High Priority
Deploy Wholesale Sitemap Protocol (/ai.txt)
Establish a machine-readable hierarchy of your entire wholesale catalog and informational content specifically for AI agents and B2B search crawlers.
Create a text file at /ai.txt with a concise introduction to your wholesale operation and product categories.
Include markdown-style links to your most important wholesale catalog pages, distributor portals, and industry-specific resource hubs.
Add a 'FAQ' section within the file to address common queries from AI bots regarding product availability, minimum order quantities (MOQs), and shipping regions.
Configure your Wholesale ecommerce crawler protocols effortlessly.
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High Priority
B2B Crawler Selective Indexing
Fine-tune which sections of your wholesale platform should be ingested by AI crawlers focused on B2B procurement and product discovery.
User-agent: WholesaleBot Allow: /catalog/ Allow: /distributor-program/ Disallow: /guest-checkout/
Utilize the AI crawler's verification tool (e.g., 'AI Search Console' for relevant bots) to confirm crawler permissions.
Monitor crawl frequency and patterns in your server logs to ensure B2B crawlers are accessing key product data and buyer-centric content.
Medium Priority
Structured Data for Product Attributes
Leverage semantic HTML and schema.org markup to help AI crawlers accurately understand the hierarchy and attributes of your wholesale product listings.
Wrap your main wholesale product descriptions and specifications within `<article>` tags to signal their importance.
Use `<section>` tags with descriptive 'data-label' attributes for distinct product features, materials, or compliance standards (e.g., 'data-label="Material Composition"').
Ensure all product data tables (e.g., size charts, technical specs) use proper `<thead>`, `<tbody>`, and `<th>` tags for structured data extraction by AI.
High Priority
RAG-Optimized Product Information Snippets
Structure your product details and technical specifications so they can be easily 'chunked' and utilized by Retrieval-Augmented Generation (RAG) pipelines for accurate buyer inquiries.
Keep related product specifications, use cases, and compatibility information within coherent logical blocks (e.g., under 500 words per distinct attribute group).
Avoid ambiguous referencing; clearly state the product name or SKU in section summaries and attribute descriptions.
Eliminate vague pronouns (e.g., 'this unit', 'it') and replace them with explicit product names, model numbers, or feature identifiers to ensure precision in AI responses.
