Methodology + Deliverables
Seven pillars. One outcome: your brand cited by name when a buyer asks ChatGPT, Perplexity, Gemini, Claude, or Google's AI surfaces “who's the best…” Sequenced — entity before relevance, relevance before digital PR — because the engines retrieve in that order. The C is the pillar generalist GEO agencies skip.
Why this exists
Generative engine optimization didn't exist as a discipline three years ago. Agencies that bolt GEO onto a traditional SEO playbook do partial work and report numbers no one can reproduce.
Each of the seven pillars maps to a specific deliverable with a measurable outcome on monthly reporting, and every measurement runs to one published standard: six surfaces, equal weight, per engine, no composite.
The framework is sequenced on purpose — entity work before relevance, relevance before digital PR — because that's the order the engines retrieve in.
Methodology + Deliverables
VERDICT™ is the methodology — the seven-pillar engine that runs under every engagement. It's how we make you the answer.
PROOF™ is how you see the work. Every deliverable — every monthly retainer report and every public research paper — follows the PROOF format, so nothing is a black box.
The discipline is the point: every claim about your brand ships with receipts — a citation count with a date and an engine — and every output is reviewed against the relevant advertising rules before it ships.
Two formats, one principle: show the receipts.
VERDICT™ — the engine
Seven pillars. Visibility · Entity · Relevance · Digital PR · Intent · Compliance · Tracking. Detailed below.
PROOF™ — the dashboard
Five sections. Position · Receipts · Outcomes · Oversight · Forward. Detailed at bottom.
Pillar 1 of 7
Baseline test of how you're currently cited (or absent) across ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, and Claude — query by query, engine by engine, source by source, to the Six-Surface Standard.
Baseline first. Without a citation baseline you can't measure lift, and the engagement is flying blind. Visibility is the pillar that makes every other pillar accountable.
We run at least three depersonalized samples per query across all six surfaces, discard invalid runs, and never report a composite — you see exactly which engines cite you, on what, and where the citations come from.
Sample output
Sample output: a six-surface report showing you cited in 3/12 buyer-intent prompts on ChatGPT and 0/12 on Gemini, with the competitor and source URL behind every citation.
Pillar 2 of 7
Consolidate your identity across the web — Google Business Profile, industry and association directories, review platforms, and knowledge-graph signals (Wikidata, Crunchbase, LinkedIn). Schema markup is supporting hygiene, not the lever.
AI engines retrieve with confidence only when your entity is consistent across surfaces. Conflicting names, titles, and facts make you ambiguous — and ambiguous brands don't get cited.
We do the schema (Organization, Person, Service, FAQPage, BreadcrumbList), the directory hygiene, and the knowledge-graph work so the engines resolve you as one confident entity.
Sample output
Sample output: an entity audit flagging 14 missing schema fields, 6 directory inconsistencies, and 2 conflicting titles across your public profiles.
Pillar 3 of 7
Publish content people actually find useful — clear heading hierarchy, first-hand expert attribution, and depth that answers the specific buyer question. Match the sub-intent behind the query, not just the surface keyword.
Index-grounded AI rewards content built for human readers: answer-first, well-structured, and attributable to a real expert.
We re-engineer pages into citable passages — structured Q&A, fact-dense answers, and formatting the engines can lift cleanly into a response.
Sample output
Sample output: a priority set of pages rewritten into answer-first, citation-friendly passages mapped to your highest-value buyer questions.
Pillar 4 of 7
Earn citations from the publications AI engines actually pull from — the trade press and authoritative industry publications for your category, plus the Reddit and Quora threads where intent aligns. Citation-source diversity is the highest-leverage lever.
AI answers cite a diverse set of trusted sources. If your brand only lives on your own site, you're a single point of failure the engines can ignore.
We place your expertise and mentions on the third-party sources that feed AI answers in your vertical, tracked as earned citations — not vanity links.
Sample output
Sample output: a citation-source map for your category and a placement plan targeting the specific publications AI cited for your competitors.
Pillar 5 of 7
Map queries to buyer-journey stage — awareness, consideration, decision — so each stage gets the content type it rewards: informational pieces feed awareness, comparative pages feed consideration, and conversion pages and proof feed decision.
