Lead Hand Skill

Lead Generation Expert Knowledge

Ideal Customer Profile (ICP) Construction

A good ICP answers these questions:

1. Industry: What vertical does your ideal customer operate in?
2. Company size: How many employees? What revenue range?
3. Geography: Where are they located?
4. Technology: What tech stack do they use?
5. Budget signals: Are they funded? Growing? Hiring?
6. Decision-maker: Who has buying authority? (title, seniority)
7. Pain points: What problems does your product solve for them?

Company Size Categories

| Category | Employees | Typical Budget | Sales Cycle | |----------|-----------|---------------|-------------| | Startup | 1-50 | $1K-$25K/yr | 1-4 weeks | | SMB | 50-500 | $25K-$250K/yr | 1-3 months | | Enterprise | 500+ | $250K+/yr | 3-12 months |

ICP Refinement Loop

The ICP should not be static. After every 3 report cycles, refine it:

1. Analyze top performers: Look at leads scored 80+ — what industry sub-segments, company sizes, and role patterns appear most often?
2. Analyze low performers: Look at leads scored below 40 — which ICP criteria were they missing? Were there false positives from overly broad keywords?
3. Tighten criteria: Narrow industry keywords (e.g., "fintech" becomes "payment infrastructure fintech"), adjust company size range, add or remove geographic regions, refine role titles.
4. Track revisions: Log each ICP revision with date, changes made, and rationale. This creates an audit trail showing how targeting improved over time.
5. Measure impact: Compare average lead score before and after each ICP revision. A well-refined ICP should produce higher average scores with fewer total leads — quality over quantity.

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Web Research Techniques for Lead Discovery

Search Query Patterns

# Find companies in a vertical
"[industry] companies" site:crunchbase.com
"top [industry] startups [year]"
"[industry] companies [city/region]"

# Find decision-makers
"[title]" "[company]" site:linkedin.com
"[company] team" OR "[company] about us" OR "[company] leadership"

# Growth signals (high-intent leads)
"[company] hiring [role]" — indicates budget and growth
"[company] series [A/B/C]" — recently funded
"[company] expansion" OR "[company] new office"
"[company] product launch [year]"

# Technology signals
"[company] uses [technology]" OR "[company] built with [technology]"
site:stackshare.io "[company]"
site:builtwith.com "[company]"

Source Quality Ranking

1. Company website (About/Team pages) — most reliable for personnel
2. Crunchbase — funding, company details, leadership
3. LinkedIn (public profiles) — titles, tenure, connections
4. Press releases — announcements, partnerships, funding
5. Job boards — hiring signals, tech stack requirements
6. Industry directories — comprehensive company lists
7. News articles — recent activity, reputation
8. Social media — engagement, company culture

Industry-Specific Search Patterns

SaaS / Technology

# Company directories
site:g2.com/products "[category]"
site:capterra.com "[category] software"
site:producthunt.com "[product type]" "[year]"
"[category] software" site:crunchbase.com/organization

# Tech stack signals
site:stackshare.io "[technology]" decisions
site:builtwith.com/websites/[technology]

# Growth signals
"[company] SOC 2" OR "[company] ISO 27001"        — enterprise readiness
"[company] API" OR "[company] integration"          — platform maturity
"[company] case study" OR "[company] customer story" — traction evidence

Healthcare

# Directories & registries
site:healthcareittoday.com "[company]"
"digital health companies" site:crunchbase.com
"health tech" "[city/state]" site:angellist.co
"HIPAA compliant" "[category] software"

# Regulatory signals
"[company] FDA clearance" OR "[company] 510(k)"
"[company] HIPAA" OR "[company] HITRUST"
"[company] clinical trial" site:clinicaltrials.gov

Financial Services

# Directories & databases
site:fintechmagazine.com "top" "[category]"
"fintech companies" "[region]" site:crunchbase.com
"banking technology" OR "insurtech" site:cbinsights.com

# Compliance signals
"[company] SOX compliance" OR "[company] PCI DSS"
"[company] banking license" OR "[company] money transmitter"
"[company] Series [A/B/C]" "fintech"

E-commerce

# Directories & tools
site:apps.shopify.com "[category]"
site:store.bigcommerce.com "[category]"
"ecommerce brands" "[niche]" site:2pm.com OR site:modernretail.co

# Revenue signals
"[company] GMV" OR "[company] ARR"
"[company] warehouse" OR "[company] fulfillment center"
"[brand] DTC" OR "[brand] direct to consumer"

