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SearchSynth.
Generative Engine Optimization

Your buyers ask an AI first. Make sure it names you.

GEO is the work of becoming the source an answer engine reaches for. We pick the queries that actually precede a purchase, baseline who gets cited today, fix the entity and schema layer that makes you machine-legible, seed the third-party sources models lean on, and track every engine weekly so you can see exactly which answers flipped.

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PRIORITY QUERIES →GPTCLAUDEGEMINIPPLXAIOSHARE OF VOICEcited

the scoreboard: every priority query, every engine, sampled weekly

Tracked weekly, query by query
5 enginesTracked weekly, query by query
Before citation movement shows
30–60 daysBefore citation movement shows
Reporting, not vanity scores
Per-queryReporting, not vanity scores
The traffic model we plan for
Zero-clickThe traffic model we plan for

The GEO retainer, unpacked

No single tactic wins a citation. Answer engines synthesise from your site, your schema, and what the rest of the web says about you — so the work runs across all three at once.

Priority query selection

We build the prompt set that matters: the 60–200 questions your buyers actually type before they shortlist, in the phrasing they use with a chatbot — which looks nothing like the keywords in your rank tracker.

  • Sales-call and support-ticket mining for real language
  • Comparison, alternative and 'best X for Y' prompt families
  • Commercial-intent scoring so effort follows revenue

Citation baseline matrix

Before anything changes, we record who gets cited for every priority query across every engine — you, your competitors, and the third-party pages the models actually pull from. That matrix is the scoreboard for the whole engagement.

  • Brand presence, competitor presence and verbatim answer text
  • Source-URL attribution: which pages earn the citation
  • Sentiment and accuracy check on how you're described

Entity & schema architecture

Models resolve entities, not strings. We make your brand, products, people and claims unambiguous with a canonical entity page, connected JSON-LD, and consistent facts across every property you control.

  • Organization, Product, Service, FAQ and Person schema
  • sameAs graph across Wikidata, Crunchbase and directories
  • One canonical fact set, reconciled site-wide

llms.txt & machine-readable layer

A maintained /llms.txt giving crawlers a clean, plain-language summary of who you are, what you sell and the direct answers to your priority queries — plus crawler access rules that don't accidentally lock out the engines you want.

  • Direct-answer file for priority queries
  • robots.txt audit for GPTBot, ClaudeBot, PerplexityBot and friends

Citation-worthy content

Answer engines quote specifics: original data, named methods, clear definitions, dated figures. We build the pages that give a model something concrete to lift, structured so the useful part is easy to extract.

  • Original research and benchmark data
  • Definitional and comparison pages built for extraction
  • Statistics with sources, dates and clear attribution

Off-site answer seeding

Much of what a model says about you comes from pages you don't own. We work the ranked listicles, review platforms, industry directories and community threads that engines lean on — transparently, and without astroturfing.

  • Placement in the listicles models cite most
  • Review-platform and directory coverage
  • Genuine expert participation in community answers

AI Overview & answer monitoring

Weekly sampling of every priority query on every engine, logged with the full answer text, so a competitor displacing you shows up as a dated delta rather than a quarter-end surprise.

  • Weekly multi-engine sampling with answer archives
  • Displacement and misinformation alerts

Share-of-voice reporting

One number your board understands, with the query-level detail underneath it: your citation rate against named competitors, trended monthly, alongside referral traffic from AI surfaces.

  • AI share of voice vs. named competitors
  • Referral analytics from chatgpt.com, perplexity.ai and AI Overviews
  • Quarterly competitive benchmark

What you get every month

  • Live citation matrix

    Every priority query, every engine, refreshed weekly, with the delta against last week highlighted.

  • Entity & schema implementation

    Deployed JSON-LD, a canonical entity page and a reconciled fact set — not a spreadsheet of recommendations.

  • Maintained /llms.txt

    Kept current as your positioning, pricing and product set change.

  • Citation-worthy content

    Two to four extraction-ready assets per month, built around the queries you're losing.

  • Off-site placement log

    Every listicle, directory and community placement, with the engine response before and after.

  • Monthly readout

    Share of voice, wins, losses, and what we're doing about the losses. Thirty minutes, live, with the analyst who did the work.

Engines and tooling we work across

Answer engines

  • ChatGPT
  • Claude
  • Gemini
  • Perplexity
  • Copilot
  • AI Overviews

Visibility tracking

  • Profound
  • Peec AI
  • Otterly
  • Custom prompt harness

Entity & structured data

  • Schema.org
  • Wikidata
  • Knowledge Graph API
  • JSON-LD

Analytics

  • GA4
  • Search Console
  • BigQuery
  • Looker Studio
Process

The first 90 days

  1. Weeks 1–2

    Baseline & prompt set

    We build the priority query set and record the starting citation matrix across every engine. Everything afterwards is measured against this.

