RadiusRankServices

Evidence-led AI search service

AI Search Analytics

AI search analytics should show what was observed, under which conditions and across how many questions. RadiusRank retains exact answers and summarizes mention rate, owned citation share, share of voice, average position, source recurrence and trends.

Updated 6 minute service brief

Scope and boundaryAI observations are native. Search, visitor and revenue data require customer-authorized sources and remain separate layers in the model.
90/moUS volume for “ai search analytics”
2026-08-11SE Ranking demand snapshot
0ranking or citation guarantees

What the evidence supports

  1. SE Ranking reported 90 monthly US searches, keyword difficulty 19 and AEO Engine at position 6 for “ai search analytics” on August 11, 2026.
  2. A percentage without the count of questions and observations can hide unstable small samples.
  3. Citation share, brand position and competitor share can move in different directions and need separate explanations.

Deliverables and acceptance evidence

A deliverable is not complete because a document exists. Each phase has observable acceptance evidence and a boundary on what it can prove.

WorkstreamShipped outputAcceptance evidence
SampleQuestion count, decision stages, providers and datesStable denominator and disclosed exclusions
ObservationRaw answer, mentions, positions and normalized citation URLsEvery aggregate can be traced to a record
OutcomeAuthorized referrals, conversions and pipeline when suppliedAttribution rule documented beside the metric

What the engagement should change

01

Find absence

Prioritize valuable questions where the brand is missing but relevant competitors appear.

02

Find weak evidence

Identify answers that name the brand but cite no owned or reliable supporting source.

03

Find movement

Connect comparable run changes to the dated work log before proposing a causal explanation.

Methodology

  1. Use a fixed buyer-question and query map so content, technical work and measurement share the same decision scope.
  2. Capture the baseline before implementation, including exact sample sizes, engines, dates, rankings or answers used.
  3. Ship the smallest evidence-backed technical, content or authority change that closes the gap, then record what actually went live.
  4. Re-run comparable observations and report counts alongside percentages. Do not infer revenue without authorized commercial data.

Limitations

  • Observed APIs may differ from consumer chat experiences.
  • Small prompt samples can produce volatile percentages.
  • Analytics cannot prove untracked influence from direct or no-click answers.

Questions

Can ai search analytics guarantee an AI citation?

No. The work can improve accessibility, clarity, evidence and external corroboration, but the answer system decides what it retrieves, names and cites.

How is progress measured without customer Search Console access?

RadiusRank can use a stable question sample, raw answers, mentions, citations, source share and public technical checks. Search and revenue claims are added only when the customer authorizes those data sources.

Sources and data

Found a changed price, product limit or source? Email team@radiusrank.com with the official URL. We preserve the snapshot date instead of silently rewriting historical data.

Start with the evidence

Start with an inspectable baseline.

The free diagnostic shows the questions, public technical issues and citation-readiness gaps before you start a subscription or scoped service.

Run the free diagnostic