Manufacturing

# Directories
site:thomasnet.com "[product category]"
"manufacturing companies" "[city/state]" site:mfg.com
"industrial [category]" site:dnb.com

# Modernization signals
"[company] Industry 4.0" OR "[company] smart factory"
"[company] ERP" OR "[company] digital transformation"
"[company] ISO 9001" OR "[company] ISO 14001"

Industry Source Quick Reference

| Vertical | Primary Directories | Key Signal Keywords | |----------|-------------------|---------------------| | SaaS/Tech | G2, Capterra, ProductHunt, Crunchbase | "API launch", "SOC 2", "Series X" | | Healthcare | HealthcareIT, ClinicalTrials.gov | "HIPAA", "FDA", "clinical trial" | | Financial Services | CBInsights, Crunchbase | "PCI DSS", "banking license", "Series X" | | E-commerce | Shopify App Store, ModernRetail | "GMV", "DTC", "fulfillment" | | Manufacturing | ThomasNet, MFG.com | "Industry 4.0", "ISO 9001", "ERP" |

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Lead Enrichment Patterns

Basic Enrichment (always available)

• Full name (first + last)
• Job title
• Company name
• Company website URL

Standard Enrichment

• Company employee count (from About page, Crunchbase, or LinkedIn)
• Company industry classification
• Company founding year
• Technology stack (from job postings, StackShare, BuiltWith)
• Social profiles (LinkedIn URL, Twitter handle)
• Company description (from meta tags or About page)

Deep Enrichment

• Recent funding rounds (amount, investors, date)
• Recent news mentions (last 90 days)
• Key competitors
• Estimated revenue range
• Recent job postings (growth signals)
• Company blog/content activity (engagement level)
• Executive team changes

Enrichment Depth Escalation Strategy

Not all leads deserve the same enrichment investment. Use a two-pass approach:

1. First pass (Standard depth): Enrich all discovered leads at Standard depth. This is cost-effective and provides enough data for initial scoring.
2. Score checkpoint: After the first pass, score all leads. Any lead scoring 70+ at Standard depth is a strong candidate.
3. Second pass (Deep depth): Re-enrich only leads scoring 70+ at Deep depth. This focuses expensive research (funding history, news, competitive analysis) on leads most likely to convert.
4. Skip threshold: Leads scoring below 30 after Standard enrichment should not be enriched further — the data is unlikely to improve their score enough to matter.

This approach typically reduces total enrichment cost by 40-60% while maintaining the same output quality for top-tier leads.

Email Pattern Discovery

Common corporate email formats (try in order):

1. firstname@company.com (most common for small companies)
2. firstname.lastname@company.com (most common for larger companies)
3. first_initial+lastname@company.com (e.g., jsmith@)
4. firstname+last_initial@company.com (e.g., johns@)

Note: NEVER send unsolicited emails. Email patterns are for reference only.

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Lead Scoring Framework

Scoring Rubric (0-100)

ICP Match (30 points max):
  Industry match:     +10
  Company size match: +5
  Geography match:    +5
  Role/title match:   +10

Growth Signals (20 points max):
  Recent funding:     +8
  Actively hiring:    +6
  Product launch:     +3
  Press coverage:     +3

Enrichment Quality (20 points max):
  Email found:        +5
  LinkedIn found:     +5
  Full company data:  +5
  Tech stack known:   +5

Recency (15 points max):
  Active this month:  +15
  Active this quarter:+10
  Active this year:   +5
  No recent activity: +0

Accessibility (15 points max):
  Direct contact:     +15
  Company contact:    +10
  Social only:        +5
  No contact info:    +0

Score Interpretation

| Score | Grade | Action | |-------|-------|--------| | 80-100 | A | Hot lead — prioritize outreach | | 60-79 | B | Warm lead — nurture | | 40-59 | C | Cool lead — enrich further | | 0-39 | D | Cold lead — deprioritize |

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Lead Qualification Frameworks

BANT Framework

Use BANT to quickly qualify leads during or after enrichment. Each dimension maps to data you can discover through web research.

| Dimension | Question | Research Signals | |-----------|----------|-----------------| | Budget | Can they afford the solution? | Funding rounds, revenue estimates, job postings for related roles, pricing tier of current tools | | Authority | Is this person a decision-maker? | Title seniority (VP+, C-level, Director), reports to CEO/CTO, listed on "Leadership" page | | Need | Do they have the problem you solve? | Job postings mentioning the pain point, tech stack gaps, competitor tool usage, complaints on forums | | Timeline | Is there urgency to buy? | Contract renewals, compliance deadlines, product launches, recent leadership changes |

