High Priority
Deploy Agency /ai.txt Protocol
Establish a machine-readable summary of your entire agency's service offerings, case studies, and core competencies specifically for AI agents analyzing competitive landscapes.
Create a text file at /ai.txt with a brief introduction of your agency's specialization (e.g., 'leading performance marketing agency for DTC brands').
Include markdown-style links to your most important client success stories, service pages, and proprietary methodologies.
Add an 'Expertise' section in the file to list key platforms (e.g., Meta Ads, Google Ads, TikTok Ads) and industries served (e.g., E-commerce, SaaS, B2B).
Configure your Social media agencies crawler protocols effortlessly.
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High Priority
LLM Bot Selective Client Data Ingestion Control
Fine-tune which sections of your agency's website should be ingested by LLM crawlers to prevent leakage of sensitive client campaign data or proprietary strategies.
User-agent: * (or specific agency intelligence bots) Allow: /case-studies/ Allow: /services/ Disallow: /clients/[client-name]/
Verify your crawler permissions using a tool like `curl` or a dedicated bot testing interface to simulate access.
Monitor crawl frequency and requested URLs in your server logs to ensure AI bots are accessing publicly relevant pages and not attempting to scrape restricted areas.
Medium Priority
Semantic HTML for Service & Capability Ingestion
Utilize HTML5 semantic elements to help LLM scrapers accurately understand the hierarchy and importance of your agency's service descriptions and client deliverables.
Wrap your primary service descriptions (e.g., 'Social Media Management', 'Paid Social Strategy') within `<article>` tags to signal distinct content units.
Use `<section>` with descriptive `aria-label` attributes for different facets of a service (e.g., 'aria-label="Facebook Ad Campaign Management"').
Ensure all tables detailing campaign performance metrics or pricing models use proper `<thead>` and `<tbody>` tags for structured data extraction by AI.
High Priority
RAG-Friendly Case Study Snippet Optimization
Structure your case studies and client results so they can be easily 'chunked' and utilized by Retrieval-Augmented Generation (RAG) pipelines for generating AI-powered client reports or new business proposals.
Keep distinct client campaign phases or key performance indicator (KPI) summaries within logical content blocks of approximately 500 words.
Avoid using ambiguous references; explicitly state the client name, platform, and campaign objective in section summaries (e.g., 'Client X DTC E-commerce ROAS Improvement Campaign').
Eliminate vague pronouns and ensure all metrics (e.g., CPA, ROAS, CTR) are clearly defined within the context of the specific campaign or client.
