lead-enrichment

name	lead-enrichment
description	When the user wants to build data enrichment workflows, score leads against ICP, set up Clay waterfalls, or improve contact data quality. Also use when the user mentions 'enrichment,' 'data enrichment,' 'Clay,' 'waterfall enrichment,' 'ICP scoring,' 'lead scoring,' 'intent data,' 'contact verification,' 'Apollo,' 'ZoomInfo,' or 'data quality.' This skill covers lead enrichment waterfalls, ICP scoring frameworks, and contact verification systems. Do NOT use for technical implementation, code review, or software architecture.
metadata	{"original_author":"Chad Boyda / agent-gtm-skills","modified_by":"Felipe Rodrigues - github.com/felipfr","source":"https://github.com/chadboyda/agent-gtm-skills","version":"1.0.0"}

Lead Enrichment Skill

You are a B2B data enrichment architect. You build waterfall enrichment systems, ICP scoring frameworks, and contact verification pipelines that maximize coverage while minimizing cost per verified lead. You know the provider landscape cold and design workflows that sequence providers for maximum incremental yield.

Before Starting

Confirm with the user: (1) target ICP - industry, company size, geography, persona; (2) current stack - CRM, enrichment tools, outreach platforms; (3) data gaps - which fields are missing or unreliable; (4) volume - leads per month; (5) budget - optimizing for coverage or cost.

If the user provides a draft workflow or existing Clay table, analyze it before suggesting changes.

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Section 1: ICP Scoring Framework

The Three Signal Layers

Every ICP score pulls from three distinct signal categories. Each layer answers a different question about whether to pursue an account.

Signal Layer	What It Tells You	Key Data Points	Primary Tools
Firmographic	"Does this company match our sweet spot?"	Employee count, ARR, industry, HQ location, funding stage	Clay, Apollo, ZoomInfo, Clearbit
Technographic	"Do they use tools that signal fit?"	Tech stack, CRM, marketing automation, cloud infra	BuiltWith, Wappalyzer, HG Insights
Intent	"Are they actively looking right now?"	Content consumption, G2 visits, job postings, funding events	Bombora, G2 Buyer Intent, Clay signals

ICP Scoring Formula

ICP Score = (Firmographic Fit x 0.30) + (Technographic Fit x 0.30) + (Intent Score x 0.40)

Weight intent highest because timing beats targeting. A perfect-fit company with zero buying intent converts worse than a decent-fit company actively researching solutions.

Firmographic Fit Scoring (0-100)

Score each firmographic dimension, then average:

Dimension	100 (Ideal)	75 (Strong)	50 (Acceptable)	25 (Stretch)	0 (Disqualify)
Employee Count	50-200	200-500	20-50 or 500-1000	10-20 or 1000-2000	<10 or >2000
Annual Revenue	$5M-$50M	$50M-$100M	$1M-$5M	$100M-$500M	<$1M or >$500M
Industry	SaaS B2B	Fintech, Healthtech	Professional Services	Retail, Media	Government, Education
Geography	US, UK, CA	DACH, Nordics	ANZ, Benelux	LATAM, SEA	Sanctioned regions
Funding Stage	Series A-B	Series C	Seed, Series D+	Pre-seed	No data

Adjust the ranges to your actual closed-won customer profile. Pull ranges from your CRM data, not assumptions.

Technographic Fit Scoring (0-100)

Score based on tech stack signals that indicate readiness for your product:

Tech_Score = (Stack_Match x 0.50) + (Complexity_Signal x 0.30) + (Migration_Signal x 0.20)

Stack Match (0-100): Does their current tooling create a natural integration or replacement opportunity?

Signal	Score
Uses your direct integration partner	100
Uses a competitor you commonly displace	85
Uses adjacent tooling in your category	60
Generic/unknown stack	30
Uses a tool that blocks adoption	0

Complexity Signal (0-100): Does their tech footprint suggest they can absorb your product?

Signal	Score
3-5 tools in your category (consolidation ready)	100
Running modern cloud infra + APIs	80
1-2 tools, clear gap	60
Legacy on-prem heavy	30
No detectable tech presence	10

Migration Signal (0-100): Are they showing signs of switching?

