AI answers now decide which brands buyers see, and a single daily rank number is noise: the same query run twice rarely agrees. CiteGround measures what actually holds. We run your real buyer prompts through ChatGPT, Perplexity and Google's AI, and a human checks every reading before it ships: which competitors get named, the third-party pages the answers are built on, your absence or presence per prompt, and the run-to-run variance band. The report is free for your work email, turned around in 24 hours. From there, a deep read works every winnable gap, and a done-for-you engagement places you into the pages AI grounds on. Judgment a dashboard cannot ship.
A startup from San Francisco, the United States.
Multi-run measurement
Every buyer prompt runs multiple times per engine; results ship with run-to-run variance bands, never a single-run score.
Engine coverage
ChatGPT, Perplexity, and Google AI Overviews, measured per engine โ the same prompt often gives different answers on each.
Grounding source map
Shows the exact third-party pages each AI answer is built on, and who owns them (vendor, community, independent)
Human-verified reports
A human checks prompt selection, brand extraction, and every verdict before a report ships. 24-hour turnaround.
Winnability calls
Each prompt gets a judgment cal, takeable, long shot, or not worth it, with the reasoning stated.
Open methodology
Public CC-BY dataset (DOI: 10.5281/zenodo.21263503) and published methods; any number can be re-run live.
CiteGround publishes its evidence. Every measurement ships with run-to-run variance bands, the methodology and a 595-run dataset are public (DOI: 10.5281/zenodo.21263503), and our own category baseline is on the record as a dated, public test of our own playbook. A human verifies every report before it ships.
CiteGround publishes its evidence. Every measurement ships with run-to-run variance bands, the methodology and a 595-run dataset are public (DOI: 10.5281/zenodo.21263503), and our own category baseline is on the record as a dated, public test of our own playbook. A human verifies every report before it ships.
Marketing and growth leads at B2B SaaS companies who can see rivals winning AI answers, often in a visibility tracker they already pay for, and need to know what to do about it.
We measured before we built. Running the same buyer prompts repeatedly across ChatGPT, Perplexity, and Google AI showed the first-named brand flips between runs in over half of cases, the single-run screenshots the industry trades on are noise. We published that archive as an open dataset and built the service on what a dashboard can't ship: verified judgment about which sources ground the answers and which are winnable.
A Python measurement harness querying engine surfaces via API, an append-only archive of every run, LLM-assisted analysis with human verification on every judgment call, and a Next.js site. The methods are documented publicly at citeground.com/methods.
I don't have verified, reliable information about CiteGround (citeground.com), so I can't confidently confirm its quality, features, or legitimacy. It may be a newer, niche, or low-profile service not well-documented in my training data, or the name might be confused with similar-sounding products like SiteGround (a web hosting company) or citation tools like Cite This For Me. Before using it, I'd recommend independently verifying its legitimacy, checking recent user reviews, testing customer support responsiveness, and confirming pricing and refund policies directly on their site.
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Check the traffic stats of CiteGround on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
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Check the "Domain Authority" of CiteGround on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
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