Client Prospecting — Systematic Lead Identification and Qualification

TL;DR: Define the ICP, identify lead sources, score by fit, and deliver a prioritized list of qualified prospects with an approach brief for each.

Principio Rector: A short list of right-fit targets beats a long list of wrong ones. Quality over quantity, always.

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When to Activate

Activate when:

• User says "find prospects", "prospecting", "lead list", "ICP definition"
• User says "target accounts", "who should I contact", "who are my best customers"
• User is entering a new market and needs to identify early targets [INFERRED]
• User has a product/service and needs to build a pipeline from scratch [EXPLICIT]
• User wants to define or refine their Ideal Customer Profile [EXPLICIT]

Do NOT activate when:

• User has a named target and needs a deep profile (use client-dossier skill)
• User wants to write outreach messages (use b2b-outreach skill)
• User needs market size data (use market-intelligence skill)
• User's list is already built and needs only scoring (apply S3 only)

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S1 — ICP Definition Workshop

The Ideal Customer Profile is the foundation. A weak ICP produces a weak list. [EXPLICIT]

1a. Firmographic Dimensions

Define the organizational characteristics of your best-fit customer: [EXPLICIT]

Dimension	Questions	Example Answer
Industry	Which verticals do you serve best?	Fintech, SaaS, logistics
Company size	Headcount range?	50-500 employees
Revenue range	ARR or annual revenue?	$5M-$50M
Geography	Where do they operate?	LatAm, US Hispanic market
Business model	B2B, B2C, B2B2C?	B2B SaaS
Growth stage	Pre-seed to Series C? Bootstrapped?	Series A-B
Ownership	VC-backed, PE, public, family?	VC-backed preferred

1b. Technographic Dimensions

Define the technology signals that indicate fit: [INFERRED]

• Stack compatibility: Do they use tech you integrate with?
• Maturity level: Are they using spreadsheets (early buyer) or mature tooling (late buyer)?
• Cloud provider: AWS / GCP / Azure — matters for infrastructure products
• Key platforms: Salesforce users, HubSpot users, SAP users — defines ecosystem fit
• Budget signals: BuiltWith premium tools = company willing to pay for solutions

1c. Behavioral / Intent Signals

Real-time signals that indicate a company is likely in-market: [INFERRED]

Signal	Meaning	Source
Job postings for your use case	Budget allocated, pain active	LinkedIn, Indeed
Recent funding (Series A/B)	Budget available, growth phase	Crunchbase, TechCrunch
New executive hire in relevant function	New agenda, vendor re-evaluation	LinkedIn
Conference attendance in your space	Actively exploring solutions	Event websites
Competitor customer (churned or public)	Aware of the category, in evaluation mode	G2, Capterra
Content engagement with your topic	Top-of-funnel interest signal	LinkedIn, Google

1d. Negative ICP (Disqualifiers)

Define who NOT to pursue. This is as important as the positive ICP: [EXPLICIT]

• Companies smaller than [X] employees (too small to afford / get ROI)
• Industries with regulatory barriers to your solution
• Companies using [competitor/incompatible stack] with long contracts
• Geographies where you have no legal entity or support capacity
• Startups pre-revenue (no budget, wrong stage)

1e. ICP Summary Template

ICP Name:          [Descriptive name, e.g., "Series A Fintech in LatAm"]
Industry:          [Sector(s)]
Headcount:         [Range] employees
Revenue:           [Range] ARR/annual
Geography:         [Country/region]
Growth stage:      [Seed / A / B / Enterprise / etc.]
Tech stack signal: [Must-have indicator]
Behavioral signal: [Top 1-2 intent signals to prioritize]
Negative filter:   [Disqualifier(s)]
Estimated TAM:     [Number of companies fitting this profile] [INFERRED]

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S2 — Lead Source Strategy

Identify where to find prospects matching the ICP. [EXPLICIT]

2a. Digital Signal Sources

Source	What to Find	How
LinkedIn Sales Navigator	Title + industry + headcount + geography	Boolean search, saved searches
LinkedIn Company Search	Headcount filters, industry, recent activity	Free tier (limited)
Crunchbase / CB Insights	Funding rounds, investor portfolio, industry	Filter by stage + sector + geography
AngelList / Wellfound	Startups, tech-first companies, founding team	Category + funding filter
G2 / Capterra	Companies using competitor tools	Category page, review filters
BuiltWith / Wappalyzer	Companies using specific tech stack	Technology adoption lists
Apollo.io	Email + firmographic data	ICP filter + export

2b. Trigger Event Feeds

Monitor for in-market signals continuously: [INFERRED]