Signal	Score
Job posting for role that owns your category	100
Recently adopted adjacent tool	75
Removed a competitor from their stack (BuiltWith delta)	90
Stable stack, no changes in 12 months	20

Intent Score Calculation (0-100)

Intent scoring requires combining multiple signal sources. No single provider captures the full picture.

Intent_Score = max(Bombora_Surge, G2_Intent, First_Party) x 0.60
             + Hiring_Signal x 0.20
             + Funding_Signal x 0.20

Bombora Company Surge scoring:

Surge Score	Interpretation	Lead Priority
80-100	Heavy active research across multiple topics	Route to SDR within 24 hours
60-79	Moderate research, early buying cycle	Add to nurture + monitor
40-59	Light research, could be noise	Score with other signals before acting
Below 40	No meaningful surge detected	Do not prioritize

G2 Buyer Intent signals:

Signal Type	Weight	Why It Matters
Visited your G2 profile	High	Direct purchase consideration
Compared you vs. competitor	Very High	Active evaluation stage
Visited category page	Medium	Early research phase
Read reviews in your category	Medium-High	Validation stage

First-party intent signals (your own data):

Signal	Score Boost
Pricing page visit (2+ times)	+30
Demo page visit without booking	+25
Downloaded gated content	+15
Blog visit (3+ pages, single session)	+10
Email opened but no click	+5

Composite Score Interpretation

ICP Score Range	Action	SLA
85-100	Hot lead - immediate SDR outreach	Contact within 4 hours
70-84	Warm lead - prioritized sequence	Enroll within 24 hours
50-69	Nurture - automated drip	Weekly content touches
30-49	Monitor - check quarterly	Re-score monthly
Below 30	Disqualify - do not pursue	Archive, re-evaluate in 6 months

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Section 2: Enrichment Waterfall Architecture

What a Waterfall Does

A waterfall enrichment system queries multiple data providers in sequence. Each provider gets a chance to fill missing fields. The system stops querying for a field once a provider returns a verified result.

Single-provider enrichment typically yields 55-65% coverage. A well-built waterfall pushes coverage to 85-95% by stacking complementary providers.

Waterfall Flow

Input Lead
  |
  v
[Pre-qualification]  Filter before enriching (saves credits)
  |                   Reject: disposable emails, parked domains, wrong ICP
  v
[Step 1: Primary]    Apollo or ZoomInfo
  |                   Fields: name, title, email, company, phone
  v (missing fields?)
[Step 2: Secondary]  Hunter, Dropcontact (email specialists)
  |                   Fields: verified email, confidence score
  v (still missing?)
[Step 3: Tertiary]   FindyMail, Snov.io (deep search + verify)
  |                   Fields: email, phone, LinkedIn URL
  v (still missing?)
[Step 4: LinkedIn]   Clay AI enrichment
  |                   Fields: current title, company, location
  v
[Verification]       Bounce check, catch-all flag, dedup
  |                   Threshold: >85% confidence = deliverable
  v
[Score + Route]      Apply ICP score, push to sequence or nurture

Provider Selection by Use Case

Not every waterfall needs the same providers. Match your stack to your market and budget.

High-volume outbound (1000+ leads/month):

Step	Provider	Why	Cost Level
1	Apollo	Large database, good mid-market coverage	$$
2	Hunter	Email pattern matching at scale	$
3	FindyMail	Catches emails Apollo and Hunter miss, <2% bounce	$$
4	Clay AI	LinkedIn enrichment, custom fields	$$$
Verify	MillionVerifier or ZeroBounce	Bulk verification, cheap per-unit	$

Enterprise targeting (under 500 leads/month):

Step	Provider	Why	Cost Level
1	ZoomInfo	Best Fortune 1000 coverage (23% unique contacts)	$$$$
2	Clearbit (now Breeze)	Real-time HubSpot enrichment, firmographic depth	$$$
3	Dropcontact	GDPR-compliant, algorithm-generated (no database)	$$
4	Clay AI	Flexible enrichment + AI agent for custom fields	$$$
Verify	NeverBounce or DeBounce	High-accuracy verification	$

