For B2B companies running outbound

Marielle Camba

GTM Engineer

Using multiple data sources + Automation + AI
to scale relevant outreach

Tools I work with:

Clay Instantly Apollo Smartlead Prospeo Apify OpenAI HubSpot

What I Do

End-to-end GTM engineering for outbound that actually works

🎯

List Building & TAM Mapping

Custom scraping from directories, Google Maps, product databases, and industry-specific sources. Not just Apollo exports.

🔬

Data Enrichment

Multi-source enrichment with AI qualification. Claygent prompts to verify ICP fit, find signals, and score leads.

✍️

Campaign Strategy & Copy

Segmented messaging based on actual data points. Multiple angles tested simultaneously to find what converts.

⚙️

Clay Workflows

Custom Clay tables with complex enrichment chains, AI scoring, and CRM integrations. Production-ready systems.

📡

Multi-Channel Outreach

Email, LinkedIn, and WhatsApp sequences working together. Account-based plays that reach the right person on the right channel.

🔗

CRM Integration

Every reply, booking, and status change synced to your CRM. Lead routing, pipeline updates, and reporting so nothing falls through the cracks.

Campaign Work

Real campaigns. Real results. Here's what I've built.

Advertising

LinkedIn Ads Agency

Approach: Scraped LinkedIn Ads using Apify, qualified which companies are B2B.

Why it worked: Personalized first line referencing their actual LinkedIn ad activity made the outreach hyper-relevant.

Key Insight: Scraped actual ad data for hyper-relevant outreach
Campaign results
Restaurant Tech

AI Solution for Restaurant Ordering

Approach: Scraped Slicelife and Toasttab restaurant directories. Used Prospeo to find emails associated with domains and reverse prompts to find job titles.

Why it worked: Restaurant prospects are hardly found in LinkedIn/Apollo. These emails are hardly touched by cold email, so they're more open.

Key Insight: Untapped email audiences with near-zero cold email saturation
Campaign results
Legal Tech

Reputation Management Platform

Approach: Scraped law firms using Serper, segmented into 3 segments with 3 different messaging angles. Scraped actual Google reviews using Apify.

Why it worked: Created 3 distinct segments (< 80 reviews, 1-2 bad reviews, 100+ reviews) with completely different pain points and messaging.

Key Insight: 3-segment approach with scraped review data for personalization
Campaign results
Hospitality

WhatsApp Business Messaging

Approach: Scraped Hotels from Apollo, Directories, and Google Maps using SerpAPI. Referenced their OTA listings.

Why it worked: Referenced their OTA listings (Booking.com, etc.) and offered to reduce commission dependency through direct WhatsApp bookings.

Key Insight: Multi-source hotel data with OTA pain point angle
Campaign results
SaaS

AI Agent for Customer Engagement

Approach: Scraped software companies offering free trials from Product Hunt, GetLatka, GetApp, Toolify, Sourceforge. Used Pandamatch and Similarweb for traffic data.

Why it worked: AI prompt checked if they actually offer free trial. Companies with free trials want to convert users to paying customers.

Key Insight: AI-qualified leads based on trial offering + traffic data
Campaign results
SaaS

Customer Retention Platform

Approach: Scraped software directories like Crunchbase, Product Hunt, GetLatka, GetApp, Toolify, Sourceforge. Ran AI prompts to check for free trial offerings.

Why it worked: Targeted companies with specific headcount in phone support/customer support department and heavy website traffic.

Key Insight: AI qualification + department headcount targeting
Campaign results
THE FOUNDATION

Process and Timeline

SETUP
~2 weeks
BUILD
~3 weeks
LAUNCH
~2 weeks
SCALE
Month 3+

ICP & Strategy

  • Firmographic / demographic map
  • Consolidate audience pain
  • Cut your solution into value prop chunks
  • Identify data signals indicating pain/need

Infra & Tech Setup

  • Inbox and domain set-up
  • Configure sequencer
  • Configure Clay
  • Connect to your Calendar + CRM

Map TAM

  • Pull every ICP contact
  • Enrich signal data indicating pain/need
  • Qualify and score with AI
  • Segment TAM based on enrichment and AI

Copywriting

  • Refine offer for cold traffic
  • Build messaging for each TAM segment
  • Split by role
  • Create A/B variants

Launch Campaigns

  • Test messaging for each segment/role
  • Analyze and optimize
  • Track reply rates and positive responses

Book Meetings

  • Create feedback loop - iterate
  • Get to optimal ratio of sent emails/meeting booked
  • Reach message-market fit

Scale & Handoff

  • Hit your whole TAM once every 60 days
  • Maximize cold email as a channel
  • Hand off systems you own

The Difference

Without a GTM Engineer

  • Apollo exports everyone else has
  • Generic "reaching out because..." emails
  • Same message to entire list
  • Manual prospecting taking hours
  • Guessing what works

With Me

  • Custom scraped lists from untapped sources
  • First lines referencing actual signals
  • Segmented messaging by pain point
  • Automated workflows that scale
  • Data-driven iteration on what converts

Let's Talk

Have an outbound challenge? Let's figure it out together.

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