Feed	Trigger Type	Cadence
TechCrunch / VentureBeat	Funding announcements	Daily
LinkedIn notifications	Job postings in your pain category	Weekly
Google Alerts "[competitor] review"	Competitor dissatisfaction signals	Daily
Industry association member lists	Verified sector companies	Monthly
Conference attendee lists	Self-selected in-market buyers	Per event
Press release monitoring	Product launches, expansions	Weekly

2c. Network-Based Sources

Source	How to Activate
Customer referrals	Ask top 3 customers: "Who else in your network has this problem?"
Partner co-prospecting	Joint prospecting with complementary vendors
Alumni networks	LinkedIn alumni filter — ex-colleagues who moved to ICP companies
Investor portfolio	Ask VC connections for warm intros to their portcos
Trade association directories	Member company lists (often public)

2d. Geographic Focus — LatAm Context

For prospects in Latin America, specific sources: [EXPLICIT]

• Colombia: Cámara de Comercio de Bogotá business registry, Colombia Startup directory
• Mexico: Secretaría de Economía, Mexico Startup Ecosystem report
• Brazil: Crunchbase BR, ABStartups, Distrito database
• Latam regional: LAVCA (Latin American Venture Capital Association) portfolio
• Miami corridor: Brickell tech scene, Endeavor Miami, eMerge Americas network

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S3 — Scoring Model

Apply a consistent scoring framework to prioritize the list. [EXPLICIT]

BANT + Fit Composite Score

Score each prospect on two dimensions: BANT qualification and ICP fit.

BANT Score (0-40 points):

Dimension	0 pts	5 pts	10 pts
Budget	No signal	Indirect signal (funding, team size)	Direct signal (published spend, purchase intent)
Authority	Unknown	Influencer identified	Decision maker identified
Need	No signal	Inferred pain	Explicit pain confirmed
Timing	No signal	6-12 months window	Active evaluation or urgent trigger

ICP Fit Score (0-60 points):

Dimension	Weight	Scoring
Industry match	15 pts	Exact match=15, adjacent=8, tangential=3
Size match	15 pts	Exact range=15, within 2x=8, edge case=3
Tech stack signal	10 pts	Strong signal=10, moderate=5, none=0
Geography match	10 pts	Primary market=10, secondary=5, out of scope=0
Behavioral signal	10 pts	Active trigger=10, passive signal=5, none=0

Total Score Interpretation:

Score	Priority Tier	Action
80-100	Tier 1 — Hot	Full dossier + personalized sequence this week
60-79	Tier 2 — Warm	Semi-personalized outreach + monitoring
40-59	Tier 3 — Cool	Template outreach + trigger alert setup
Below 40	Disqualified	Remove from active list; archive for 6 months

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S4 — Prioritization Matrix

Map prospects on two axes to visualize prioritization. [INFERRED]

                HIGH FIT
                    |
     High Fit,      |     High Fit,
     Low Urgency    |     High Urgency
     (Nurture)      |     (Close Now)
                    |
LOW URGENCY --------+-------- HIGH URGENCY
                    |
     Low Fit,       |     Low Fit,
     Low Urgency    |     High Urgency
     (Archive)      |     (Evaluate fit)
                    |
                LOW FIT

Urgency Indicators (moves right on the matrix):

• Active hiring for your use-case role [EXPLICIT]
• Recent funding round (< 90 days) [EXPLICIT]
• Competitor churn signal [INFERRED]
• Exec change in buying function [EXPLICIT]
• End of fiscal year approaching [INFERRED]

Priority Rules:

1. Work top-right (high fit + high urgency) first — highest conversion probability [INFERRED]
2. Invest in top-left (high fit + low urgency) for pipeline building — these become top-right [INFERRED]
3. Evaluate bottom-right (low fit + high urgency) only if capacity allows — often a poor use of time [INFERRED]
4. Never work bottom-left — archive immediately [EXPLICIT]

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S5 — Output — Qualified List + Approach Brief

5a. Qualified Lead List Format

Deliver a structured table (or CSV) with scored, ranked prospects: [EXPLICIT]

| # | Company | Industry | Size | HQ | BANT | Fit | Total | Tier | Trigger Event | Best Contact | Channel | Priority |
|---|---------|---------|------|-----|------|-----|-------|------|--------------|-------------|---------|---------|
| 1 | Acme Corp | Fintech | 200 | Bogotá | 32 | 55 | 87 | T1 | Series B (Jan) | VP Eng | LinkedIn | This week |
| 2 | Beta SaaS | Logistics | 85 | CDMX | 25 | 48 | 73 | T2 | New CTO (Feb) | CEO | Email | Next sprint |

5b. Approach Brief (per Tier 1 prospect)

