High Priority
Deploy /sales-intelligence.txt Protocol
Establish a machine-readable inventory of your prospect database structure, data enrichment sources, and CRM integration endpoints specifically for AI sales intelligence agents.
Create a text file at /sales-intelligence.txt with a brief overview of your outbound sales intelligence stack and data sources.
Include markdown-style links to your most critical data schemas, API documentation for enrichment tools, and CRM sync protocols.
Add a 'Data Dictionary' section to clarify key fields (e.g., ICP attributes, trigger events, technographics) for AI consumption.
Configure your Outbound sales teams crawler protocols effortlessly.
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High Priority
Cognitive Sales Bot Selective Indexing
Fine-tune which prospect data segments and intelligence sources are accessible to specialized AI sales intelligence crawlers and data enrichment platforms.
User-agent: SalesIntelBot Allow: /accounts/ Allow: /contacts/ Disallow: /internal-crm-notes/
Verify your crawler permissions using the AI bot tester provided by your intelligence platform (e.g., ZoomInfo, Apollo.io's bot simulator).
Monitor data refresh rates and API call logs to ensure AI bots are accessing and processing the correct prospect and company intelligence.
Medium Priority
Structured Prospect Data Semantic Ingestion
Utilize structured data formats (e.g., JSON-LD, Schema.org for `Person` and `Organization`) to help AI sales intelligence crawlers understand prospect and company hierarchies and attributes.
Wrap your primary prospect data points (e.g., job title, company, industry) in JSON-LD structured data to signal their importance to AI scrapers.
Use `schema.org/JobPosting` or `schema.org/Organization` with descriptive properties for firmographic and technographic data extraction.
Ensure all prospect contact information tables use proper `<thead>` and `<tbody>` tags for structured data extraction by intelligence tools.
High Priority
RAG-Friendly Prospect Data Snippet Optimization
Structure your prospect and company data so it can be easily 'Chucked' and retrieved by Retrieval Augmented Generation (RAG) pipelines for AI-powered outreach.
Keep core prospect attributes (e.g., firmographics, technographics, pain points) within logically grouped data clusters (e.g., < 500 tokens per prospect profile).
Avoid ambiguous data references; ensure each data point is clearly linked to a specific company or contact within your CRM or intelligence platform.
Eliminate vague descriptors and replace them with specific, quantifiable data (e.g., 'Uses Salesforce' instead of 'Uses CRM').
