Measure and optimize growth using the AARRR (Pirate Metrics) framework with stage-specific KPIs and funnel analysis
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Conduct deep account and contact research to personalize outreach and identify compelling angles for engagement
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실행 점수 미검증
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Systematically research target accounts and contacts to craft personalized, relevant outreach that cuts through the noise.
Based on Jeb Blount's Fanatical Prospecting and TOPO Account-Based Research, combining:
| Claude Does | You Decide |
|---|---|
| Structures research framework | Time per account |
| Identifies key data points | Outreach approach |
| Suggests personalization angles | Which angle to use |
| Creates research templates | Tool selection |
| Synthesizes findings | Message crafting |
Firmographic Data:
| Data Point | Source | Why It Matters |
|---|---|---|
| Company size | LinkedIn, website | ICP fit |
| Revenue | ZoomInfo, news | Budget potential |
| Industry | Relevance | |
| Locations | Website | Territory |
| Tech stack | BuiltWith, job posts | Integration fit |
Business Context:
| Data Point | Source | Why It Matters |
|---|---|---|
| Recent funding | Crunchbase, news | Budget, growth mode |
| Executive changes | LinkedIn, news | New priorities |
| Product launches | Press releases | Initiatives |
| Earnings/reports | SEC, investor calls | Priorities, challenges |
| Partnerships | News | Ecosystem |
Professional Profile:
| Data Point | Source | Why It Matters |
|---|---|---|
| Current role | Relevance | |
| Tenure | Influence level | |
| Career path | Context | |
| Content shared | LinkedIn, Twitter | Interests |
| Mutual connections | Warm intro |
Personal Connection Points:
Timing Triggers:
| Trigger | Implication |
|---|---|
| New in role | Building stack, making changes |
| New company | Bringing solutions from previous |
| Funding | Budget available |
| Hiring | Scaling, needs support |
| Bad earnings | Cost cutting or growth push |
Personalization Hierarchy:
Output:
## Account Research: DataFlow Systems
### Company Snapshot
| Attribute | Value | Source |
|-----------|-------|--------|
| Company | DataFlow Systems | |
| Industry | B2B SaaS (Analytics) | LinkedIn |
| Size | 340 employees | LinkedIn |
| Revenue | ~$50M ARR (est.) | ZoomInfo |
| Founded | 2018 | Crunchbase |
| HQ | Austin, TX | Website |
| Funding | $45M Series B (Oct 2024) | Crunchbase |
---
### Technology Stack
| Category | Tool | Source |
|----------|------|--------|
| CRM | Salesforce | BuiltWith, Jobs |
| Marketing | HubSpot | BuiltWith |
| Analytics | Mixpanel | Careers page |
| Data | Snowflake | Job posting |
| [Your Category] | None detected | Research |
**Implication:** Salesforce user = good fit for integration. No tool in our category = greenfield opportunity.
---
### Recent Triggers
| Date | Trigger | Relevance |
|------|---------|-----------|
| Oct 2024 | Series B ($45M) | Budget for tools |
| Nov 2024 | VP Sales hired | New leader = new tools |
| Dec 2024 | 12 SDR positions posted | Scaling outbound |
| Jan 2025 | G2 reviews mention "[pain]" | Known problem |
---
### Business Context
**From LinkedIn:**
- Growing 60% YoY (CEO post)
- Expanding to enterprise segment (VP Sales announcement)
- Recent product launch: AI analytics features
**From News:**
- Named to "Top 50 Startups" list
- Partnership with [Complementary Company]
- CEO spoke at [Industry Conference]
**From Job Posts:**
- Hiring: SDRs (12), AEs (5), RevOps (1)
- Reveals: Scaling sales org significantly
- Tech stack mentioned: Salesforce, Gong, Outreach (competitor!)
---
### Challenges (Inferred)
Based on triggers and context:
1. **Scaling sales team** - Need tools to support
2. **Moving upmarket** - Enterprise processes needed
3. **Rev Ops hire** - Building infrastructure
4. **Competitor in stack** - May be open to alternatives
---
### Target Contacts
| Name | Title | Priority | Angle |
|------|-------|----------|-------|
| Sarah Kim | VP Sales | Primary | New to role (90 days) |
| Mike Chen | RevOps Manager | Secondary | Posted RevOps opening |
| David Park | CEO | Executive | Series B scaling |
---
### Recommended Approach
**Primary Target: Sarah Kim, VP Sales**
- New to role = making changes
- Scaling team = needs tools
- Moving upmarket = needs process
**Angle:** "Congrats on the VP role and Series B! I noticed you're hiring 12 SDRs. Most VP Sales at your stage tell me [challenge] is their biggest issue. Curious if that's true for you?"