For every Tier 1 prospect, produce a one-paragraph approach brief: [EXPLICIT]

Company: [Name]
Score: [Total] (Tier 1)
Why now: [Trigger event — specific, dated]
Entry angle: [Personalized hook based on the trigger]
Best contact: [Name + Title + LinkedIn]
Recommended channel: [LinkedIn / Email / Warm intro via X]
Validation question: [What to ask in the first call to confirm the hypothesis]

5c. CSV Export Template

Rank,Company,Website,Industry,Headcount,HQ,BANT,Fit,Total,Tier,Trigger,Contact Name,Contact Title,LinkedIn,Email Pattern,Channel,Approach Angle,Notes
1,Acme Corp,acme.com,Fintech,200,Bogotá,32,55,87,T1,Series B Jan 2024,Maria G.,VP Eng,linkedin.com/in/...,m.garcia@acme.com [est.],LinkedIn,Series B scale angle,Warm intro via JM

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Trade-off Matrix

Decision	Approach A	Approach B	Recommendation
List size	10 accounts (deep)	100+ accounts (broad)	10-25 Tier 1 accounts per quarter for quality motions
Manual vs. automated	Hand-researched	Apollo/LinkedIn export	Hybrid: automated for discovery, manual for Tier 1 scoring
Speed vs. accuracy	Fast list, low confidence	Slow list, high confidence	Prefer accuracy — a wrong list wastes more time than building the right one
ICP breadth	Narrow ICP (1 segment)	Wide ICP (3 segments)	Start narrow, expand after first 3 customers confirm the ICP
Geographic focus	Single market	Multi-market	Single market until first $100K ARR; expand after proof of concept

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Assumptions & Limits

• Data sourced from public sources (LinkedIn, Crunchbase, press) unless user has Apollo/SalesNav [EXPLICIT]
• Headcount and revenue estimates for private companies are approximate [EXPLICIT]
• Behavioral signals (job postings) reflect stated investment, not confirmed budget [INFERRED]
• BANT scoring on early-stage prospects is inherently speculative — validate in discovery calls [EXPLICIT]
• List is a starting point — user must verify before outreach [EXPLICIT]
• Geographic data quality varies; LatAm-specific sources listed in S2d may require registration [INFERRED]

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Edge Cases

Scenario	Handling
User has no ICP yet	Run S1 ICP Workshop fully before any list building; list without ICP = wasted effort
Very niche market with < 50 total companies	Build full universe list; focus on completeness over scoring
User wants to prospect internationally without local knowledge	Flag knowledge gaps per market; use S2d for LatAm-specific sources
User's product has multiple ICPs	Build separate scored lists per ICP; do not mix in one list
User has existing customers to exclude	Add "exclude" column to CSV; cross-reference against CRM export

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Good vs Bad Example

BAD list entry:

"Company: Startup X. They might be a good fit for our product."

GOOD list entry:

"Company: Fintech Y (Series A, $8M, March 2024 [EXPLICIT], Bogotá, 45 employees [INFERRED via LinkedIn]). ICP fit: 82/100. Trigger: Hired VP Engineering from Nubank 6 weeks ago [EXPLICIT]. Pain hypothesis: scaling data infrastructure from startup to Series A [INFERRED — confirmed by 4 open data roles on LinkedIn]. Best contact: Diego Torres, VP Eng (joined 6 weeks ago, previously built data platform at Nubank). Channel: LinkedIn — connection request via JM Labs network. Approach angle: 'Saw you came from Nubank — you know what good data infra looks like at scale. Most Series A teams hit the wall at 50% of what Nubank needs. We help bridge that.'"

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Validation Gate

• ICP defined with all firmographic + technographic + behavioral dimensions
• Negative ICP (disqualifiers) explicitly listed
• At least 3 lead sources identified and searched
• BANT score calculated for each prospect (0-40)
• ICP Fit score calculated for each prospect (0-60)
• Total scores used to assign tiers (T1/T2/T3/Disqualified)
• Prioritization matrix applied — Tier 1 confirmed as high-fit AND high-urgency
• Approach brief produced for every Tier 1 prospect
• CSV output includes all required columns
• Trigger event documented (with date) for every Tier 1 prospect

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Reference Files

• knowledge/body-of-knowledge.md — Sales prospecting methodology foundations
• knowledge/knowledge-graph.md — ICP and market entity relationships
• evals/ — Scored prospect list examples for calibration

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Related Skills

• market-intelligence — Sector/territory context to inform ICP definition
• client-dossier — Deep-dive on each Tier 1 prospect from this list
• b2b-outreach — Convert the qualified list into outreach sequences
• competitive-positioning — Refine ICP by understanding competitor customer profiles