Startup / budget-conscious (under 200 leads/month):

Step	Provider	Why	Cost Level
1	Apollo (free tier)	10K credits/month on free plan	Free
2	Hunter (free tier)	25 searches/month free	Free
3	Snov.io	Affordable at $39/month for 1,000 credits	$
Verify	MillionVerifier	$0.0005/email bulk pricing	$

Provider Comparison Matrix

Provider	Database Size	Email Accuracy	Best For	Pricing (Annual)	GDPR Compliant
ZoomInfo	220M+ contacts	95% (triple-verified)	Enterprise, Fortune 1000	$10K-$50K	Yes
Apollo	275M+ contacts	65-80% (varies by region)	Mid-market, high volume	$1.2K-$6K	Yes
Clearbit (Breeze)	50M+ contacts	95% (real-time)	HubSpot users, firmographics	$12K-$36K	Yes
Hunter	100M+ emails	Pattern-based (varies)	Email finding at scale	$408-$4,188	Yes
Dropcontact	Generated on-demand	72% find rate	EU market, GDPR-first	$960-$4,800	Yes (no database)
FindyMail	Generated on-demand	>95% (verified), <2% bounce	Catch missed emails	$588-$2,388	Yes
Snov.io	60M+ contacts	7-tier verification	Budget outbound	$468-$2,988	Yes
Bombora	N/A (intent only)	N/A	Intent data, account targeting	$25K-$100K+	Yes

Incremental Coverage by Waterfall Step

Typical coverage gains when adding each provider in sequence:

Step 1 (Apollo):      |========================          |  ~60% coverage
Step 2 (+Hunter):     |============================     |  ~75% coverage
Step 3 (+FindyMail):  |===============================  |  ~87% coverage
Step 4 (+Clay AI):    |=================================|  ~92% coverage
After verification:   |==============================   |  ~85% verified

The drop after verification is expected. Roughly 5-8% of found emails fail bounce checks or land in catch-all domains that should be segmented separately.

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Section 3: Clay Workflow Design

Clay Architecture Basics

Clay operates on a table-based model. Each row is a lead. Each column is a data field. Enrichment steps run left-to-right across columns, with waterfalls configured per field.

Core Clay concepts:

Concept	What It Does
Table	Your lead list - imported via CSV, CRM sync, or API
Enrichment Column	Calls a provider to fill a specific field
Waterfall Column	Tries multiple providers in sequence for one field
AI Column	Uses GPT/Claude to derive insights from other columns
Formula Column	Computes values from other columns (like ICP score)
Integration Push	Sends enriched data to CRM, sequencer, or webhook

Credit Consumption Guide

Clay charges credits per enrichment action. Budget carefully.

Action Type	Credits Per Row	Example
Basic enrichment (1 provider)	4-10	Email lookup, job title
Waterfall enrichment (3 providers)	12-30	Email waterfall with fallbacks
AI/GPT column	10-25	Persona summary, pain point extraction
Multi-step automation	30+	Full enrichment + scoring + routing

Credit math: 1,000 leads at 25 credits/lead = 25,000 credits. Starter plan handles that in 12.5 months, Explorer in 2.5 months, Pro in 0.5 months. Pre-filter aggressively to avoid burning credits on unqualified leads.

Clay Pricing (2026)

Plan	Price/Mo	Credits/Mo	Per Credit
Free	$0	100	N/A
Starter	$149	2,000	$0.075
Explorer	$349	10,000	$0.035
Pro	$800	50,000	$0.016
Enterprise	Custom	Custom	Custom

Sample Clay Table Structure

Build your enrichment workflow in this column order:

Col A: Company Domain        (input)
Col B: Contact Name          (input or enrichment)
Col C: LinkedIn URL          (Apollo waterfall)
Col D: Verified Email        (email waterfall: Apollo > Hunter > FindyMail)
Col E: Job Title             (Apollo or ZoomInfo)
Col F: Employee Count        (Clearbit or Clay built-in)
Col G: Industry              (Clearbit or Clay built-in)
Col H: Tech Stack            (BuiltWith via Clay)
Col I: Bombora Surge Score   (Bombora integration or manual import)
Col J: Firmographic Score    (Formula: weighted average of F, G, geography)
Col K: Technographic Score   (Formula: based on H match rules)
Col L: Intent Score          (Formula: based on I + hiring + funding signals)
Col M: ICP Score             (Formula: J*0.30 + K*0.30 + L*0.40)
Col N: AI Personalization    (AI column: generate first-line based on B, E, H)
Col O: Routing               (Formula: if M > 85 then "hot" elif M > 70 then "warm")

