Prompt Patterns
9 production-ready patterns AutoClaygent uses for common use cases
Why These Patterns Are Different
These aren't generic "find company info" patterns. They're battle-tested approaches from real GTM engineering projects that achieve 85%+ accuracy. Each pattern solves a specific problem that native integrations can't handle well.
These patterns use techniques like URL subdomain detection (95% accuracy vs 70% for text scraping) and decision trees with explicit branching logic.
AutoClaygent knows all 9 patterns and chooses the right one based on your description. It customizes each pattern for your specific use case—adding the right fallbacks, sources, and output fields automatically.
Pattern 1: Business Model Classification
Use case: Classify service businesses by revenue model (subscription vs transactional vs hybrid)
Why it's valuable: Most CRM data about "business type" is wrong. Explicit decision trees beat generic prompts.
Given the company domain: {{domain}}
Classify this business by their revenue/pricing model.
**Research Steps:**
1. Navigate to {{domain}} and look for:
- /pricing, /plans, /membership, or /subscribe pages
- Explicit dollar amounts with time periods ($/month, $/year)
2. Classify based on what you find:
SUBSCRIPTION = Recurring membership model
- Look for: "monthly", "annual", "per seat", "subscription"
- Customer pays regularly (weekly/monthly/yearly)
- Examples: "$99/month", "Starting at $49/user/month"
TRANSACTIONAL = Per-use or one-time payment
- Look for: "per project", "one-time", "pay as you go"
- Customer pays for each service/product
- Examples: "$500 per audit", "Quote-based pricing"
HYBRID = Offers BOTH recurring AND one-time options
- Has subscription tiers AND pay-per-use options
- Examples: "Base plan $49/mo + $5 per additional user"
ENTERPRISE = Custom/contact sales pricing
- No public pricing, "Contact us", "Request demo"
3. If no pricing page exists:
- Check /about or homepage for business model clues
- Look at how they describe their service delivery
**Output as JSON:**
{
"business_model": "subscription" | "transactional" | "hybrid" | "enterprise" | null,
"pricing_found": true | false,
"pricing_details": "Brief description of what you found" | null,
"evidence_url": "URL where you found pricing info",
"confidence": "high" | "medium" | "low"
}Pattern 2: Platform Detection via URL Patterns
Use case: Detect what SaaS platforms a company uses by analyzing portal URLs
Why it's valuable: URL patterns are 95%+ accurate. Companies use vendor-hosted portals that reveal their tech stack.
Given the company domain: {{domain}}
Detect what platforms this company uses by analyzing their portal/login URLs.
**Research Steps:**
1. Look for customer-facing portals:
- Check {{domain}}/login, {{domain}}/portal, {{domain}}/app
- Look for "Client Login", "Patient Portal", "Customer Portal" links
- Check the footer for portal links
2. When you find a portal link, analyze the URL pattern:
**Subdomain Patterns (highest confidence):**
- {company}.platformname.com → Uses Platform Name
- app.{company}.com redirecting to vendor → Uses that vendor
- portal.vendorname.com/{company} → Uses Vendor Name
**Common Platform URL Patterns:**
- *.salesforce.com → Salesforce
- *.hubspot.com → HubSpot
- *.zendesk.com → Zendesk
- *.calendly.com → Calendly
- *.webflow.io → Webflow
3. Check for scheduling/booking tools:
- Look for "Book Now", "Schedule", "Appointments"
- These often reveal Calendly, Acuity, Cal.com, etc.
**Output as JSON:**
{
"platforms_detected": [
{
"platform_name": "Name of platform",
"platform_category": "CRM | Support | Scheduling | Chat | Website",
"detection_method": "subdomain | redirect | widget | integration_page",
"evidence_url": "URL that revealed this"
}
],
"portal_url": "Customer portal URL if found" | null,
"confidence": "high" | "medium" | "low"
}
**Why this works:** URL subdomain patterns are 95%+ accurate vs text scraping at 70%. DNS doesn't lie.Pattern 3: CRM Validation & Mismatch Detection
Use case: Find where your existing CRM data is WRONG by comparing to website reality
Why it's valuable: Finding 5,000 wrong records is more valuable than enriching 50,000 records.
Given:
- Company domain: {{domain}}
- CRM field to validate: {{field_name}}
- Current CRM value: {{crm_value}}
Validate if the CRM value matches what's actually on the company's website.
**Research Steps:**
1. Navigate to {{domain}} and find information related to {{field_name}}
2. Look in these locations based on field type:
- Company size/employees → /about, /team, /careers
- Industry/vertical → Homepage, /about, meta description
- Location/HQ → /contact, /about, footer
- Business type → /pricing, /about, homepage
3. Compare what you find to the CRM value:
MATCH = Website confirms CRM value
MISMATCH = Website contradicts CRM value (specify what you found)
STALE = CRM value appears outdated
UNVERIFIABLE = Cannot confirm or deny from website
**Output as JSON:**
{
"field_validated": "{{field_name}}",
"crm_value": "{{crm_value}}",
"website_value": "What you found on website" | null,
"validation_status": "match" | "mismatch" | "stale" | "unverifiable",
"evidence": "Specific text proving your finding",
"recommendation": "keep" | "update" | "review",
"confidence": "high" | "medium" | "low"
}
**Why this works:** Finding errors in existing data is more valuable than adding new fields.More Patterns (Full Course)
The complete course includes 6 additional production patterns:
| Pattern | Use Case | Key Innovation |
|---|---|---|
| Digital Maturity Profiling | Score prospects by online sophistication | Email domain as proxy for website existence |
| B2B vs B2C Detection | Determine target market | Navigation menu as primary signal |
| Corporate Structure Detection | Find parent companies, subsidiaries | Identify actual decision-maker level |
| Buying Intent Detection | Find companies ready to buy NOW | Funding + leadership timing signals |
| Multi-Axis Classification | Classify along 5 dimensions | Per-dimension confidence scoring |
| SMB Owner Discovery | Find small business owner names | 5-stage waterfall with confidence stacking |
Pattern Combinations
For comprehensive enrichment, chain patterns in sequence:
Sales Timing Optimization
- Buying Intent Detection → Is now a good time?
- CRM Validation → Is our data still accurate?
- Corporate Structure → Who actually decides?
SMB Outreach Pipeline
- Digital Maturity → Segment before enrichment (personal email = different approach)
- SMB Owner Discovery → Find the decision-maker via 5-stage waterfall
- Business Model → Understand how they make money
Tech Stack Intelligence
- Platform Detection → What do they use? (URL patterns)
- Multi-Axis Classification → Tech sophistication level
- Buying Intent → Are they likely to switch vendors?
Each pattern should be its own Claygent column in Clay. Don't combine them into one mega-prompt—that violates the 3-task rule and tanks accuracy.
Key Principles
These patterns work because they follow these principles:
- URL patterns beat text parsing — 95% accuracy vs 70%
- Navigation signals come first — Check menu before body content
- Null is a feature — Returning null when unsure beats wrong data
- Confidence by dimension — Not one overall score, but per-field
- Mismatch detection is valuable — Finding errors in existing data
- Decision trees beat "find X" — Explicit branching logic