Legal

Personal injury firm, Baltimore — via partner agency, white-label

Wrong-fit AI leads → 2 signed clients in 4 months

4% visibility

before

21%+ sustained

after
-
120
days
Scope
Baltimore PI prompts, English + Spanish · 4 engines · weekly re-scores on identical prompts · via partner agency
the situation

This firm came in with AI presence already — ChatGPT was surfacing their name to Marylanders asking about injury attorneys. But every AI-sourced lead was wrong: wrong jurisdiction, wrong case type, no claim, or already settled. Five leads in two months, zero signed. The problem wasn't whether AI mentioned them. It was what AI mentioned them for.

What we measured first

Overall AI visibility at 4% across Google AI Overviews, ChatGPT, Perplexity and Gemini. Presence concentrated on prompts mismatched to the firm's practice focus. Baseline lead quality: 0 signed from 5 AI-sourced inquiries in the prior two months.

what we did

Foundation and targeting work in English and Spanish — re-pointing the firm's AI signal toward the case types and jurisdiction it actually handles, then building the mentions, listings and content that corroborate it. (Phase-level by design; the sequence is our method.)

What changed

Visibility tripled within 10 days and peaked at 46% by week six, holding 21%+ sustained. #1 brand position and 100% Share of Voice on the market's top slip-and-fall prompt, featured in Google AI Overview. And the number that matters: two signed clients traced directly to ChatGPT — attribution tracked in the firm's intake system — versus 0-for-5 before the engagement.

"
Two signed clients, both traced to ChatGPT — after 0-for-5 in the two months prior.
"

Attribution via partner agency intake data

What this means for you

Visibility isn't the goal — being recommended for the right cases is. See where you stand. → Get your Trust Index