Campaign Strategy

Campaign Strategy Skill

Transform client research into an actionable email strategy for a single segment. Output email sequence blueprints and AI personalization variables for the Email Copywriting skill to execute.

Output Contract

strategy.md is not machine-parsed - it's read by downstream skills (email-copywriting, prompt-writer) for context. Hard rules this skill must honor anyway, since its output flows into files that other tools read:

• AI variable names must be Title Case with spaces: Subject Line, First Line, PS Line. They become [Title Case] brackets in emails.md and H3 headings in prompts.md - the three have to agree exactly.
• AI variable names ≤30 chars (enforced in prompts.md by the prompt-writer contract).
• Never reference data sources personalization tools typically lack (news, funding, events, social media, blogs) - these propagate into prompts.md and break at runtime when the data is not available.

Required Context

Before creating a strategy, always load the client context:

1. Read {workspace}/research.md - Client research: overview, ICP, value prop, case studies, lead magnets
2. Read {workspace}/notes.md (if it exists) - Client-specific preferences
3. Read plan.md from parent directory - Get segment definition, angle, ICP, and testing hypothesis

Directory Structure Reference ({workspace} = the client campaign workspace, default ./cold-email/{slug}/):

{workspace}/
├── research.md       # Client research - ICP, value prop, case studies
├── notes.md          # Optional client preferences and feedback
└── {plan_folder}/    # One per campaign, e.g. "03-15 - plan 1"
    ├── plan.md           # Plan with ICP, segments, angles, testing hypothesis
    ├── 1 - {segment}/
    │   └── strategy.md   # THIS file - segment strategy
    ├── 2 - {segment}/
    │   └── strategy.md
    └── ...

Required Inputs

After loading context, gather:

1. Segment folder path - e.g., {workspace}/03-15 - plan 1/1 - early-stage/
2. Plan.md - Read from parent directory of segment folder to get:
   • Broad ICP definition
   • Segment-specific criteria
   • Messaging angle for this segment
   • Testing hypothesis (if any)
3. Client Research Document - Check {workspace}/research.md or uploads
4. Campaign Goal - What action to drive:
   • Book demos/meetings
   • Drive traffic to landing page
   • Get replies for qualification
   • Promote lead magnet

Output Format

Generate a single Markdown document saved to {segment_folder}/strategy.md:

# {Client} - {Segment Name} Strategy

## Segment Overview
- **ICP**: {Broad ICP from plan.md}
- **Segment**: {Specific segment criteria from plan.md}
- **Angle**: {Messaging angle from plan.md}
- **Goal**: reply-based / click-based
- **Funnel Type**: {type}

## Email Sequence

[Markdown format - see references/email-sequence-guide.md]

## AI Personalization Variables

[JSON array - see references/ai-variables-guide.md]

## AI Rewriting (Optional)

Enable: [yes/no]
Tone: [description]

## Sequence Tests (Optional)

[Only when supporting macro test from plan.md Testing Hypothesis]

AI Rewriting Guidelines

Include the AI Rewriting section when:

• Campaign uses AI personalization (first lines, PS lines, body variables)
• Higher quality/variation is desired for personalization outputs
• Budget allows ($5 per 1,000 contacts for rewriting flow)

Skip AI Rewriting when:

• No AI personalization variables exist
• Subject lines only (rewriting too risky for subjects)
• Budget constraints require minimizing AI costs

When enabled, prompt-writer will add a rewriting prompt at the end of prompts.md.

Core Principles

1. Building block approach - Treat copy and campaigns as modular building blocks (like Legos) that can be tested in many combinations. Volume of combinations is how we discover what works. See references/building-blocks.md for the full philosophy.

2. Start strong, diversify, close strong - Lead email uses strongest angle. Middle emails try new angles. Final email is a breakup with second-strongest angle.

3. Relevance over personalization - Don't just use {firstName}. Show deep understanding of their world using AI variables sourced from LinkedIn/website.

4. One idea per email - Each email has one goal, one CTA, one main point.

5. Value-first - Every touch provides insight, education, or genuine help.

6. Data constraints - AI variables can ONLY use: company website main page, LinkedIn company page, LinkedIn individual profile. No news, events, funding announcements, or timely triggers.

