Kevin Sullivan Senior SEO Strategist

SEO strategist building for the next generation of search.

I turn complex search problems into clearer information architectures, measurable organic growth, and repeatable systems—across technical SEO, entity strategy, and AI search.

View selected work Explore AI search

Operating fieldKS / 01

Research connected to implementation.

8⁺

Years across technical, local, content, and strategic SEO

5,508^%

Organic traffic growth at Ideal Turf

Within approximately 20 months

1,588^%

Organic lead growth at Ideal Turf

Within approximately 20 months

471^%

Organic lead growth at Heavenly Greens

Within approximately 3 months

Selected work

Evidence, not adjectives.

Methods, systems, and search programs built to turn ambiguous visibility problems into decisions a team can act on.

Methodology

AI Visibility Diagnostic

A repeatable method for investigating how brands are found, interpreted, cited, and recommended across generative search—and translating those observations into implementation priorities.

Cross-platform analysis
Entity interpretation
Prioritized action

Operating system

AI-Assisted SEO Workflows

A human-in-the-loop system for standardizing recurring SEO analysis, improving consistency, and protecting the strategic judgment automation cannot replace.

Repeatable workflows
Human review gates
Scalable delivery

Experimental build

Turf Network

An industry resource and research environment used to test entity architecture, structured information, internal relationships, and AI-search retrieval.

2,500+ organizations
142 entity pages
Architecture experiments

AI search research

Studying how search systems understand and recommend information.

I have analyzed hundreds of responses across Google AI Overviews, ChatGPT, Claude, Gemini, and Perplexity—looking for patterns in brand inclusion, source selection, citations, entity recognition, and recommendation behavior.

The goal is not to turn limited observations into universal rules. It is to ask better questions, build clearer diagnostics, and create more useful implementation priorities.

Diagnostic modelObservation → action

01
ObserveWhat appears, where, and in what context?
02
InterpretWhat do inclusion, omission, sources, and relationships suggest?
03
PrioritizeWhich entity, architecture, validation, or content changes are actionable?
04
Test againWhat changed, what did not, and what remains uncertain?

How I work

From research to a system that can improve.

01
Research
Understand the environment, audience, entities, competitors, prompts, and constraints.
02
Structure
Organize the information, relationships, priorities, and implementation path.
03
Build
Create the strategy, architecture, workflow, deliverable, or experiment.
04
Test
Examine performance, inclusion, retrieval, outputs, and feedback.
05
Refine
Change the approach when evidence challenges the original hypothesis.

“Content depth is not the same thing as information clarity.”

A principle earned through Turf Network: when long topical clusters stopped serving the information model, I removed them and shifted toward clearer entity pages, relationships, and internal architecture.

Established SEO outcomes

Strategy grounded in business results.

AI search is an evolution of an established SEO practice—not a replacement for the technical, architectural, and strategic fundamentals beneath it.

Heavenly GreensInformation architecture

Simplifying 1,000+ pages into an intentional search architecture.

Restructured the site into approximately 100 targeted assets through content auditing and information-architecture redesign.

Organic traffic: +1,523%
Organic leads: +471%
Posts consolidated: 1,000+

Results measured within approximately 3 months.Read the Heavenly Greens case study

Ideal TurfMulti-location SEO

Building a scalable multi-location organic search strategy.

Developed and executed an integrated Local, technical, content, and information-architecture strategy.

Organic traffic: +5,508%
Organic leads: +1,588%
Goal completions: +3,833%

Results measured within approximately 20 months.Read the Ideal Turf case study

Kevin SullivanSEO strategist

About

Eight years of search work. One recurring focus.

Make complex search problems clearer, more measurable, and more actionable.

My work has progressed from traditional, technical, and Local SEO into information architecture, entity strategy, AI-search research, and workflow development. The terminology has changed. The underlying work—understanding systems, organizing information, testing assumptions, and turning findings into practical decisions—has remained consistent.

Technical SEO→Information architecture→Entity strategy→AI search

Next conversation

Looking for someone who can connect search strategy to the systems behind it?

I’m interested in senior SEO, AI-search, organic strategy, and search-focused consulting opportunities.

kevin@kevinsullivan.io