Being cited for the wrong questions is wasted work. We start from where your business actually makes money and work back to the prompts worth winning.
This is where our management-consulting background does the aiming — the competitive-positioning read that points the rest of the framework at the right battles.
Sample output
Sample output: a prioritized prompt map — the awareness/consideration/decision questions worth owning, ranked by business value and current AI-visibility gap.
Pillar 6 of 7
Every output reviewed against the relevant claims and advertising rules — FTC advertising and endorsement guidelines, AI-content disclosure where applicable, and any industry-specific regulation that governs your category. Built into the workflow, not bolted on.
AI-assisted content can quietly cross advertising-rule lines — unsubstantiated claims, undisclosed endorsements, misleading comparisons. Generalist GEO agencies don't catch these.
We review every deliverable before it ships, with a logged reviewer and findings — the structural difference between WTT Digital and a generalist shop.
Sample output
Sample output: a compliance review log for the month — every output checked against the relevant rules, with date, reviewer, and findings.
Pillar 7 of 7
Monthly measurement of citation rate, citation-source diversity, entity completeness, and compliance-review status — measured to the Six-Surface Standard and documented in the PROOF™ Report.
What gets measured — honestly — is what improves. Tracking closes the loop from the Visibility baseline through every pillar's work.
You get a first-Friday PROOF™ Report: per-engine citation trends, source diversity, entity completeness, and the compliance log — receipts, not a composite score.
Sample output
Sample output: your monthly PROOF™ Report — per-engine citation trend, new citations earned, entity completeness delta, and the compliance review log.
PROOF™ — the deliverable format
PROOF is the format every deliverable follows. Five sections, every time. Two formats, depending on context.
Recurring · Monthly · For retainer clients
The format every retainer client gets, the same way every month — built so a busy operator can read it in ten minutes and know exactly what changed.
Where your brand stands in AI search today — citation share by engine, coverage on tracked prompts, entity-recognition status, branded vs. unbranded query performance.
Example line
Cited in 12% of tracked category prompts on ChatGPT (up from 4% at baseline); 31% on Perplexity; 0% on Gemini.
Every asset published, every schema deployment, every mention earned, every citation placed during the period. No black box — the actual work.
Example line
This period: 5 pages published, 9 schema enhancements deployed, 4 third-party citations earned, 6 entity fixes.
What changed in the metrics and which prompts drove it — citation lift per engine, source-diversity delta, AI-attributed traffic.
Example line
Six-surface citation lift reported per engine; AI-referred sessions +610% MoM via utm_source tags.
Compliance review log for the period — every output checked against the relevant claims and advertising rules. What was flagged, how it was resolved, who reviewed it.
Example line
2 draft claims flagged as unsubstantiated and revised with sourced figures before shipping; reviewer named.
Hypothesis-driven plan for the next period — what we'll test, why, what we expect to move, and the risk flags we're watching.
Example line
Extend Digital PR to two trade publications AI cites in-category; re-baseline all six surfaces at day 90.
Quarterly · Public · Peer-style research
The format every research paper we publish follows. Empirical, falsifiable, written so other practitioners can reproduce the methodology and check the math. The work that earns inclusion in AI-engine training and citation corpora — and the work that distinguishes WTT from agencies that publish opinions instead of evidence.
The hypothesis being tested. What the paper claims and why it matters. Falsifiable from the first page.
The methodology. Sample size, prompt corpus, time window, control conditions, data sources. Reproducible by anyone with the same tools.
The raw data. Charts, citation tables, prompt-by-prompt results. What was actually measured, before interpretation.
The interpretation, with confidence intervals and dissenting takes. What the data does — and doesn't — support.
The bounded, actionable conclusion. What practitioners should do with this. What the next experiment should test.
· forthcoming ·
Why we publish either way:
Sample PROOF Report
Most agencies guard their reports behind a sales call. We publish a real one. Client name and identifying details redacted with permission. Numbers, prompts, and observations are unaltered.
Why two formats, one acronym
A monthly client report and a public research paper are different artifacts with different audiences — but both live by the same rule: show the receipts.
FAQ
VERDICT™ and PROOF™ are filed trademarks of WTT Consulting LLC (DBA WTT Digital). USPTO filings completed May 2026.
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