sales-narrative

name	sales-narrative
description	Generate persona-specific sales narratives using Peter Kazanjy's founding sales methodology. Creates problem-solution-specifics narratives for economic buyers, technical buyers, and end users based on discovery data.
allowed-tools	Read,Write,Bash
version	2.0.0

Sales Narrative Generator (Kazanjy Methodology)

You generate persona-specific sales narratives from discovery interviews using Peter Kazanjy's founding sales approach.

Methodology

Read: {baseDir}/references/kazanjy_methodology.md for full framework

Key principles:

• Hypothesis-driven: Every deal tests ICP/pain/value assumptions
• Discovery-based: Generate from actual prospect data, not templates
• Persona-specific: Economic ≠ Technical ≠ End User narratives
• Objection pre-emption: Address blockers before they arise

Process

Step 1: Validate Discovery Completeness

Run validation script:

python {baseDir}/scripts/validate_discovery.py S001

If valid: false, stop and inform user which discovery files are missing.

Step 2: Check Staleness (if narrative exists)

python {baseDir}/scripts/detect_staleness.py S001 economic-buyer

If is_stale: false, inform user narrative is current.

Step 3: Extract Discovery Data

python {baseDir}/scripts/extract_discovery.py S001

This gives you structured JSON with:

• Problem interview insights
• Solution interview insights
• Stakeholder/persona mapping

Step 4: Read Canvas Positioning

Read these files to understand current strategic positioning:

• strategy/canvas/problem.md - Validated pain hypothesis
• strategy/canvas/solution.md - How we solve it
• strategy/canvas/unique-value.md - Differentiation
• strategy/canvas/metrics.md - Proof points

Step 5: Read Persona Patterns

Read: {baseDir}/references/persona_patterns.md

This shows you example narratives for each persona type:

• Economic buyer (CFO, VP): ROI focus
• Technical buyer (CTO, Eng): Implementation focus
• End user (Designer): Daily workflow focus

Step 6: Generate Narrative

You generate the narrative using:

• Discovery data (Step 3)
• Canvas positioning (Step 4)
• Persona patterns (Step 5)
• PSS structure (Problem-Solution-Specifics)

Follow this structure:

# [Persona] Narrative: [Thread ID]
*Generated: [timestamp]*
*For: [Persona Name] - [Role]*

## Problem

[Write problem section using:]
- Specific pain points from their problem interview
- Quantified impact where they provided numbers
- Competitive/opportunity cost context
- Use their language and examples

## Solution

[Write solution section using:]
- How your product addresses their specific pain
- Canvas unique value proposition
- Why now / why us
- Risk mitigation relevant to this persona

## Specifics

[Write specifics section using:]
- Canvas metrics/proof points
- Case studies relevant to their industry
- ROI model (economic buyer) OR integration timeline (technical) OR workflow improvement (end user)
- Implementation details they care about

## Pre-Empted Objections

[Include objections from solution interview + common ones for persona:]
- **[Objection]**: [How we address it]

## Next Steps

[Recommend next action based on persona and stage]

Step 7: Write Output

Write to: artifacts/sales/{segment}/narratives/{segment}-{persona}.md

File naming convention:

• Economic buyer: {segment}-economic-buyer.md
• Technical buyer: {segment}-technical-buyer.md
• Objection library: {segment}-objection-lib.md

No metadata file needed - narratives are regenerated when Canvas/discovery changes

Step 8: Present to User

Show:

• Path to generated narrative
• Key insights you incorporated from discovery
• Which objections you pre-empted
• Recommended next action

Persona-Specific Guidance

Read detailed patterns in {baseDir}/references/persona_patterns.md

Economic Buyer

They care about: Business impact, ROI, risk, budget Problem section: Quantified cost of status quo, opportunity cost Solution section: Financial model, payback period, risk mitigation Specifics section: ROI calculation, case study outcomes, TCO comparison

Technical Buyer

They care about: Implementation, integration, maintenance, security Problem section: Technical debt, complexity, vendor concerns Solution section: Architecture fit, API simplicity, support quality Specifics section: Integration timeline, security/compliance, SLA

End User

They care about: Daily workflow, ease of use, productivity Problem section: Manual frustration, inconsistent results Solution section: Speed, accuracy, simplicity Specifics section: Time saved per task, quality improvement, training time

Error Handling

Missing discovery files:

Cannot generate narrative for S001:
- Missing: discovery/problem-interview.md

User must complete problem interview first.

Persona not in stakeholders:

Persona 'economic-buyer' not found in stakeholders.md
Available personas: technical-buyer, end-user

User should update stakeholder mapping or specify correct persona.

Examples

Read complete example narratives in {baseDir}/references/persona_patterns.md