Work Sample: Moving a Brand's AI-Search Visibility from 22 to 85

The engagement

Client: Thrive Smart Systems. The goal was to get the brand surfaced and cited inside AI-generated answers (ChatGPT, Perplexity, Google AI Overviews), not only ranked in traditional search. I owned the work end to end: audit, strategy, build, and reporting.

Starting point

An AI-visibility / SEO score of 22. The site's content and structure were not being interpreted or cited by answer engines, so the brand was effectively invisible in the AI-answer surface where buyers increasingly start.

What I did

• Rebuilt site content around the question-based, high-intent queries the target audience actually asks AI tools, so pages map to how people search now.
• Restructured on-page architecture and implemented Schema markup, giving AI crawlers explicit context and authorship signals.
• Built an answer-engine (GEO / AEO) content layer: blog and landing pages designed to be lifted and cited by LLMs, not just indexed by Google.
• Shipped the pages (live and expanding organic reach) and set up GA4 and Google Search Console tracking to monitor traditional rankings and AI visibility together.

Result

The AI-visibility / SEO score climbed from 22 to 85. Pages now surface as cited, preferred answers across both generative and traditional search.

How I build and scale this work

• A library of 30+ reusable automation workflows (keyword research, backlink and competitor analysis, content repurposing, GA4/GSC reporting) that compress multi-hour tasks into minutes.
• Claude Code as a daily driver for building the tooling, integrations, and content pipelines behind the strategy.
• Systems beyond SEO: an autonomous nightly reconciliation pipeline I built for a retail client that runs untouched and flags only the exceptions, showing the same build-it-once, run-it-forever approach I bring to search.