LEG 01 · FIND
GEO
GENERATIVE ENGINE OPTIMIZATION
Can an AI system find and cite you when someone asks for the best in your category?
SCORED /100 · 8 CATEGORIES
ACTOR: THE MODEL, AT ANSWER TIME
THE MEASUREMENT SYSTEM · FIND → CONVERT → TRANSACT
Most agencies sell one number and call it visibility. We measure three independent systems — and we never blend them — because a business can win the AI citation and still lose the job ninety seconds later.
GEO gets you named in the answer. Agent Readiness is what happens when the user says “ok, book it” — and an autonomous agent tries to act on your site. Different actor, different failure, different score.
I THE THREE PILLARS
A prospect's path runs find → convert → transact. Each leg is driven by a different actor, measured on its own rubric, and reported as its own score out of 100 across eight scored categories. We diagnose which leg is leaking before anyone spends a dollar on “more visibility.”
LEG 01 · FIND
GENERATIVE ENGINE OPTIMIZATION
Can an AI system find and cite you when someone asks for the best in your category?
SCORED /100 · 8 CATEGORIES
ACTOR: THE MODEL, AT ANSWER TIME
LEG 02 · CONVERT
CONVERSION RATE OPTIMIZATION
Once a human lands, does the page earn the call, the form, or the booking?
SCORED /100 · 8 CATEGORIES
ACTOR: A PERSON
LEG 03 · TRANSACT
AGENT READINESS
Can an autonomous agent act on a person's behalf — book, quote, or buy — in real time?
SCORED /100 · 8 CATEGORIES
ACTOR: AN AGENT, IN REAL TIME
WIN THE CITATION (GEO)→ EARN THE HUMAN (CRO)→ LET THE AGENT FINISH THE JOB (AR)
II THE AGENT READINESS RUBRIC
AR is scored 0–100 and mapped to five client-facing bands. Most sites we look at score well below where their owners assume — a polished site can still read to an agent as a brochure, not a business.
III WHOSE STANDARD THIS IS
The Agent Readiness rubric is built on guidance Google published for making websites work with AI agents — and on a browser category Google shipped to measure it. We didn't invent the criteria. We assembled them into a repeatable score.
THE WRITTEN STANDARD
Google's web.dev guidance, “Build agent-friendly websites,” lays out what an AI agent needs to read and act on a page. Our eight AR categories map directly to it.1
SOURCE: GOOGLE WEB.DEV — LAST UPDATED 2026-04-01
THE MEASURING TOOL
Chrome's Lighthouse added an Agentic Browsing category — a checklist you can run against any URL. We run it methodically and record the result on every scorecard.2
SOURCE: CHROME LIGHTHOUSE AGENTIC BROWSING — ANNOUNCED 2026-06-22, CHROME 150+
Three scores from a rubric anyone can check — not a black box, and not a hunch.
HONEST CAVEAT: the Lighthouse Agentic Browsing category is described by Google as informational and unbenchmarked. We treat AR scores as a diagnostic and a trend line, not an industry-certified grade. As our own re-scoring dataset grows, we report movement over time rather than a settled benchmark.2
IV TWO MARKET WINGS
When an agent acts for a local customer, it is booking an appointment. When it acts for a manufacturer's buyer, it is sourcing a part. The rubric holds; what “transact” means does not.
WING A · LOCAL SERVICE
The agent is completing an appointment on a person's behalf — or moving on to a competitor that lets it.
Why the calling wave matters: at Google I/O (2026-05-19) Google described agents that book and call businesses on a user's behalf, starting with home repair, beauty, and pet care in a U.S. rollout through summer 2026.3 Businesses an agent can't complete a booking with get skipped — quietly.
WING B · B2B MANUFACTURING
The agent isn't booking — it's building an RFQ from your published capabilities.
V PRODUCTIZED INTELLIGENCE
Five productized reports for buyers who want the analysis without a full engagement. Each is built from the same scoring discipline behind the three-pillar scorecard.
R·01
Where an incumbent agency's work leaves visibility and agent-readiness on the table.
R·02
A category read for investors and acquirers assessing a target's AI-era demand position.
R·03
Where a SaaS brand is found, cited, and skipped across AI answer engines.
R·04
The three-pillar scorecard, packaged for a single local business and its market.
R·05
Location-by-location scoring across a franchise footprint, ranked by readiness.
VI ENGAGEMENTS
S·01 · FLAGSHIP AUDIT
The three-score deliverable: GEO, CRO, and AR, each scored across eight categories, with the leaking legs called out and prioritized. Sample numbers throughout are labeled SAMPLE.
S·02 · ENGAGEMENT
A four-phase build that turns the scorecard into work:
S·03 · SPECIALIST
A legal-advertising compliance review for regulated verticals, matched to your state’s rules — so visibility work never outruns the rules that govern how a firm may advertise.
Pricing model: scoped up front, billed phase by phase. Stop at any phase — every phase ends in a verifiable deliverable. No per-lead, per-booking, or contingency pricing.
VII TAKE A READING
Request an audit and we'll score GEO, CRO, and AR against the published standard — and show you which leg of find → convert → transact is costing you the job.
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