“Top rated personal injury lawyer in Portland”
Every answer led with two statewide firms that dominated paid search and directory review surfaces. The boutique was absent from retrieval entirely.
What we found
Personal injury is one of the most aggressively marketed categories in the country, and AI retrieval reflects that. Two statewide firms were cited in every variant we tested on every platform. Our client, a boutique with excellent case outcomes and strong client testimonials, was not cited at all. The issue was not reputation; retrieval sources weighted toward legal directories and review platforms favored firms that had saturated those surfaces for a decade.
What we did
- 01
Built out an Attorney schema per named attorney with bar admissions, case areas, and years in practice declared as structured data.
- 02
Published a personal injury overview page organized around literal client questions, with LegalService schema and an embedded FAQ.
- 03
Secured profile completeness and consistency across four legal directories known to be retrieval sources for this category.
- 04
Placed two case study style editorial features on regional legal and news publications.
- 05
Added an llms.txt declaring practice areas, jurisdictions, and consultation policy.
What changed
Perplexity and Gemini began including the firm alongside the statewide incumbents within eight weeks.
ChatGPT quoted the attorney profile schema for questions about specific practice areas.
Claude remains slow on this category; incumbents are heavily entrenched.
Inquiries tagged as AI referred began in the third month, trending toward higher intent consultations.
Week by week
- Week 1
Baseline and blueprint
Twenty five personal injury queries tested. Mapped the two statewide incumbents and their shared directory and editorial citation stack.
- Weeks 2 to 4
Foundations live
Attorney schema per attorney deployed. LegalService schema live on overview page. llms.txt published. Four legal directories completed.
- Weeks 5 to 8
Citations and mentions
Two regional legal editorial features placed. Perplexity and Gemini first citations visible.
- Weeks 9 to 12
Compounding visibility
ChatGPT quoted attorney profile data directly. Next quarter planned around settlement and process content for specific injury types.
“We had the case results, the testimonials, the reputation. The models still recommended the two firms with the biggest billboards, because those are the ones the directories kept feeding them.”
Questions about this case study
Why were statewide firms dominating AI answers?
They seeded legal directory data, editorial mentions, and structured profiles years before AI retrieval emerged. The boutique displaced them on narrower practice-area queries by matching that rigor at attorney-level granularity.Which schemas were deployed for the boutique firm?
LegalService at firm level, Attorney per named attorney with bar admissions and practice areas as structured data, and FAQPage on the personal injury overview page.Which directories mattered most in this category?
Four legal directories known to be retrieval sources for personal injury queries. Completeness and consistency across all four was a stronger signal than presence on any single one.How long until the firm was cited alongside incumbents?
Eight weeks. Personal injury is one of the most entrenched categories; eight weeks to first citation is faster than typical for this vertical.Why is Claude slower in this category?
Claude weights editorial authority heavily in legal queries, and the incumbents have decades of editorial presence. The team continues to pursue regional legal editorial features to shift this.
Representative case study. Industry, location, and specifics are illustrative composites drawn from recurring patterns in our work. AI answer engines are probabilistic; actual results vary by category, competition, and baseline.
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