Sequence Structure

• 3-5 emails maximum
• Delays: 0 days for first, 2-4 days between follow-ups
• CTAs: Reply-based for meetings, click-based for lead magnets. Every email's CTA asks for the actual offer, including Email 1 (which leads with the strongest version of that ask). No soft diagnostic questions as CTAs. Never send naked booking links - ask a direct question first.
• Length: keep static bodies punchy - at or under ~80 words (follow-ups well under). email-review enforces a hard ceiling.
• Format: AI variables use {{Title Case}}; every email signs with {sender_signature}.

Workflow

1. Receive segment folder path
2. Read plan.md from parent directory to get ICP, segment definition, and angle
3. Load client research from {workspace}/research.md
4. Read references:
   • references/building-blocks.md - Campaign testing philosophy
   • references/email-sequence-guide.md - Sequence planning details
   • references/ai-variables-guide.md - Personalization patterns
   • references/sequence-tests-guide.md - Email sequence A/B testing
5. Check for test opportunities (optional):
   • Read plan.md Testing Hypothesis section
   • Evaluate if sequence tests would SUPPORT (not conflict with) macro test
   • Only propose tests that refine HOW, not change WHAT (ICP/angle/offer)
   • Skip tests if first campaign for client, low TAM, or no clear hypothesis
6. Generate strategy document with email sequence (Markdown) and AI variables (JSON)
7. Save to {segment_folder}/strategy.md

Alignment Checklist

Before finalizing, verify:

• Value props from client research are woven through sequence
• Segment-specific pain points inform email hooks
• Angle from plan.md is reflected in the messaging
• Funnel type matches campaign goal
• Lead magnets integrated at appropriate point
• AI variables feasible with available data sources
• Each email has distinct purpose in sequence progression

Edit Mode (Improvement Context)

When invoked with improvement context (mode: "edit"), this skill edits/rewrites portions of strategy.md while preserving what works.

Detecting Edit Mode

Check for improvement context in the conversation:

• mode: "edit" indicates edit mode
• trigger: "analytics" or trigger: "feedback" indicates source
• improvement_instruction contains specific changes to make

Edit Mode Workflow

1. Read improvement context: Extract improvement_instruction object
2. Load existing strategy.md: Parse current strategy from segment folder
3. Identify preservation zones: What should NOT change (see below)
4. Identify change zones: What specifically to modify
5. Apply scoped changes: Only modify specified sections
6. Generate diff: Show before/after for changed sections
7. Get approval: Wait for user to confirm changes
8. Save: Update strategy.md with approved changes
9. Cascade check: Notify if changes affect downstream files (emails.md, prompts.md)
10. Log: Update improvement-log.md in plan folder

Handling Edit Scopes

Preservation Rules

When editing strategy.md:

Always preserve (unless explicitly changing):

• ICP and segment definition (unless pivoting)
• Available data sources and constraints
• Funnel type (reply-based vs click-based)
• Core value proposition from client research

Consider preserving:

• Email sequence structure if only changing copy angle
• AI variable names if prompts are working

Safe to change:

• Email descriptions and goals
• AI variable definitions
• Messaging angle and hooks
• Offer/CTA specifics

Edit Mode Output Format

## Proposed Changes to strategy.md

### Email Sequence Section

**Before:**
Email 3:
- primary_goal: Re-engage with social proof
- description: Share a case study relevant to their industry
- delay_in_days: 3

**After:**
Email 3:
- primary_goal: Re-engage with curiosity hook
- description: Ask a thought-provoking question about their growth strategy, no case study yet
- delay_in_days: 3

**Rationale:** Email 3 has 15% lower opens - case study subject lines may feel too salesy

### Cascade Impact
- emails.md: Email 3 will need rewriting (invoke email-copywriting after approval)
- prompts.md: No changes needed (same AI variables)

---

Approve these changes? [Yes/No/Modify]

Analytics-Informed Editing

When analytics_context is provided:

• Use sequence_stats to identify which emails need strategic changes
• Reference weak_spots for specific improvement areas
• Consider sibling_comparison to learn from winning campaigns

Common patterns:

• Low Email 1 opens = Strengthen opening hook strategy
• Drop-off after Email 2 = Email 3 strategy needs pivot
• Low replies across all = CTA or offer strategy issue

Feedback-Informed Editing

When feedback_context is provided:

• "Wrong angle" = Pivot messaging strategy
• "Offer not resonating" = Update lead magnet/CTA strategy
• "ICP mismatch" = Update segment overview section
• "Emails too long" = Adjust email descriptions

Cascade Notifications

After editing strategy.md, check if changes affect downstream files:

Notify user: "Strategy updated. These downstream files may need regeneration: [list]"

Edit Mode Checklist

Before saving edits, verify:

• Only specified sections were modified
• Preservation zones respected
• Changes align with client research
• Cascade impacts identified
• Diff shown and approved by user

Sequence Test Guidelines

Define micro-level email sequence tests that complement (not duplicate) macro-level tests from campaign-planning.

