What the diagnostic actually shows when we run it against a real business.

Documented work with home service operators. What the audit surfaced, what the work that followed looked like, and what changed in the months after. Real businesses, anonymized for confidentiality, with the findings preserved in detail.

A note on anonymization

Each business covered here has given written consent to publish the work. To protect the operator’s competitive position, all identifying detail is removed. Case studies are presented by category and approximate size band only. The findings, the work, and the outcomes are documented exactly as they unfolded.

Three case studies currently being written. Publishing through summer 2026.

Case Study Vol. I

A mid-market exterior services contractor in the Northeast.

2026

Coming soon · Summer 2026

The diagnostic that surfaced the gap, and what it took to close it.

A multi-location exterior services business running mature traditional marketing but invisible across AI search. The audit named the gap. The work that followed addressed entity authority, source quality, and the structural decisions sitting under the visibility problem. Outcomes documented at 60 and 120 days.

Case Study Vol. II

A regional paving operator in a top-25 metro market.

2026

Coming soon · Summer 2026

When the foundational decision had never been made, and what changed once it was.

A paving business with a strong local reputation and ten years of category-leading review velocity, but missing from AI search answers in its own market. The audit surfaced a decision the operator had never made, that infrastructure had quietly made on their behalf. Walking through the decision, the recovery work, and the measured visibility shift that followed.

Case Study Vol. III

A growth-stage roofing operator in a major Sun Belt market.

2026

Coming soon · Summer 2026

What it looks like when a category leader is showing up everywhere, except in AI search.

A growth-stage roofing business already winning on traditional channels, looking at where the next decade of customer acquisition would come from. The audit showed the gap between local-market dominance and AI search presence. The work that followed addressed both halves. Outcomes documented across a 90-day window.

Same structure across every case study. Findings, work, outcomes.

i.

The findings

What the diagnostic surfaced, in detail. The specific gaps documented across ChatGPT, Google AI, and Perplexity. The infrastructure and source-quality issues that were producing the gap. Citation-level evidence, the same way it appears in a full audit report.

ii.

The work

What was done about it. The decisions made by the operator, the technical and editorial work that followed, and the ordering of that work. What worked on the first attempt, what required a second pass, and what got deferred to a later phase.

iii.

The outcomes

What changed in the months that followed. Measured visibility shift across the three AI platforms, with before and after citation patterns. Honest reporting on what did and didn’t move, and the reasonable interpretation of the timeline.

The same diagnostic that opens every case study, delivered in five business days.

The Market Visibility Audit is the first step in every engagement documented here. It’s also offered as a stand-alone deliverable, whether or not we ever work together further.