What exactly is AiVIS Cite Ledger?

AiVIS Cite Ledger is an evidence-backed AI citation audit and remediation system. It measures how AI models, ChatGPT, Perplexity, Claude, and Google AI, interpret, trust, and cite your web content. The result is a 0–100 CITE LEDGER score across seven weighted dimensions, with BRAG evidence-linked findings and prioritized fixes.

How is this different from Semrush, Ahrefs, or Clearscope?

Traditional SEO tools optimize for keyword ranking in traditional search results. AiVIS Cite Ledger audits citation readiness, the specific signals that determine whether AI answer engines retrieve and cite your content. A page can rank #1 on Google and be completely invisible to AI answer synthesis.

What is BRAG and how does it make findings trustworthy?

BRAG stands for Based-Retrieval-Auditable-Grading. It ties every audit finding to a real, traceable element on your page, a specific heading, schema block, meta tag, or content section, each carrying a unique evidence ID. You can open the element, verify the finding, and recheck it after a fix. No black boxes.

Is the free tier genuinely useful, or just a teaser?

The Observer (free) plan gives you a full composite CITE LEDGER score and all seven dimension letter grades, so you can see exactly where you stand and which categories are hurting you. BRAG evidence IDs and prioritized fix packs require a paid plan. Three audits per month, no credit card.

AI Visibility for E-Commerce Stores | AiVIS Cite Ledger

When shoppers ask AI 'what are the best running shoes under $150?', AI models cite stores with machine-readable product data. Your catalog needs structured data to compete.

AI-Powered Shopping

AI shopping assistants are changing how people discover products. Instead of browsing marketplaces, users ask AI for curated recommendations, and AI cites stores with the best structured product data.

E-commerce sites on Shopify, WooCommerce, and BigCommerce need Product schema, review markup, and clear categorization to appear in these AI-generated recommendations.

E-Commerce Schema Essentials

Product schema: name, description, image, offers (price, currency, availability), brand, and sku.

AggregateRating: your average review score and total review count. AI models reference ratings in product comparisons.

BreadcrumbList: shows product hierarchy (Store > Category > Subcategory > Product) for AI navigation.

FAQ schema on product pages: answers common buyer questions (shipping, returns, sizing) for direct AI extraction.

Category and Collection Pages

Category pages with structured data help AI answer broader queries like 'best X products' by providing curated collections.

Include filtering metadata and product counts so AI understands your catalog depth.

Write unique category descriptions that explain what the category contains and who it's for, AI models use these for classification.

Frequently Asked Questions

Does my Shopify store need extra schema?: Shopify adds basic Product schema, but it's often incomplete. Add FAQ schema, review markup, and enhanced Product properties for full AI visibility.
How do product reviews affect AI?: AggregateRating schema lets AI cite your review data in product comparisons. Products without review markup are harder for AI to evaluate.
Should I add schema to every product?: Yes, every product page should have complete Product schema. This is especially important for your top-selling products.