contact-enrichment

name	contact-enrichment
description	Get verified emails, phones, socials.
metadata	{"author":"Alfonso Sainz de Baranda (Growth4U)","version":"1.0","system":"SanchoCMO","phase":"Encuentra (one-to-one)","depends_on":"decision-maker-finder","chains_to":"outreach-sequence-builder, email-sequences"}
context_required	["brand/{slug}/company-brief/company-brief.current.md","brand/{slug}/go-to-market/ecps/ecps.current.md","brand/{slug}/go-to-market/ecps/ecps.current.md"]
context_writes	["campaigns/","brand/{slug}/operational/assets.md"]

Contact Enrichment — The Last Mile Before Outreach

"The best outreach fails if it lands in the wrong inbox."

Este skill convierte una lista de decision makers en contactos listos para outreach. No basta con saber quienes son — necesitas saber COMO llegar a ellos: email verificado, telefono directo, perfiles sociales.

Diferencia con decision-maker-finder:

• decision-maker-finder: Quienes son los decision makers (IDENTIDAD)
• contact-enrichment: Como contactarlos (DATOS DE CONTACTO)

Read ./brand/ per _system/intelligence/brand-memory.md (if using SanchoCMO framework)

Follow _system/output/output-format.md (if using SanchoCMO framework)

---

Prerequisites

Required input:

• Decision makers list from decision-maker-finder skill
• File: brand/{slug}/operational/decision-makers-YYYYMMDD.json
• At minimum: name + company + title (LinkedIn URL is a bonus)

API Keys needed (at least ONE):

• Minimum: Hunter.io free plan (25 searches/mo + 50 verifications/mo)
• Recommended: Apollo.io (free, 50 credits/mo) + Hunter.io (verification)
• Full stack: Apollo + Hunter + SignalHire + Snov.io

Optional context:

• brand/{slug}/operational/target-companies.json (for domain lookup)
• brand/{slug}/go-to-market/ecps.json (for title matching validation)

---

Workflow

Step 0: Tool Detection (Automatic)

Check which enrichment APIs are configured:

CHECK environment for API keys:
  ├─ APOLLO_API_KEY     → apollo available
  ├─ HUNTER_API_KEY     → hunter available
  ├─ SIGNALHIRE_API_KEY → signalhire available
  ├─ SNOV_CLIENT_ID     → snov available
  ├─ LUSHA_API_KEY      → lusha available (phone)
  └─ ZOOMINFO_*         → zoominfo available (phone)

Mode: FULL (3+ providers) / STANDARD (1-2) / LIGHT (manual)

Estimated found rate:
  FULL:     85-95% emails, 50-70% phones
  STANDARD: 70-85% emails, 30-50% phones
  LIGHT:    40-60% emails (manual)

If NO API keys → switch to LIGHT mode (see section below).

---

Step 1: Load Contacts

Read from Context Lake:
  └─ brand/{slug}/operational/decision-makers-YYYYMMDD.json

Extract per contact: name, title, company, domain, LinkedIn URL, existing data

If NO decision makers file → ERROR: Run /decision-maker-finder first

Present: total contacts, % with LinkedIn URL, % with domain, how many already have email.

---

Step 2: Select Enrichment Depth

Depth	What	Best for	Cost per 100
Email Only	Email waterfall + verification	Email-first outreach	$5-15
Email + Phone	Full waterfall	Multi-channel, SDR teams	$20-40
Full Enrichment	Email + Phone + Social	ABM, high-value prospects	$30-60

User selects -> Proceed with appropriate depth.

---

Step 3: Waterfall Email Enrichment

For each contact, try providers in order. STOP at first verified match.

See waterfall-providers.md for complete API details.

Pass 1 — Apollo.io (if available):

POST https://api.apollo.io/v1/people/match
Body: { first_name, last_name, organization_name, domain }

IF email_status == "verified" → ACCEPT (high confidence)
   BONUS: Also capture phone if returned
IF email_status == "guessed" → pending_verification
IF no result → CONTINUE

Hit rate: 60-70%. Time: ~2 min/100 contacts.

Pass 2 — Hunter.io (if available):

GET https://api.hunter.io/v2/email-finder
Params: domain, first_name, last_name

IF score >= 90 → ACCEPT (high confidence)
IF score >= 70 → pending_verification
IF no result → CONTINUE

Additional hit rate: 15-25%.

