Matilde Ferrer Ortega

What AI says

AI engines have very limited information about Matilde Ferrer Ortega, a Agriculture supplier in es. Across recent queries the company scored 8 out of 100 (Dark Signal), with the strongest dimension being Digital Footprint at 50 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, and trust queries.

Improvement Roadmap

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

1. 1

   Register company on Google Business Profile and LinkedIn

   +18 pts

   Create a Google Business Profile with complete business name, address, phone, and website URL. Establish a LinkedIn Company Page with basic details and company description. These are foundational directories that AI discovery engines crawl first; current zero detection suggests the company lacks presence on these essential platforms.

   Identity & Presence · Low effort

2. 2

   Document and publish product/service list with structured data

   +16 pts

   Create a dedicated Products or Services page on your website listing specific agricultural offerings (crops, equipment, services, or inputs supplied). Use schema.org markup (Product or Organization schema) to label each item. AI systems currently find zero product mentions; structured data makes offerings machine-readable and improves recommendation rankings.

   Product Clarity · Medium effort

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