, consultants and hands-on marketers. It also offers a focused managed SEO service, starting with electrical contractors. This page states who is responsible for its publishing and what readers should expect from its research.
Authorship and responsibility
Brandvane is the organizational author and publisher of the field notes on this site. Brandvane is responsible for topic selection, research design, analysis, writing, editing, and corrections.
Randall is Brandvane’s founder and the direct contact for its managed SEO service. Articles use the Brandvane organizational byline. The site does not claim professional credentials, laboratory status, academic review or certification that have not been documented.
Editorial standard
Published claims should be traceable to visible methods, first-party observations, cited public sources, or clearly labeled product plans. Commercial interest does not change the evidence threshold: when a sample is small, a system is variable, or a conclusion is only directional, the copy should say so.
Comparisons are based on the capabilities and public information available at the time of review. They are not endorsements by, or affiliations with, the companies discussed.
Research and measurement method
Brandvane keeps three evidence layers separate: sampled AI answers, verified infrastructure access, and AI-referred human visits. One layer does not prove another. A crawler visit does not prove inclusion in an answer, and a sampled answer does not prove a person visited a site.
Reports should retain the question set, sample size, date, engine or surface, location and device when relevant, source links, and known limitations. Repeated runs are used because generated answers vary. First-party analytics and Search Console data are described as observations from the connected property, not as universal market estimates.
Read the full measurement framework or review the sample report to see how those rules appear in a deliverable.
Updates and corrections
Articles show a publication date and, when a material revision is recorded, an updated date. Material errors should be corrected in the article rather than left in place for narrative consistency. Because AI products and search surfaces change quickly, readers should treat dated tests as snapshots.
Contact context
For privacy requests or research corrections, contact support@brandvane.ai. Include the publication URL and the evidence you would like us to review.