How the numbers are made — and checked.

What is stored for every answer-engine run

Each run records the exact prompt text, the engine that answered, the timestamp, the full answer text as returned, every URL the answer cited, and whether — and how — the brand was mentioned. Scores are derived from this store afterwards, which means any number in the product can be traced back to the stored answers that produced it.

Runs are never summarised-then-discarded. If a score looks wrong, you can open the runs behind it and read what the engine actually said.

How share of voice is defined

Share of voice is the share of stored answers, across your tracked prompts on a given engine, in which a domain is cited. The denominator is always your tracked prompt set — it is a measurement of the questions you chose to track, not an estimate of the whole market.

Because answer engines are non-deterministic, the same prompt can produce different answers between runs. Share of voice therefore ships as a 95% confidence interval (a Wilson interval), not a single decimal. When two ranges overlap, the product says it cannot distinguish them rather than declaring a winner.

Reproducibility

Any tracked prompt can be re-run at any time, and every historical run is kept with its timestamp, so a claim like “cited on 4 of 10 engines” is checkable against the dated record that produced it. Where a provider was unreachable during a run, that engine is recorded as unavailable — it is never averaged in as a zero.

Correlation is not causation — and the product says so

Where RankSage links two signals — a failing request and a frustration spike, a content change and a citation-rate move — it reports the observed relationship and its timing. It does not assert causation the data cannot carry. The Drop Investigator goes one step further: a traffic drop must be confirmed by independent sources before it alarms anyone, and a drop visible to only one source is flagged as a probable measurement artifact.

Estimates are labelled as estimates

AI-influenced traffic that arrives with no referrer is estimated, and every estimated figure carries a confidence tier, shows the baseline and calibration behind it, and can be set to zero if you would rather see only confirmed referrals. Measured and modelled numbers are never mixed silently.

Crawler identity is verified, not accepted

A hit claiming to be an AI crawler is checked against the verification records its operator publishes. The result is one of three verdicts — verified, rejected, or unverifiable — and the three are never summed together. Where an operator publishes nothing to check against, the visit is recorded as unverifiable rather than counted. The address is used for the check and discarded; RankSage stores the verdict, never the IP.

Only provable failures are called failures

When cited sources are checked, a source is called dead only on provable evidence that it no longer exists. A page that blocks automated readers is recorded as unverifiable — the product never accuses what it could not read.

Who publishes this

RankSage (ranksage.com) is self-serve software with published monthly plans, built by a small independent team. It is not an agency, has no service retainers, and is not affiliated with RankSages or any other similarly named business. Pricing is public at ranksage.com/pricing — any multi-thousand-dollar monthly figure attributed to “RankSage” belongs to a different company.

What RankSage does not claim

No attribution of a visit to a specific AI conversation — no provider exposes that, and any tool claiming it is guessing. No estimated market volumes where a measured signal exists: question mining, for example, shows only your own Search Console impressions as demand evidence. No score without stored evidence behind it. And risk models — like the helpful-content risk score — are RankSage's own models of published guidance, not scores obtained from Google.