Start with a reproducible baseline
GEO Strategy & AI Search Audit

Some of the 500+ brands we've worked with
See all referencesDiagnose before implementation
Work out what is happening before choosing a fix


AI Search VisibilityAudit & Baseline


GEO Roadmap& Measurement Design
What the audit can answer
A visibility score only records what happened
We start with what the platforms visibly return. Your teams can then check crawl access, rendered content, entity facts, claim support, cited sources, and first-party outcomes. The surrounding evidence tells us whether the observation supports a diagnosis.
After the diagnosis
The evidence travels with the finding
Once reproduced, technical, content, entity, authority, and measurement findings move to the relevant GEO capability. Strategy keeps the priority, owner, acceptance rule, and original evidence connected so the delivery team does not have to repeat the investigation.
Scope and ownership
The evidence travels with the finding, so delivery never repeats the investigation
The sample is agreed before collection, which keeps prompt selection tied to real decisions rather than flattering ones.
Your audiences, markets, journey stages, platforms, and run conditions define the panel before anything is collected, and raw responses stay stored with their citations while specialists inspect crawl access, rendered text, entity facts, page support, recurring sources, and any first-party outcomes available for comparison. Observations, proxies, hypotheses, and constraints are labelled separately, and unresolved platform behaviour stays an explicit unknown rather than a soft conclusion. Strategy keeps the priority, owner, acceptance rule, and original evidence connected; technical, content, entity, authority, and measurement findings move to the relevant GEO capability with that record attached.
Build the plan from evidence your team can replay
Agree the sample before collection
Your audiences, markets, journey stages, platforms, and run conditions define the panel. Agreeing them first keeps prompt selection tied to actual decisions, including results that present the brand unfavorably.
Save the answers with their sources
Raw responses and citations stay together. Specialists inspect crawl access, rendered text, entity facts, page support, recurring sources, and any first-party outcomes available for comparison. The record remains versioned.
Mark the limits of the evidence
Observations, proxies, hypotheses, and constraints receive separate labels, while unresolved platform behavior remains an explicit unknown.
Make the funding decision
A validated finding may be fixed, tested, monitored, deferred, or rejected. Its dependencies, owner, measure, review window, and stop rule remain part of that decision.
Clients on the work
What it is like to work with Zeo
Our clients describe the work in their own words.
Adjacent search evidence
Case Studies
Organic search engagements establishing the indexation, content depth, and domain authority that AI answer engines draw from.
People who watch how AI cites a brand
GEO work starts with recording what AI answers actually say about a brand today, then moves to the parts you can influence. The consultants below work on the specific capability this page covers.

Aybüke Göktuna
Senior SEO Analyst

Can Mutioğlu
Senior SEO Executive

Gülşah Şahin Özkan
Senior SEO Analyst

Ezgi Gülsen Yaylı
SEO Manager

Samet Özsüleyman
SEO Manager

Elif Naz Akan Karakoç
Senior SEO Executive

Ozan Ketenci
VP of Consulting & Strategy

Burak Pehlivan
Co-founder & CEO

Mehmet Aktuğ
Co-Founder & COO

Metehan Urhan
New Business & Partnership Manager

Zafer Yıldız
Web Analytics Manager

Ataberk Yüzat
SEO Executive

Didem Himmetli
Marketing Executive
Tools we use
What we watch AI answers with
Generative search leaves less to read than a rankings report does, so most of this work is assembling evidence from tools that were never built for it.
AI answer and citation tracking
- ProfoundThis page's own first step, agreeing the sample before collection, is what Profound's panel-based tracking exists to do: the same question set runs repeatedly across the platforms and markets in scope, and every answer is retained with its date, model, and mode, which is the raw material the roadmap's baseline gets built from.
- Peec AIWhere the audit needs to separate a branded question's result from a non-branded category question, Peec AI's prompt-level tags are what keep that distinction visible instead of collapsing everything into one score, which matters directly to this page's own point that a single visibility number cannot explain a pattern.
Entity and structured data
- Screaming FrogOnce a material pattern is confirmed in the panel data, this page's diagnosis step inspects technical access alongside entity facts, content support, and source exposure; Screaming Frog is the crawl that answers the technical-access half of that question before the roadmap assigns the finding to a specific method.
- Google Search ConsoleBefore concluding that an AI engine is choosing not to cite a page, the audit checks Search Console to confirm the page is indexed and served at all, since an indexing problem and a selection problem call for different roadmap items entirely.
Content evidence and sourcing
- NotionThe audit's final handoff, a roadmap that names the owner, measure, and stop rule for each decision, gets written and shared as a Notion document, since a roadmap only funds work if every team it assigns work to can open and reference the same record.
Establish the baseline
Find out whether GEO work is justified


Before the first sample
