Pass 3 — SignalHire (if available):

POST https://www.signalhire.com/api/v1/candidate/search
Body: { linkedin_url }

IF isVerified == true → ACCEPT (high confidence)
   BONUS: Phone numbers often included
IF no result → CONTINUE

Additional hit rate: 5-15%.

Pass 4 — Snov.io (if available):

POST https://api.snov.io/v1/get-emails-from-name
Body: { firstName, lastName, domain }

IF emailStatus == "valid" → ACCEPT (medium confidence)
IF emailStatus == "unverifiable" → low confidence
IF no result → "not_found"

Last resort. Additional hit rate: 5-10%.

---

Step 4: Email Verification

See email-verification.md for full pipeline.

VERIFICATION PIPELINE:

1. Syntax check (instant) — regex, remove malformed
2. MX record check (instant) — DNS lookup, remove no-MX domains
3. Hunter.io verification API:
   GET https://api.hunter.io/v2/email-verifier?email={email}
   "deliverable" + score >= 90 → HIGH
   "deliverable" + score 70-89 → MEDIUM
   "risky"                     → MEDIUM (max)
   "unknown"                   → LOW
   "undeliverable"             → DISCARD
4. Catch-all detection — if catch-all domain → cap at MEDIUM
5. Disposable email check — if disposable → DISCARD

---

Step 5: Phone Enrichment (if requested)

Only runs for "Email + Phone" or "Full Enrichment" depth.

PHONE WATERFALL:
1. Check Apollo responses (may already have phone from Step 3)
2. SignalHire → POST /api/v1/candidate/search (LinkedIn URL input)
3. Lusha → POST https://api.lusha.com/person (name + company)
4. ZoomInfo → enterprise only, if client has subscription

---

Step 6: Social Profile Enrichment (if requested)

Only runs for "Full Enrichment" depth.

1. LinkedIn URL — already from decision-maker-finder (95%+ coverage)
2. Twitter/X — WebSearch: "{name} {company} site:twitter.com OR site:x.com"
3. GitHub/Medium — optional, for technical/content decision makers

---

Step 7: Confidence Scoring

FOR each contact:
  HIGH   = email verified + non-catch-all + 2+ sources (90%+)
  MEDIUM = email found + MX valid + catch-all OR single source (70-89%)
  LOW    = email guessed + no verification OR pattern match only (<70%)

  overall = min(email_confidence, phone_confidence) if phone requested
         OR email_confidence if email only

---

Step 8: Present Results

CONTACT ENRICHMENT — Complete

Emails: [found]/[total] ([%]) | Verified: [N] | HIGH: [N] | MEDIUM: [N] | LOW: [N]
Phones: [found]/[total] ([%]) | Mobile: [N] | Direct: [N]
Social: LinkedIn [N] | Twitter [N]

Provider breakdown + cost per provider
Total cost: $X for [N] contacts

READY FOR OUTREACH: [N] HIGH confidence (safe) + [N] MEDIUM (caution)

---

Step 9: Save Output

File: brand/{slug}/operational/contacts-enriched-YYYYMMDD.json

{
  "date": "2026-02-21",
  "source": "contact-enrichment",
  "enrichment_depth": "email+phone",
  "providers_used": ["apollo", "hunter", "signalhire"],
  "contacts": [
    {
      "name": "Jane Doe",
      "title": "VP Marketing",
      "company": "Example Corp",
      "email": "[e-mail]",
      "email_confidence": "high",
      "email_source": "hunter",
      "email_verified": true,
      "phone": "[phone]",
      "phone_type": "mobile",
      "phone_source": "signalhire",
      "linkedin_url": "linkedin.com/in/janedoe",
      "twitter_url": "twitter.com/janedoe",
      "enrichment_date": "2026-02-21"
    }
  ],
  "stats": {
    "total_contacts": 142,
    "email_found": 128,
    "email_verified": 115,
    "phone_found": 67,
    "email_found_rate": "90%",
    "avg_confidence": "high",
    "providers_hit_rate": {
      "apollo": "65%",
      "hunter": "20%",
      "signalhire": "5%"
    }
  }
}

Append summary to ./brand/{slug}/operational/assets.md.

