Naama

What AI says

AI engines have very limited information about Naama, a retail supplier in il. Across recent queries the company scored 5 out of 100 (Dark Signal), with the strongest dimension being Digital Footprint at 30 out of 100 and the weakest AI Recommendation Rate at 0 out of 100. None of the 3 tested AI engines (GPT-4o mini, Claude Haiku, deepseek-chat) 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

   Register company on Google Business Profile and LinkedIn

   +18 pts

   Create or claim a Google Business Profile with accurate business name, address, phone, and website URL. Establish a LinkedIn company page with company description and industry classification. These are primary signals AI systems use for entity recognition and basic discoverability.

   Identity & Presence · Low effort

2. 2

   Add structured product schema markup to website homepage

   +16 pts

   Implement JSON-LD schema.org markup (Product or LocalBusiness type) on your website listing your main retail categories and product lines. This enables AI systems to parse what you sell, improving product clarity and recommendation eligibility.

   Product Clarity · Medium effort

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