Respondent

What AI says

AI engines have very limited information about Respondent, a Market Research supplier in us. Across recent queries the company scored 11 out of 100 (Dark Signal), with the strongest dimension being Digital Footprint at 70 out of 100 and the weakest AI Recommendation Rate at 0 out of 100. None of the 2 tested AI engines (GPT-4o mini, Claude Haiku) returned substantive information about the company, even when queried by name, category, or domain. No specific products were surfaced by AI engines for this supplier, which contributes directly to the Product Clarity dimension at 0 out of 100. No certifications or third-party validations surfaced in AI responses, which limits the Buyer Trust dimension at 0 out of 100 and the AI Recommendation Rate at 0 out of 100. The biggest opportunity for improvement is the AI Recommendation Rate dimension; the Improvement Roadmap below lists concrete supplier-executable actions ranked by expected score uplift.

AI engine breakdown

One row per AI engine. Aggregates identity, sourcing, trust, and verdict queries.

Improvement Roadmap

Concrete actions to lift this supplier's Signal Score, ranked by impact. Generated from the latest audit.

1. 1

   Add structured company schema markup to homepage

   +18 pts

   Implement JSON-LD schema (Organization type) on your homepage with company name, description, headquarters location, and contact email. This enables AI systems to reliably identify and extract core company data during web crawls. Currently, 0/2 LLM queries found you by name, indicating schema or semantic clarity gaps that structured data directly fixes.

   Identity & Presence · Low effort

2. 2

   Create dedicated product/service listing page with schema

   +16 pts

   Publish a structured page detailing your market research offerings (e.g., survey services, qualitative research, panel services) with product schema markup. AI systems found zero specific products; explicit product pages with semantic markup force clarity and make your offerings machine-readable.

   Product Clarity · Medium effort

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