---

LIGHT Mode — Manual Enrichment

When no API keys are configured or budget is zero.

1. Hunter.io Free Plan — 25 searches/mo + 50 verifications/mo. Use for top-priority contacts.

2. Domain Pattern Detection — GET https://api.hunter.io/v2/domain-search?domain=example.com. Find the pattern, apply to all contacts at that domain.

3. Common Email Patterns (try in order):

   {first}.{last}@domain.com       [e-mail]
   {first}{last}@domain.com        [e-mail]
   {first}@domain.com              [e-mail]
   {f}{last}@domain.com            [e-mail]
   {first}_{last}@domain.com       [e-mail]
   

4. Google Pattern Search — "jane doe" "example.com" email or "[e-mail]"

5. Manual LinkedIn — Profile > Contact info (requires connection or InMail).

LIGHT Workflow:

1. Group contacts by domain
2. Hunter.io domain search per domain → detect pattern
3. Apply pattern to all contacts at that domain
4. Verify top 5 per domain via Hunter.io verifier
5. If pattern works → apply to rest (MEDIUM confidence)
6. Remaining: Google search + LinkedIn manual
7. Output mostly MEDIUM confidence

---

Cost Estimation

Per 100 Contacts

Depth	Providers	Cost	Found Rate
Email only (free)	Apollo free + Hunter free	$0	40-60%
Email only (paid)	Apollo + Hunter paid	$5-15	80-90%
Email + Phone	Apollo + Hunter + SignalHire	$20-40	Email 85%, Phone 50%
Full enrichment	All providers	$30-60	Email 90%+, Phone 60%+

Monthly Budget by List Size

Contacts	Email Only	Email + Phone	Full
50	$3-8	$10-20	$15-30
100	$5-15	$20-40	$30-60
500	$25-75	$100-200	$150-300
1,000	$50-150	$200-400	$300-600

---

GDPR / Privacy Warning

This skill handles personal data. Comply with applicable data protection laws.

Requirement	Action
Legal basis	Document legitimate interest for B2B prospecting
Data minimization	Only collect data needed for outreach purpose
Storage limitation	Delete enriched data after 12 months if no engagement
Right to erasure	If contact requests removal, delete within 30 days
Opt-out mechanism	Every outreach must include unsubscribe option
Record keeping	Log when and where each data point was obtained

EU (GDPR): B2B email to professional addresses permitted under legitimate interest. Personal emails (gmail, yahoo) require more care. Always include company name + opt-out.

Spain (LOPDGDD): Follows GDPR. AEPD active on enforcement. Add "Conforme al Art. 21 LSSI" in commercial emails.

Best practice: Limit outreach to professional email addresses at company domains. Avoid personal email and mobile unless clear business relationship.

---

Integration with SanchoCMO Framework

Reads from Context Lake

File	What it provides	How it's used
brand/{slug}/operational/decision-makers-YYYYMMDD.json	Names, titles, companies, LinkedIn URLs	Input contacts to enrich
brand/{slug}/operational/target-companies.json	Company domains	Domain lookup for email patterns
brand/{slug}/go-to-market/ecps.json	Target titles/roles	Validation enriched contacts match target

Writes to Context Lake

File	What it contains
brand/{slug}/operational/contacts-enriched-YYYYMMDD.json	Enriched contacts with emails, phones, socials
./brand/{slug}/operational/assets.md	Append: Enrichment summary and stats

Chains to

• /outreach-sequence-builder — Build personalized outreach sequences
• /email-sequences — Create email drip campaigns to verified emails
• /direct-response-copy — Write outreach copy using contact context

Depends on

• /decision-maker-finder — Must run first to provide contacts to enrich

---

Reference Files

• waterfall-providers.md — Provider guide: API endpoints, auth, formats, rate limits, costs
• email-verification.md — Verification pipeline: syntax, MX, SMTP, catch-all, disposable, scoring

---

Frequency

• Initial run: After each decision-maker-finder execution
• Re-verification: Every 90 days (people change jobs, emails go stale)
• Pre-campaign: Always re-verify before launching new outreach campaign
• Why: 2-3% of B2B emails go stale per month. Re-verification costs less than bounce damage.

---

The last mile matters most. Verified data = delivered outreach = real conversations.