Data · dataset · 2026
Schema Markup Adoption in Personal Injury Law Firm Websites: A Systematic Analysis of Structured Data Implementation Across North American Legal Services
Listed in Teesside University Research Data Repository
Structured data markup, particularly JSON-LD implementations of the Schema.org vocabulary, has become a critical factor in how search engines interpret, classify, and surface web content.
Description
Despite growing recognition of schema markup's role in search engine optimization (SEO), there has been limited empirical investigation into its adoption within specific professional service verticals. This study presents a systematic analysis of schema markup implementation across 500 personal injury (PI) law firm websites operating in the United States.
Through automated crawling and programmatic code inspection, we examine the prevalence of key schema types, including LegalService, Attorney, Organization, FAQPage, BreadcrumbList, and WebPage, and assess the completeness, accuracy, and semantic richness of deployed structured data. Our findings reveal significant gaps: 67.6% of sampled firms implement some form of JSON-LD markup, yet only 40.0% deploy the LegalService schema type specifically designed for legal service providers.
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The mean Schema Completeness Index (SCI) across sites with structured data was 11.8 out of a possible 25. Entity disambiguation remains the weakest dimension: only 84.0% of sites with schema include @id properties and 81.4% include sameAs references. These findings have implications for legal services discoverability in both traditional search engine results pages (SERPs) and emerging AI-mediated answer engines.
We propose a Structured Data Maturity Model for legal service websites and outline directions for future research.
Links
Where it is published
- DOI doi.org/10.17632/zw8k98439h.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Earth & Environmental Science · Engineering · Social Science
Provenance · 1 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/zw8k98439h.1 | 17 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |