High Priority
Deploy Brand Catalog /ai.txt Protocol
Establish a machine-readable summary of your entire DTC brand's product hierarchy and key content assets specifically for AI agents and discovery platforms.
Create a text file at /ai.txt with a brief introduction of your brand's core value proposition and product categories.
Include markdown-style links to your most important catalog pages, collection pages, 'About Us', and brand story pages.
Add a 'FAQ' section in the file to answer common AI training bot queries directly, such as 'What are your shipping policies?' or 'What materials are used in Product X?'
Configure your DTC brands crawler protocols effortlessly.
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High Priority
LLM Crawler Selective Indexing for Product Pages
Fine-tune which sections of your DTC site should be ingested by AI crawlers to prioritize product catalog and conversion-focused content.
User-agent: LLM-Crawler Allow: /collections/ Allow: /products/ Allow: /brand/ Disallow: /checkout/ Disallow: /account/
Verify your crawler permissions using a generic bot tester tool, simulating common LLM user-agent strings.
Monitor crawl frequency in your server logs to ensure LLM crawlers are prioritizing product detail pages (PDPs) and category pages.
Medium Priority
Semantic HTML for Product Data Ingestion
Utilize HTML5 semantic elements and structured data to help LLM scrapers accurately understand product attributes, pricing, and availability.
Wrap individual product listings on collection pages within <article> tags to signal distinct items.
Use <section> elements with descriptive 'aria-label' attributes for different product features, specifications, and customer reviews.
Ensure all product data tables (e.g., size charts, material breakdowns) use proper <thead>, <tbody>, and <th> tags for structured data extraction by AI.
High Priority
RAG-Friendly Product Description Optimization
Structure your product descriptions and supporting content so they can be easily 'chunked' and utilized by Retrieval Augmented Generation (RAG) pipelines for personalized recommendations and chatbots.
Keep related product features, benefits, and use cases within 500-word logical containers.
Avoid ambiguous references; repeat the specific product name or key feature in section summaries to provide context for AI.
Eliminate vague pronouns (e.g., 'It', 'This') and replace them with explicit references to the Brand Name, Product Name, or specific Feature.