BANT Scoring Overlay

Apply these modifiers on top of the base lead score:

Budget confirmed (funding, revenue signal):   +5
Authority confirmed (VP+ or C-level):         +5
Need confirmed (pain point evidence):         +5
Timeline confirmed (urgency signal):          +5
                                     Max bonus: +20

MEDDIC Framework

Use MEDDIC for complex / enterprise sales qualification where longer deal cycles demand deeper research.

| Dimension | Definition | What to Look For | |-----------|-----------|-----------------| | Metrics | Quantifiable outcomes the buyer cares about | Case studies they publish, KPIs in job postings, analyst reports, earnings calls | | Economic Buyer | Person with budget authority to sign | CFO, CEO, VP Finance, or "Head of Procurement" listed on team pages | | Decision Criteria | Factors they use to evaluate vendors | RFP documents, vendor comparison blog posts, compliance requirements, review site feedback | | Decision Process | Steps from evaluation to purchase | Procurement team presence, legal/compliance review cycles, pilot program mentions | | Identify Pain | Specific problems driving the purchase | Support forums, Glassdoor reviews, social media complaints, analyst reports on industry challenges | | Champion | Internal advocate for your solution | Conference speakers, blog authors, open-source contributors, people who engage with your content |

MEDDIC Research Checklist

For each enterprise lead, attempt to discover:
[ ] At least one quantifiable metric they care about
[ ] The economic buyer's name and title
[ ] 2+ decision criteria (compliance, performance, price, integration)
[ ] Whether they run formal procurement (RFP, committee)
[ ] 1+ specific pain point with evidence
[ ] A potential internal champion (engaged user, tech advocate)

Choosing Between BANT and MEDDIC

The qualification_framework setting controls which framework is applied. When set to "auto", use this decision table:

| Scenario | Recommended Framework | |----------|----------------------| | SMB / startup targets, short sales cycle | BANT | | Enterprise targets, $100K+ deal size | MEDDIC | | Mixed list with varied company sizes | BANT first pass, MEDDIC for A-grade enterprise leads | | Time-constrained research | BANT (faster to assess) |

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Deduplication Strategies

Matching Algorithm

1. Exact match: Normalize company name (lowercase, strip Inc/LLC/Ltd) + person name
2. Fuzzy match: Levenshtein distance 90 days without activity) for review

• Provide clear data export in all supported formats

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Common Pitfalls

1. Outdated Data

Problem: Company details change fast — people change jobs, startups pivot, funding info ages. Mitigation:

• Verify every lead against at least 2 sources, and prefer sources updated within the last 90 days
• Flag any data point older than 6 months as "needs re-verification"
• Check LinkedIn tenure: if a contact joined their current role 10% headcount): -10

Lawsuit / regulatory action: -5 Executive turnover (CEO/CTO left): -5 Declining web traffic (per SimilarWeb): -3

### 8. Skipping the ICP Step
**Problem**: Jumping straight into search without a clear ICP produces scattered, low-quality results.
**Mitigation**:
- Always define the ICP **before** the first search query, even if it takes 5 extra minutes
- Write the ICP down explicitly (industry, size, geography, role, pain point, budget signal)
- Revisit and tighten the ICP after the first 10 leads if results are too broad

### Pitfall Severity Quick Reference
| Pitfall | Severity | Frequency | Fix Effort |
|---------|----------|-----------|------------|
| Outdated data | High | Very common | Medium (multi-source verification) |
| Single source reliance | High | Common | Low (add 1-2 extra sources) |
| Poor enrichment quality | Medium | Common | Medium (set thresholds, second pass) |
| Vanity list sizes | Medium | Common | Low (enforce scoring cut-off) |
| Company name variants | Medium | Very common | Low (normalize + domain match) |
| Hiring != purchase intent | Low | Occasional | Low (adjust scoring weight) |
| Ignoring negative signals | High | Common | Medium (add negative modifiers) |
| Skipping ICP | High | Occasional | Low (5-minute discipline) |

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [librefang](https://github.com/librefang)
- **Source:** [librefang/librefang-registry](https://github.com/librefang/librefang-registry)
- **License:** MIT

Install and usage instructions live in the source repository linked above.