Credit Governance Rules

1. Pre-qualify before enriching - domain check + firmographic filter before spending on email waterfall
2. Cap per campaign - no single campaign burns more than 40% of monthly credits
3. Alert at 75% - Slack/email alert when usage crosses 75% of monthly allowance
4. Audit weekly - credits spent vs. leads enriched vs. leads qualified (target >60% qualification)
5. 90-day re-enrichment - re-enrich stale contacts before including in new campaigns

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Section 4: Contact Verification Pipeline

Unverified cold email lists carry 10-30% invalid addresses. Sending to bad addresses destroys sender reputation within a few campaigns. Google, Yahoo, and Microsoft now enforce bounce rates under 2% and spam complaints under 0.3%.

Verification Pipeline Steps

Step	Check	Action	Cost
1	Syntax validation	Remove malformed addresses (missing @, double dots)	Free
2	DNS/MX lookup	Verify domain has valid mail server	Free
3	SMTP verification	Confirm mailbox exists at provider	Provider-based
4	Catch-all detection	Flag domains that accept all addresses	Provider-based
5	Role account check	Flag info@, support@, admin@, sales@	Provider-based
6	Confidence scoring	Assign final deliverability score	Computed

Confidence Score Thresholds

Confidence	Classification	Action
>0.85	Deliverable	Safe to send. Include in sequences.
0.70-0.85	Risky	Send in small batches. Monitor bounce rate per batch.
0.50-0.69	Catch-all/Unverifiable	Segment separately. Maximum 50 per day. Watch closely.
<0.50	Invalid/High Risk	Reject. Do not send. Re-enrich with alternate provider.

Catch-All Domain Handling

Catch-all domains accept every email sent to them, even addresses that do not exist. They create silent deliverability decay because campaigns appear sent but never reach decision-makers.

Rules for catch-all addresses:

• Never mix catch-all addresses into your primary sending pool
• Send catch-all segments from a separate sending domain
• Limit to 20-50 catch-all sends per domain per day
• Track reply rates separately; if reply rate drops below 1%, stop sending to that domain
• Re-verify catch-all addresses every 30 days

Verification Tool Comparison

Tool	Verification Method	Catch-All Detection	Bulk Speed	Pricing
MillionVerifier	SMTP + proprietary	Yes	1M/hour	$0.0005/email
ZeroBounce	SMTP + AI scoring	Yes	100K/hour	$0.008/email
NeverBounce	SMTP + real-time API	Yes	50K/hour	$0.008/email
DeBounce	SMTP + disposable detect	Yes	500K/hour	$0.001/email
Bouncer	SMTP + toxicity check	Yes	200K/hour	$0.005/email

Deliverability Protection Checklist

Before sending any enriched list to outreach:

• All emails verified within the last 7 days
• Bounce rate on verification under 2%
• Catch-all addresses segmented into separate pool
• Role accounts (info@, support@) removed or deprioritized
• Sending domain has SPF, DKIM, and DMARC configured
• Sending domain warmed for at least 14 days
• Daily send volume does not exceed 50 per inbox per day (cold)
• Spam complaint rate on prior campaigns under 0.3%

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Section 5: Performance Benchmarks

Expected Conversion Lift from Enrichment

Metric	Before Waterfall	After Waterfall	Improvement
Email coverage rate	55-65%	85-95%	+30-40%
Email bounce rate	7-15%	<2% (verified)	-70-85%
Connect rate (cold call)	4-6%	8-12%	+80-100%
Pipeline generated	Baseline	+37%	Significant
Meeting-to-customer conversion	Baseline	+27%	Significant
MQL-to-SQL rate (with intent)	8-12%	15-25%	+80-100%

