Services

A four-phase
engagement.

Discovery is on me. The audit is fixed-price. Activation is itemised, so you only pay for the work you actually need. Monitoring is monthly. Whether an AI engine cites a brand depends on five things — all of which can be assessed and most of which can be improved.

Phase 1
Discovery
A 30-minute call to understand the business, the competitive landscape, and what success looks like. Before we speak, I run 10 tracked queries across major AI engines and pull a short visibility snapshot — so the conversation starts with real data, not hypotheticals. If GEO is the right move for the brand, we'll know by the end of the call. If it isn't, I'll tell you that too.
Phase 2
Audit
A structured diagnostic across two tracks: a 40-point technical pre-GEO audit covering crawlability, schema, site architecture and AI crawler permissions; and a citation readiness audit measuring how AI engines currently describe the brand across 50 tracked prompts. The output is a readiness score, a documented baseline, and a prioritised activation plan — sized to what the brand actually needs, not a standard package.
Phase 3
Activation
Implementation work scoped directly from the audit findings — itemised so you can see exactly what's being done and why. This typically covers crawler access and llms.txt, schema markup, content restructuring for answer-first formatting, entity authority work across Knowledge Panel and Wikidata, NAP consistency, and AI referral tracking in GA4. Delivered in a focused sprint, with scope agreed before anything is invoiced.
Phase 4
Citation Monitoring
Monthly tracking across major AI models on 6 metrics — measured against the audit baseline so movement is visible and documented. Each month includes two citation-ready content pieces developed from social listening data, a written report covering visibility, share of voice, sentiment and position, and a strategy call to discuss what the numbers mean and what comes next.
What the audit covers

Five layers of
citation readiness

Each is a different way a brand can be invisible to AI — or visible but represented badly. The audit covers all five.

01
Crawler access
Can AI engines actually read the site? robots.txt, llms.txt, Cloudflare bot settings, blanket blocks. If they can't crawl it, nothing else matters.
02
Schema & structured data
Schema is how a site communicates structured information to AI in a format it can reliably read. Organisation, Article, FAQ, BreadcrumbList, Product/Service — coded and validated.
03
Content extractability
Whether key pages answer real questions in the first 100 words, with named authors and sourced statistics. Answer-first formatting matters because that's what AI engines lift.
04
Entity authority
Whether AI recognises the brand as a distinct entity. Google Knowledge Panel, Wikidata, Crunchbase, NAP consistency, third-party reviews. The sameAs chain AI uses to verify identity.
05
Visibility baseline
A 50-prompt baseline measuring how the brand currently appears across AI engines — present, absent, or misrepresented. This is what every future month is compared against.
From audit to action

How the audit
shapes the work

The audit returns two things — a readiness score and a strategy mode. Together they define what activation does and in what order.

Readiness score
Can we start?
A percentage score across 40 SEO and technical checks. Above 80% means activation can begin. Below that, foundational fixes come first — GEO work on a broken technical foundation wastes money.
Strategy mode
What kind of work?
Three modes. Additive: brand is well-represented, expand share of voice. Mixed: partial presence, corrective and additive. Corrective: poor or inaccurate AI perception, fix entity clarity first.
Prioritised plan
In what order?
Activation work is sequenced by what moves the dial fastest given the score and mode. Itemised pricing means scope stays transparent and only what's needed gets invoiced.
What measurement looks like

A monthly report,
not a vanity dashboard

Every report covers six metrics per platform, tracked against the baseline established at audit — plus a platform comparison, GA4 AI referral traffic, and a forward plan. Here is what that looks like in practice.

Six metrics tracked per platform
Visibility
% of tracked AI queries where the brand is explicitly mentioned by name. The primary measure of presence.
Share of voice
The brand's share of all mentions across all tracked competitors combined. High SOV means AI is focusing on you, not just listing you.
Sentiment
0–100 score reflecting how positively AI describes the brand when it does mention it.
Position
Average rank when the brand appears in a list within an AI response. Lower is better — position 1 means named first.
Website retrieval
% of AI conversations where the site is used as a source — whether cited by name or used silently in the background.
Citation rate
How often the domain is explicitly named in the response text, vs used silently. Higher means AI is actively attributing content.
Monthly AI Visibility Report — Sample
ct. May 2026 · Month 3 of monitoring · Baseline: 01 Mar 2026
Visibility ↑ 14pp
SOV ↑ 11pp
Retrieval ↑ 24pp
Google AI
ChatGPT
Platform comparison →
Visibility
42%
+14pp vs baseline
Share of voice
31%
+11pp vs baseline
Sentiment
74/100
+8 vs baseline
Position
#2
−1 vs baseline
Website retrieval
55%
+24pp vs baseline
Citation rate
68%
+19pp vs baseline
Movement vs last month and baseline
Metric Baseline Last month This month Change
Visibility 28% 36% 42% +6pp
Share of voice 20% 27% 31% +4pp
Sentiment (0–100) 66 71 74 +3
Position (avg) #3 #2 #2 —
Website retrieval 31% 47% 55% +8pp
Citation rate 49% 61% 68% +7pp
GA4 — AI referral traffic this month
AI referral sessions
214
+38 vs last month
Conversions
6
+4 vs last month
Conversion rate
2.8%
+1.4pp
Numbers are illustrative. Actual reports cover Google AI, ChatGPT and a platform comparison, plus GSC, Bing and the content plan for next month.
Want to talk it through?
The discovery call is the most efficient way to scope what's actually right for your brand.
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