  2. Weeks 3–4

    Entity & schema foundation

    Canonical entity page, JSON-LD rollout, sameAs graph, llms.txt and a crawler-access audit. This is the layer everything else compounds on.

  3. Weeks 5–8

    Content & off-site push

    Extraction-ready assets for the queries you're losing, plus placement work on the third-party sources the models are already citing.

  4. Weeks 9–12

    Measure, cut, double down

    First real signal on which queries moved. We drop what didn't work, expand what did, and widen the prompt set.

  5. Ongoing

    Hold the position

    Answers get re-synthesised constantly and competitors keep pushing. Weekly sampling catches displacement while it's still cheap to fix.

GEO engagements

Audits are fixed-fee and standalone. Retainers assume a 6-month horizon, because citation patterns don't move in four weeks.

AI Visibility Audit

$2,400

fixed fee · 2 weeks

Where you stand today across every engine, why, and the ranked list of what would change it.

  • Priority query set built with your team
  • Full baseline citation matrix, all engines
  • Entity, schema and crawler-access review
  • Competitor citation teardown
  • Prioritised 90-day roadmap

Finding out whether you have a GEO problem at all.

Get started
Most chosen

GEO Retainer

from$4,500

per month · 6-month minimum

The full programme: entity foundation, content, off-site seeding and weekly tracking across every engine.

  • Everything in the Audit
  • Entity, schema and llms.txt implementation
  • 2–4 citation-worthy assets per month
  • Off-site placement and answer seeding
  • Weekly multi-engine tracking
  • Monthly live readout

Brands whose buyers research through AI before they ever visit.

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Enterprise GEO

from$12,000

per month · custom scope

Multi-brand, multi-market programmes with the internal enablement to match.

  • Multi-region and multi-language prompt sets
  • Product-line and sub-brand entity architecture
  • Misinformation monitoring and correction
  • Custom tracking dashboards on your BI stack
  • Enablement for in-house content teams

Large catalogues, several brands, or regulated claims.

Get started

Prices are starting points, not quotes. Scope drives the number, and you get a fixed one before you commit.

GEO

GEO questions, answered

Is GEO just SEO with new branding?
They overlap but they optimise for different things. SEO competes for a ranked position on a results page; GEO competes to be the source a model synthesises its answer from. The mechanics differ — entity clarity and machine-readable facts matter more than link volume, third-party pages you don't own carry unusual weight, and success is a citation rate rather than a rank. Technical SEO is the foundation underneath it, which is why we run both.
How do you actually measure it?
We sample every priority query on every engine weekly and log whether you were mentioned, whether you were cited with a link, which source page earned the citation, and what the answer said about you. That produces a citation rate per query, an aggregate share of voice against named competitors, and a weekly delta report. We pair it with referral traffic from AI surfaces, though that undercounts badly — most of the value lands as a buyer arriving already convinced.
How long before we see movement?
Schema and entity fixes can register within days to a few weeks. Citation patterns for competitive commercial queries typically take 60–90 days, because models weight established third-party consensus and that takes time to shift. Anyone promising a fixed timeline for a specific query is guessing.
Does GEO actually drive revenue, or just mentions?
Being the brand an answer engine names during the research phase is worth more per impression than a blue link, because the recommendation arrives with the model's implied endorsement. But it is genuinely harder to attribute — much of it is zero-click. We track referral traffic where it exists, and we recommend adding a 'how did you hear about us' field, which is where most of our clients first see it show up.
Can you fix an AI saying something wrong about us?
Often, yes. Model hallucinations about a brand usually trace back to a real source: an outdated page, a stale directory entry, a wrong Wikipedia line, a review site with old pricing. We locate the source, correct it where it's controllable, and publish authoritative counter-evidence where it isn't. It's not instant — models retrain and re-crawl on their own schedule — but it is tractable.
Do we need GEO if we already rank well on Google?
Ranking well is a real advantage — you're already in the corpus these models learned from. It just isn't sufficient, because the engines reformat the answer and choose which sources to name. We routinely find clients holding position one who go completely uncited for the same question asked conversationally. The audit tells you which of those two situations you're in.

Find out what the models say about you. Today.

We'll run your top ten commercial queries through every major engine before the call and walk you through the answers. No deck, no pitch — just what's actually being said.

30-minute strategy call

With an engineer, not a closer

Book a strategy call

Typical reply time: under 4 business hours.

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