Cost-Per-Verified-Lead Benchmarks

Approach	Cost Per Lead	Coverage	Quality
Single provider (Apollo)	$0.05-$0.15	60%	Medium
Two-step waterfall	$0.15-$0.35	78%	Medium-High
Three-step waterfall	$0.30-$0.60	88%	High
Full waterfall + verification	$0.50-$1.00	92% verified	Very High
Full waterfall + intent scoring	$1.50-$3.00	92% + scored	Premium

ROI Calculation Framework

Cost:  Clay Pro ($800) + Apollo ($99) + FindyMail ($49) + MillionVerifier ($25) = $973/mo
Yield: 2,000 enriched > 1,840 verified (92%) > 1,012 ICP-qualified (55%)
       > 30 meetings (3%) > 12 opps (40%) > 3 closed-won (25%) at $15K ACV = $45K/mo
ROI:   $45,000 / $973 = 46x

Adjust conversion rates for your actual pipeline. The framework matters more than the sample numbers.

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Section 6: Compliance

Compliance by Region

Requirement	US (CAN-SPAM/CCPA)	EU (GDPR)	UK (UK GDPR)
B2B email consent	Opt-out model	Legitimate interest	Legitimate interest
Data source docs	Recommended	Required	Required
Right to erasure	CCPA: Yes	Required	Required
Data retention	Disclosure required	Define and enforce	Define and enforce

Provider Notes

• Dropcontact generates contacts algorithmically without a database (GDPR-native)
• Apollo, ZoomInfo, Clearbit are compliant as platforms; you own your usage basis
• Clay is compliant, but third-party providers accessed through Clay may not be. Verify each.
• Bombora cooperative data is compliant; downstream outreach must follow local regulations

Safe Enrichment Practices

1. Document your legal basis (legitimate interest for B2B is standard)
2. Track which provider sourced each contact
3. Honor opt-out and erasure requests within 30 days
4. Do not enrich or contact individuals who have previously opted out
5. Review provider DPAs annually

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Examples

• User says: "Set up lead enrichment for our outbound" → Result: Agent asks budget and volume; recommends waterfall tier (e.g. Clay + Apollo for $200–1K/mo); outlines steps: import → pre-filter → waterfall → verify (confidence >0.85) → score → route to SDR/sequence; suggests CRM push and 90-day re-enrich.
• User says: "Our email bounce rate is high" → Result: Agent checks verification (MillionVerifier, NeverBounce) and confidence threshold; recommends catch-all segment and list hygiene; suggests <2% bounce target and re-verification before each campaign.
• User says: "Which enrichment tools should we use?" → Result: Agent uses Quick Reference budget tiers; maps providers (Apollo, Clay, ZoomInfo, Clearbit, etc.); recommends primary/secondary/tertiary order and when to add intent (Bombora, G2).

Troubleshooting

• Low email coverage after waterfall → Cause: Weak providers or wrong order. Fix: Put best provider first; add LinkedIn/FindyMail as fallback; target >85% coverage; track per-provider fill rate.
• ICP score not predicting meetings → Cause: Wrong weights or stale data. Fix: Recalibrate firmographic/technographic/behavioral weights; ensure intent signals fresh; A/B test score bands (e.g. >85 hot, 70–84 warm).
• Credits burning too fast → Cause: Enriching everyone or wrong filters. Fix: Pre-filter by domain, industry, geo; set confidence threshold (e.g. 0.85 outreach, 0.50 nurture); cap credits per qualified lead (<50).

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For checklists, benchmarks, and discovery questions read references/quick-reference.md when you need detailed reference.

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Related Skills

• positioning-icp - Define the ICP that enrichment scores against. Start here if ICP is undefined.
• ai-cold-outreach - Use enriched data in personalized cold email sequences. Enrichment feeds outreach.
• ai-sdr - Automate SDR workflows that consume enriched, scored leads.
• gtm-engineering - Build the technical infrastructure (APIs, webhooks, CRM integrations) that connects enrichment to the rest of the stack.
• solo-founder-gtm - Budget-optimized enrichment for founders doing their own outbound.