Two A/B levels - don't confuse them. This skill defines email-step A/B (### Variant A/B inside one step - subject, hook, CTA). Testing whole sequences against each other is a different thing: a segment-level sequence A/B test, set up in campaign-planning as percentage mode (random %-distribution arms, each arm a totally different sequence). If the plan is in percentage mode, each arm is its own segment folder and you write its full sequence normally - the "test" is the arm itself, so you usually skip within-step variants in that arm.

What campaign-planning handles (DON'T duplicate):

• ICP testing (different personas/industries)
• Messaging Angle testing (different hooks/pain points)
• Lead Magnet testing (different offers)
• Whole-sequence testing (percentage mode - each arm a different full sequence)

What sequence tests handle:

• Email execution tests within a SINGLE segment/arm
• Tests defined here, implemented in emails.md by email-copywriting skill
• Variants appear in same emails.md file (Variant A / Variant B)

Testable Variables

Only email sequence tests (no prompt tests):

When to Propose Tests

• Plan has clear macro hypothesis to support (sequence test refines delivery)
• Campaign targets 5,000+ prospects (enough volume to split 50/50)
• Two reasonable approaches exist for an element
• Client expressed preference worth validating
• Historical data suggests optimization opportunity

When to Skip Tests

• Macro test is already complex (don't add noise)
• Limited TAM (<2,000 contacts - not enough volume)
• First campaign for client (establish baseline first)
• No clear hypothesis (testing for testing's sake)
• Tests would conflict with plan's macro test variable

Test Design Rules

1. Maximum 1 test per strategy (keep it simple)
2. Must reference plan.md's test variable (show how it supports the macro test)
3. Hold constant: ICP, messaging angle, offer, AI variables
4. Vary only: Delivery elements (subject format, PS line, body length, CTA phrasing, timing)
5. Clear hypothesis: State expected outcome and why
6. Measurable: Define primary metric (open rate / reply rate / click rate)

Sequence Tests Output Format

When including a sequence test, add this section to strategy.md:

## Sequence Tests

### Test Context
**Plan Test Variable**: [From plan.md - what macro test is running]
**Supporting Hypothesis**: [How this micro-test supports the macro test]

### Active Test

**Test Name**: [e.g., PS Line Inclusion Test]
**Variable**: [What's being tested]
- **Variant A (Control)**: [Default approach - describe]
- **Variant B (Test)**: [Alternative approach - describe]
- **Hypothesis**: [Why we think B might outperform A]
- **Primary Metric**: [Open rate / Reply rate / Click rate]
- **Affected Emails**: [Which emails have variants - e.g., "Email 1 only", "All emails", "Emails 2-3"]

**Implementation for email-copywriting:**
[Clear instructions on how to create variants in emails.md]

Example: PS Line Inclusion Test

## Sequence Tests

### Test Context
**Plan Test Variable**: Messaging Angle (guarantee vs ROI)
**Supporting Hypothesis**: The guarantee angle may perform differently with/without personal PS lines - testing whether personalization adds or detracts from the focused offer message.

### Active Test

**Test Name**: PS Line Inclusion Test
**Variable**: PS Line
- **Variant A (Control)**: Include AI-personalized PS line after signature
- **Variant B (Test)**: No PS line - end email at CTA
- **Hypothesis**: The guarantee message is already strong; PS line may dilute focus or add unnecessary length
- **Primary Metric**: Reply rate
- **Affected Emails**: Email 1 and Email 4 (the emails that currently use {{PS Line}})

**Implementation for email-copywriting:**
- Email 1: Write two versions - one with {{PS Line}} placeholder, one without
- Email 4: Write two versions - one with {{PS Line Final}} placeholder, one without
- Emails 2-3: No variants needed (they don't have PS lines)

Alignment with Campaign Planning

Before defining a sequence test, verify it SUPPORTS (not conflicts with) the macro test:

Rule: If plan.md is testing ICP, skip sequence tests entirely to get clean ICP comparison.