Gtm Enrichment Smart

GTM Enrichment — Smart (Multi-Provider Waterfall)

Setup

Choose the available runtime before doing any credential setup:

• Terminal-free client: skip the shell commands below. Use connected MCP tools. For ScrapeCreators operations, read scrapecreators-api and prefer call_data_provider. If a required enrichment provider has no connected tool, report that part of the waterfall as unavailable rather than fabricating enrichment data.
• Local terminal: use the GooseWorks credentials and proxy commands below.

Read your credentials from ~/.gooseworks/credentials.json:

export GOOSEWORKS_API_KEY=$(python3 -c "import json;print(json.load(open('$HOME/.gooseworks/credentials.json'))['api_key'])")
export GOOSEWORKS_API_BASE=$(python3 -c "import json;print(json.load(open('$HOME/.gooseworks/credentials.json')).get('api_base','https://api.gooseworks.ai'))")

If ~/.gooseworks/credentials.json does not exist, tell the user to run: npx gooseworks login

The local proxy endpoints use Bearer auth: -H "Authorization: Bearer $GOOSEWORKS_API_KEY". ScrapeCreators operation descriptions below remain environment-neutral in both runtimes.

Enrich a lead from an email address (+ optional name) using a waterfall strategy: start with cheap APIs ($0.01 each), cross-reference for confidence, then use expensive AI agents only for gaps. Spends proportionally to lead quality.

Cost: $0.04 (best) to ~$0.12 (typical with buying signals) to ~$0.26 (worst, Sixtyfour fallback) Latency: ~5-15s typical, up to 60s if Sixtyfour fallback triggers

Input

Required:

• email — the lead's email address (e.g., jane@acme.com)

Optional:

• name — full name if known (improves match rate)

Workflow

Step 0: Extract Domain + Free Email Check

Extract the domain from the email. Check if it's a free email provider.

Free email providers (skip Brand.dev if match): gmail.com, yahoo.com, hotmail.com, outlook.com, aol.com, icloud.com, mail.com, protonmail.com, zoho.com, yandex.com, gmx.com, live.com

Set is_free_email = true/false — this gates whether Brand.dev runs in Phase 1.

PHASE 1 — Core (always run, parallel) — ~$0.03-$0.06

Run ALL of these simultaneously:

1a. Apollo People Match ($0.01):

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"apollo","path":"/api/v1/people/match"}'
  "email": "{email}",
  "reveal_personal_emails": true
}'

Extract: person.name, person.title, person.linkedin_url, person.city, person.state, person.country, person.organization.name, person.organization.id (save org_id for Phase 4), person.organization.industry, person.organization.estimated_num_employees, person.organization.keywords, person.organization.funding_events, person.organization.total_funding.

1b. Hunter Combined Enrichment ($0.01):

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"hunter","path":"/v2/combined/find","query":{"email":"{email}"}}'

Extract: data.person.first_name, data.person.last_name, data.person.linkedin_handle, data.person.title, data.company.name, data.company.domain, data.company.industry, data.company.description, data.company.headcount, data.company.technologies, data.company.twitter, data.company.category.

1c. Brand.dev Retrieve ($0.03 — CONDITIONAL: only if is_free_email == false):

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"brand-dev","path":"/v1/brand/retrieve","query":{"domain":"{domain}"}}'

Extract: title (company name), description, industries (including eic code), socials (twitter URL, github URL, linkedin URL), employeeCount, foundedYear, location.

SKIP this call if is_free_email == true — saves $0.03.

1d. Hunter Email Verifier ($0.01):

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"hunter","path":"/v2/email-verifier","query":{"email":"{email}"}}'

Extract: data.status (valid/invalid/accept_all/webmail/disposable/unknown), data.result (deliverable/undeliverable/risky).

