### Job Change Signal Tracking Setup (YAML)

Source: https://context7.com/sachacoldiq/coldiq-s-gtm-skills/llms.txt

Configuration for tracking job changes to identify high-intent prospects. It defines timing frameworks and outreach strategies based on the duration since a job change, aiming for a peak engagement window.

```yaml
# Clay Setup - Method 1: Monitor Existing Table
# 1. Go to Actions > Monitor for Job Changes
# 2. Specify the LinkedIn URL column
# 3. Save and run — new row created for each detected change

# Clay Setup - Method 2: Create New Tracking Table
# 1. +Create New > Table > Track Job Changes
# 2. Include "Person LinkedIn URL" for future monitoring
# 3. Include "Company LinkedIn URL" for historical detection

# Timing Framework
timing:
  days_0_13:
    multiplier: "Too early"
    action: "Monitor only — they are still settling in"
  days_14_45:
    multiplier: "1.5x (Peak)"
    action: "Immediate outreach — vendor amnesty window"
  days_46_90:
    multiplier: "1.0x (Good)"
    action: "Standard outreach — still building stack"
  days_90_plus:
    multiplier: "0.7x (Declining)"
    action: "Lower priority — stack likely set"

# Outreach Template
---
Hey congrats on the new role at {{company}}.

As you are taking over {{department}}, curious how you are
currently handling {{relevant_problem}}?

We helped {{similar_company}} with exactly that.
---
```

--------------------------------

### Email Waterfall Enrichment Setup in Clay

Source: https://context7.com/sachacoldiq/coldiq-s-gtm-skills/llms.txt

Configures an email waterfall enrichment process in Clay to increase email coverage from approximately 40% to over 85%. It involves ordering providers by cost, mapping inputs, enabling validation, and using conditional run formulas to optimize credit usage and minimize bounce rates. This setup is crucial for maximizing contactability in outreach campaigns.

```javascript
// Recommended Provider Order (Cheapest First)
// 1. LeadMagic (2 credits)
// 2. Prospeo (2 credits)
// 3. Hunter (2 credits)
// 4. Apollo (3 credits)
// 5. RocketReach (3 credits)
// 6. FindyMail (2 credits)

// Setup Steps:
// 1. Add enrichment → "Work Email" → select waterfall
// 2. Reorder providers (cheapest first)
// 3. Map inputs: domain, LinkedIn URL, full name
// 4. Enable ZeroBounce validation
// 5. Add conditional run formula
// 6. Test on 50 rows first

// Mandatory Conditional Run Formula
// (Prevents wasting credits on rows with emails)
/email is empty

// For re-enrichment workflows
/email is empty OR /email_validation equals "invalid"

// 5-Provider Email Waterfall Formula (Pick First Non-Empty)
{{Prospeo - Work Email}} || {{LeadMagic - Work Email}} || {{Wiza - Work Email}} || {{Hunter - Work Email}} || {{FullEnrich - Work Email}} || ""

// Expected Results:
// - Single provider: ~40% coverage
// - 4-provider waterfall: 70-80% coverage
// - 6-provider waterfall: 85%+ coverage
// - Target bounce rate: <2%
```

--------------------------------

### AI Column Prompt Templates

Source: https://github.com/sachacoldiq/coldiq-s-gtm-skills/blob/main/master-skills/clay/resources/formulas/clayscript-guide.md

Structured natural language prompts designed for AI-powered column enrichment. These templates demonstrate how to reference existing column data using the /field syntax to extract specific insights.

```text
Company Summary:
Visit /company_domain and give me an exhaustive summary of what the company does.

Fit Check:
Based on this summary: /company_summary
Is this company a [TYPE]?
Output "true" if yes, "false" if no.
Only output true or false, nothing else.

LinkedIn Post Summary:
Here is a LinkedIn post: /linkedin_post
Summarize what they're talking about in one sentence.
If it's about politics, religion, or controversial topics, output "SKIP".

Case Study Extraction:
Visit /company_domain/case-studies and find their customer case studies.
For each case study, extract:
- Customer name
- What they helped them achieve
- Any metrics mentioned

If no case studies found, output "purple".
```

--------------------------------

### Conditional Logic Formulas in Clayscript

Source: https://github.com/sachacoldiq/coldiq-s-gtm-skills/blob/main/master-skills/clay/resources/formulas/clayscript-guide.md

Examples of conditional expressions used to filter or validate data within Clay columns. These formulas utilize standard comparison operators to evaluate row-level data.

```javascript
// Email exists
/email is not empty

// Email valid or valid catchall
/validation_result equals "valid" OR equals "catchall valid"

// Company type match
/company_type equals "B2B"

// Minimum score
/lead_score is greater than 50

// Combined conditions
/email is not empty AND /company_fit equals "true"

// Check column completion status
Clay.getCellStatus(#{{field_id}}) == "completed" AND {{previous_column}} == ""
```

--------------------------------

### Cold Email Writing Frameworks and Structure

Source: https://context7.com/sachacoldiq/coldiq-s-gtm-skills/llms.txt

Provides a guide for writing high-performing cold emails, focusing on brevity (60-90 words), plain text, and a single Call to Action (CTA). It details eight effective frameworks and a structure checklist, emphasizing leading with pain points over features and using specific social proof to maximize engagement and response rates.

```markdown
# 8 Allowed Frameworks
1. Before/After — Show current state vs. desired state
2. Pattern Interrupt — Break expectations to earn attention
3. Ask Before Pitch — Open-ended question before selling
4. Upfront Value — Give something useful before asking
5. Do the Math — Trigger + pitch + calculation + CTA
6. Challenge of Similar Companies — "Companies doing X often struggle with Z"
7. Neutral Insight — Share third-party resource, build trust
8. Typical Problems by Role — Role-specific pain prompting reflection

# Structure Checklist
Opening (trigger) + Assumption + Social proof with numbers + Open-ended question
- 60-90 words max
- No bullets in cold emails
- One soft CTA ("Worth a quick look?" not "Book a 30-min demo")
- Specific social proof ("47% increase" not "significant improvement")
- Plain text only

# Example: Do the Math Framework
Subject: 12 open roles

{{firstName}}, quick math:

{{company}} has 12 engineering roles open averaging 45 days to fill.

At $500/day in lost productivity, that's $270K sitting on the table.

We helped {{similar_company}} cut time-to-fill by 38%.

Want to see the breakdown?

# Example: Ask Before Pitch Framework
Subject: marketing data

{{firstName}}, curious --

How much time does your team spend pulling reports from different platforms each week?

Most marketing ops leads I talk to say 6-8 hours.

We helped {{similar_company}} get that to under 1 hour.

Worth a quick look?

# Example: Challenge of Similar Companies
Subject: {{company}} security

{{firstName}},

Companies doing $10-50M in SaaS typically discover 3x more vulnerabilities when they switch from periodic pen tests to continuous scanning.

{{similar_company}} found 47 critical issues in their first week.

Open to seeing how that compares to your setup?
```