Orsini's

What AI says

AI engines have very limited information about Orsini's, a Consumer Electronics supplier in us. Across recent queries the company scored 14 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. One AI engine (out of 4 tested: GPT-4o, Claude Sonnet, Perplexity Sonar, deepseek-chat) returned substantive information about the company across identity, sourcing, and trust prompts. No specific products were surfaced by AI engines for this supplier, which contributes directly to the Product Clarity dimension at 10 out of 100. Certifications and trust indicators referenced by AI: achc (accreditation commission for health care). 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 with Google Business Profile and consumer electronics directories

   +20 pts

   Create and verify a Google Business Profile explicitly naming Orsini's as a consumer electronics supplier with correct category tags. Submit company profile to major B2B directories (Thomas Register, Kompass, IndusNet) and consumer appliance databases to establish clear identity separation from the healthcare pharmacy entity. This ensures AI engines correctly identify your appliance/electronics business on first query.

   Identity & Presence · Low effort

2. 2

   Build structured product schema markup for core appliance categories

   +25 pts

   Add JSON-LD schema markup to your website's product pages covering refrigeration, cooktops, ranges, dishwashers, laundry, and outdoor grills with specific model numbers and SKUs. This signals to AI indexers exactly what products you supply and makes them discoverable in appliance-specific recommendation queries. Without this, AI systems cannot recommend your products in relevant buyer searches.

   AI Recommendation Rate · Medium effort

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