PHASE 1 MERGE — Cross-Reference & Confidence

After all Phase 1 calls complete, merge data:

Person merge rules:

1. Full name: prefer Apollo (structured), cross-ref with Hunter
2. Title: prefer Apollo, cross-ref with Hunter
3. LinkedIn URL: prefer Apollo linkedin_url, fallback to Hunter linkedin_handle (prepend https://linkedin.com/in/)
4. Location: prefer Apollo (structured city/state/country)
5. If Apollo and Hunter agree on name+title: confidence = "high"
6. If only one source has data: confidence = "medium"
7. If they disagree on name or title: flag conflict, keep both, confidence = "low"

Company merge rules:

1. Name: prefer Apollo org name, cross-ref with Hunter + Brand.dev
2. LinkedIn URL: prefer Brand.dev socials, fallback Apollo
3. Description: prefer Brand.dev (richer), fallback Hunter
4. Employee count: prefer Apollo, cross-ref with Brand.dev + Hunter headcount
5. Funding: use Apollo funding_events and total_funding
6. Geo: prefer Apollo org location, cross-ref with Brand.dev
7. Tech stack: use Hunter technologies
8. Social URLs: use Brand.dev socials (twitter, github)

AI/B2B Classification (zero extra cost):

Cross-reference three sources from Phase 1:

Confidence rules:

• high: 2+ sources agree
• medium: 1 source has signal
• low: weak inference only (e.g., "tech company" but no explicit AI/B2B terms)

PHASE 2 — Gap-Fill (conditional) — $0.00-$0.02

2a. Apollo Organization Enrich ($0.01 — ONLY if Apollo Phase 1 returned NO funding_events or funding data is empty):

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"apollo","path":"/api/v1/organizations/enrich","query":{"domain":"{domain}"}}'

Extract: organization.funding_events[], organization.total_funding, organization.latest_funding_stage, organization.latest_funding_amount, organization.estimated_num_employees, organization.annual_revenue.

2b. Tomba Enrich ($0.01 — ONLY if Apollo and Hunter disagree on person name OR title):

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"tomba","path":"/v1/enrich","query":{"email":"{email}"}}'

Use as tie-breaker. If Tomba agrees with Apollo: use Apollo data. If Tomba agrees with Hunter: use Hunter data. If all three disagree: keep Apollo as primary, flag conflict.

PHASE 3 — Sixtyfour Fallback (conditional, expensive) — $0.00-$0.20

3a. Sixtyfour Enrich Lead ($0.10 — ONLY if person NOT found after Phases 1-2, meaning no name AND no title AND no LinkedIn URL from any source):

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"sixtyfour","path":"/enrich-lead"}'
  "lead_info": {
    "email": "{email}",
    "domain": "{domain}"
  },
  "struct": {
    "full_name": "Full legal name of this person",
    "title": "Current job title",
    "linkedin_url": "LinkedIn profile URL (full URL)",
    "city": "City",
    "state": "State or region",
    "country": "Country"
  }
}'

3b. Sixtyfour Enrich Company ($0.10 — ONLY if company has major gaps AND org has >500 employees):

Major gaps = missing 2+ of: LinkedIn URL, description, employee count, funding data.

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"sixtyfour","path":"/enrich-company"}'
  "target_company": {
    "domain": "{domain}"
  },
  "struct": {
    "company_name": "Official company name",
    "description": "One-paragraph description",
    "linkedin_url": "LinkedIn company page URL",
    "employee_count": "Number of employees",
    "total_funding_usd": "Total funding raised in USD",
    "latest_funding_date": "Most recent funding round date",
    "latest_funding_stage": "Most recent round stage",
    "latest_funding_amount_usd": "Most recent round amount"
  }
}'

PHASE 4 — Buying Signals (qualified leads only) — $0.00-$0.04

Gate: Only run Phase 4 if the company is:

• Funded (total_funding > 0) AND
• Classified as B2B (is_b2b_saas = true) AND
• Has >50 employees

4a. Brand.dev AI Products ($0.03 — extracts products, pricing tiers, and features from the website):

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"brand-dev","path":"/v1/brand/ai/products"}'
  "domain": "{domain}"
}'

From the products response, extract buying signals:

• has_enterprise_plan: Check if any product has "enterprise" in name, tier, or target_audience
• has_self_serve: Check if any product has a listed price (self-serve) vs "Contact sales" pricing
• target_market: Infer from target_audience arrays across products

4b. Apollo Job Postings ($0.01 — ONLY if organization_id was captured from Phase 1):

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"apollo","path":"/api/v1/organizations/{organization_id}/job_postings","query":{"organization_id":"{organization_id}"}}'

Search job postings for enterprise sales signals: titles containing "Enterprise", "Account Executive", "Solutions Engineer", "Sales Director", "Customer Success". If found, set hiring_enterprise_reps = true.