A senior-led AI Recommendation Readiness Assessment: we baseline how AI answers your buyers' questions across multiple engines, diagnose why you're named or skipped, score it, and deliver a prioritized roadmap. Cited — our measurement engine — does the evidence-gathering; the judgment is ours.
Why independent intelligence
As marketing gets automated, the systems that used to explain your performance — dashboards, platforms, agencies — increasingly can't tell you the one thing that now decides discovery: how AI describes and recommends you when a buyer asks. That answer forms outside your analytics, across engines you don't control, and it shifts over time. ARR is the independent read on it — and the plan to change it.
The ARR journey
One loop, run end to end — and re-run, so you can prove the fixes worked.
Assess
Intake the business, the audience, and the buyer questions that matter. Define the competitive set.
Measure
Run those questions through live AI engines, repeated for confidence, per market where it matters.
Diagnose
Read the evidence question by question: who's named, who's cited, and why the answer lands where it does.
Prioritize
Rank the gaps by commercial importance, miss frequency, competitor dominance, and fixability.
Build
Produce the assets and evidence the answers reward — delivered as the Cited Roadmap.
Remeasure
Re-run to confirm which interventions actually moved the answers. The loop is the moat.
What the assessment scores
Every brand gets one comparable ARR score, built from what AI actually answered — never a single run, always a range.
Is the brand named at all when the question is asked?
When present, is it the first or top recommendation — or an also-ran?
Is the brand cited, and from credible sources — owned pages and press, or thin third-party mentions?
How much of the conversation does the brand own versus the competitors AI names instead?
For multi-location brands we add a Footprint read — local-page citation and cross-market consistency, the layer generic tools never see. An Entity Blueprint explains whether AI can cleanly understand your brand as an entity in the first place.
primacy top recommendation 2/6 · rival Competitor leads 3/6
authority cited via press + directories · owned-source citation thin
footprint location pages cited 0/6 local gap
What you get
Business & audience intake
The commercial context, the buyer, and what a win looks like — before a single query runs.
Buyer-question map
The real questions your market asks AI, organized by intent and commercial value.
Entity & authority assessment
Whether AI can understand and trust your brand as a coherent entity.
Multi-engine recommendation baseline
How AI answers today across surfaces, with repeated sampling and honest per-surface labels.
Competitor & citation analysis
Who AI names instead of you, and the sources it actually cites to do it.
Content & evidence gap analysis
What's missing, mapped to a fixed gap taxonomy — with the evidence trail behind each gap.
ARR scorecard
One comparable grade across retrieval, primacy, authority, and share — reported as a range.
Cited Roadmap
10–25 evidence-backed actions, prioritized by impact and fixability — not 400 generic ideas.
Executive findings presentation
The narrative your leadership reads: what was tested, what it means, and what to do.
Remeasurement plan
How and when we re-run to prove the fixes moved the answers.
Where Cited fits
Cited is the measurement and evidence engine behind the assessment. It queries live AI surfaces — Perplexity, OpenAI web-grounded, and Gemini with Search grounding — resolves what each one actually cites, and records every answer as evidence. It's what makes ARR measurable and repeatable. But Cited is the instrument, not the offer: what you're buying is senior judgment applied to what the instrument finds.
Who it's for
Franchise and multi-location leaders who need to know what their platforms, agencies, and dashboards aren't telling them — and want a plan, not another dashboard. ARR is led by senior operators: enterprise and franchise marketing leadership paired with hands-on paid-media, SEO, technical, and AI-systems engineering. One frames the business question and its executive implications; the other builds the systems that make the answer measurable, repeatable, and actionable.
Frequently asked questions
What is AI Recommendation Readiness?
AI Recommendation Readiness (ARR) is a measure of how easily AI answer engines understand, trust, and recommend a brand when buyers ask. The ARR Assessment baselines it across multiple engines, diagnoses the gaps, and scores the brand on retrieval, primacy, citation and authority, and share of mentions.
How is the ARR Assessment different from the free AI check?
The free Cited check is a quick, single-surface look. The ARR Assessment is a senior-led engagement: a full buyer-question map run across multiple engines with repeated sampling, an entity and authority assessment, a competitor and citation analysis, an ARR scorecard, and a prioritized roadmap delivered with an executive findings presentation.
Which AI engines do you measure?
Perplexity, OpenAI (web-grounded), and Gemini with Google Search grounding, each labeled by the exact surface queried. Answers are collected with repeated sampling because single runs are directional, so scores are reported as ranges rather than false-precise numbers.
Is Cited the product?
No. Cited is the measurement and evidence engine that supports the assessment. What you buy is senior judgment — the diagnosis, prioritization, and roadmap built from what Cited observes.
Do you need to run our paid media to do this?
No. The assessment stands alone and carries no channel conflict. If you have an agency, they remain your agency — we hand you findings and a plan, not a pitch to take over your marketing.