**Secondary Path:**
- RevOps Manager Mike Chen (operational angle)
- Mutual connection: [Name] (former colleague)
Output:
## Contact Research: Sarah Kim, VP Sales
### Profile Summary
| Attribute | Value |
|-----------|-------|
| Name | Sarah Kim |
| Title | VP of Sales |
| Company | DataFlow Systems |
| Location | Austin, TX |
| Tenure | 3 months (started Oct 2024) |
| LinkedIn | linkedin.com/in/sarahkim |
---
### Career Path
| Period | Company | Role | Relevance |
|--------|---------|------|-----------|
| 2024-Present | DataFlow | VP Sales | Target |
| 2021-2024 | ScaleUp Inc | Director Sales | Previous tools? |
| 2018-2021 | BigCorp | Sales Manager | Enterprise exp |
| 2015-2018 | StartupXYZ | AE | SMB background |
**Insight:** Rose through ranks. Enterprise + SMB experience. First VP role = motivated to succeed.
---
### Content Activity
**LinkedIn Posts (Last 90 days):**
- "Excited to join DataFlow!" (Oct)
- Shared article on "Scaling SDR teams"
- Commented on post about sales forecasting
- Posted about team offsite (Dec)
**Themes:** Sales leadership, team building, scaling
**Quote-worthy:** "The hardest part of scaling isn't hiring—it's making sure every rep can sell like your best rep."
---
### Connection Points
| Type | Detail | Approach |
|------|--------|----------|
| Mutual Connection | John Smith (2nd degree) | Ask for intro |
| Content | Scaling article | Reference in outreach |
| Alma Mater | Stanford MBA | Mention if relevant |
| Previous Company | ScaleUp used our competitor | Migration angle |
---
### Professional Interests
Based on activity:
- Sales enablement
- Team scaling
- Forecasting accuracy
- Rep productivity
---
### Personalization Angles
**Angle 1: New VP + Scaling** (Strongest)
Hi Sarah,
Congrats on the VP role at DataFlow—and jumping into a Series B scaling mode!
I noticed you shared that article on scaling SDR teams. The quote "making every rep sell like your best rep" really resonated.
That's exactly what [Similar Customer] focused on when they went from 5 to 50 reps.
Curious: what's your #1 challenge as you build out the team?
**Angle 2: Content-Based**
Hi Sarah,
Loved your take on the hardest part of scaling: "making every rep sell like your best rep."
I work with a lot of VP Sales going through exactly that transition. The common thread? [Insight from our customers].
Worth comparing notes?
**Angle 3: Mutual Connection**
Hi Sarah,
John Smith mentioned you just took over sales at DataFlow—congrats!
He thought we should connect given your focus on [area].
Would love to hear what's top of mind as you build out the team.
---
### Red Flags / Cautions
- Just started (Oct) - may not have full authority yet
- Previous company used competitor - could be loyal
- No public content about specific pain points
---
### Recommended Sequence
**Day 1:** Email (Angle 1 - New VP + Scaling)
**Day 1:** LinkedIn connection (mention scaling article)
**Day 3:** Follow-up email with customer story
**Day 5:** LinkedIn voice note
**Day 7:** Final email with value offer
**Expectation:** 20-30% response rate with this level of personalization
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Measure and optimize growth using the AARRR (Pirate Metrics) framework with stage-specific KPIs and funnel analysis
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Calculate A/B test statistical significance. Use when: determining if test results are significant; calculating required sample size; estimating test duration; analyzing conversion experiments; making data-driven decisions
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Assess customer account health using product usage, support sentiment, payment status, and relationship signals
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Analyze paid advertising performance across channels and recommend budget reallocation to maximize ROAS and minimize CAC. Use when: planning quarterly ad budget allocation, diagnosing underperforming ad channels, deciding whether to scale spend on a channel, calculating marginal ROI across Google Ads, Meta, LinkedIn, or TikTok, rebalancing media mix after performance shifts, or setting up a test-and-scale framework for new channels.
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Use when testing skills, commands, or agents for quality. Use after creating new skills, before deploying agents, or when debugging inconsistent agent behavior. Triggers on "evaluate", "test quality", "is this skill working", or QA of AI workflows.
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Use when analyzing server logs to understand how AI crawlers (GPTBot, ClaudeBot, PerplexityBot) interact with your site. Use when optimizing content placement for LLM retrieval, diagnosing why AI search isn't citing your content, or auditing crawl patterns to find optimization gaps.
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