Alberto Torres | Marketing Automation & Email Operations Specialist

Technical Stack

The Tools Behind a $4.2M Operation

Managing 23M+ subscribers and 3.6M+ monthly sends requires the right infrastructure. Here's what I use daily to analyze 400+ campaigns per cycle and drive measurable revenue improvements.

Analytics & Code

SQL Analytics (Looker + Claude/Gemini)
Google Analytics & Looker Studio
Google Postmaster Tools (Deliverability)
API/Webhook Integrations
HTML/CSS (Email Debugging & Templates)
JSON (API Payloads & Data Mapping)
Python & Playwright (Automated Link Verification)
Terminal & Claude Code (AI-Assisted Ops)

ESP & Automation

Ongage, MessageBird (Revenue Operations)
Klaviyo (4+ years)
Brevo (Email, Drip Campaigns & CRM)
Marketo & HubSpot
Zapier & Make.com (Complex Workflows)
Google Sheets + Apps Script (Data Integration)
Synergy/Everflow (Affiliate Tracking)
LiveIntent, Ezoic, Outbrain (Ad Monetization)

Scale & AI Workflow

3.6M+ Monthly Sends
Claude AI (Queries, Troubleshooting, Interpretation)
Gemini (Raw Data Processing)
User Lifecycle Tracking & Funnel Analytics
Multi-Domain Management

My Analytical Approach

How I Analyze Email Revenue

I approach email operations with forensic rigor — tier classification, fatigue detection, and slot optimization working together as a systematic decision engine.

Tier Classification

Revenue Per Email (RPE) Based

🏆 TOP SHELF RPE > $0.001

Premium slots only (MD). High-value offers with proven performance.

Ex: milestone_tng ($0.0039), destiny_tng ($0.0032)

📊 MEDIUM SHELF $0.0005 - $0.001

Secondary slots (AM, TAR). Rotation candidates.

Ex: mdfoodbreakfast ($0.00089)

⛔ LOW SHELF RPE < $0.0005

Eliminate or pause. Dragging down averages.

Ex: bundled_offers ($0.00000)

Fatigue Detection

Early Warning System

LOW FATIGUE 0-5% penalty

• CTR decline < 10%
• Unsub rate < 0.15%

→ Safe to continue

MEDIUM FATIGUE 10-20% penalty

• CTR decline 10-30%
• Unsub rate 0.15-0.25%

→ Increase rotation gap

HIGH FATIGUE 30%+ penalty

• CTR decline > 30%
• Unsub rate > 0.25%

→ PAUSE IMMEDIATELY

Formula: Optimal_Gap = (Peak_CTR / Current_CTR) × 14 days

Slot Multipliers

Time-Based Optimization

MD (Midday)

11am-1pm window

1.00x

BASELINE

AM (Morning)

7am-9am window

0.53x

TAR (Targeted)

Segment-specific

0.44x

PM (Afternoon)

3pm-5pm window

0.34x

Rule: TOP_SHELF offers → MD slots only. Medium performers rotate through AM/TAR.

📊 Real Data From My Dashboard

Email Performance & Audience Fatigue Chart - June to August 2025

Fatigue Detection in Action: Open Rate, CTR, and Unsub trends tracked over 90-day windows

This approach analyzes 400+ campaigns per cycle and drives measurable revenue improvements.

See It In Action

Proof, Not Promises

What I've Built — Real Revenue Impact

From scaling $4.2M email operations to automating $137K+ in manual workflows — here's how I've applied data analytics and automation to drive measurable results.

$4.2M Operation 23M+ Subscribers 400+ Campaigns/Cycle SQL & AI

Building a $4.2M Revenue Engine That Runs on Autopilot

📉 The Problem:

$4.2M in revenue but profit margins stuck at 22%. Performance was declining, offer rotation was disorganized, and there was no systematic tracking. The team needed visibility into what was actually driving results.

🔍 The Diagnosis:

Manual processes + poor segmentation meant no visibility into what actually drove performance. The team needed a systematic tracking approach.

🛠️ The Fix:

Campaign Analytics System

Built custom tracking analyzing 400+ campaigns per reporting cycle across 90-day windows, systematically finding offer fatigue patterns, slot performance sweet spots, and optimal send times

Automated Revenue Optimization

Built Zapier workflows connecting Looker analytics to Ongage, eliminating manual processes and enabling real-time rotation based on AI-predicted fatigue scores

Scale Operations

Managed 5 daily campaigns across 23M+ subscribers with 3.6M+ monthly sends across multiple domains while maintaining deliverability

Affiliate & Monetization Operations

Managed 99+ affiliate offers via Synergy/Everflow, coordinated ad revenue across ZAN, Ezoic, LiveIntent, and Outbrain. Executed cross-platform revenue forensics that caught $8,400+ in misattributed revenue

Deliverability & IP Recovery

Monitored IP reputation via Google Postmaster Tools. Executed emergency recovery from 100% Medium to 40% High in 5 days using targeted 30-day engaged user strategy

✅ The Result:

30% Revenue Decline Reversed

12% Q/Q RPE Increase

53% Unsub Rate Drop

400+ Campaigns Analyzed/Cycle

🔍 Analytical Wins (Real Cases):

💰 Scoredit Fix

$15K/mo

Revenue gap identified via placement analysis—identical traffic, 100x revenue difference

📈 KFC Recovery

+155.6%

CTR improvement via strategic rotation—documented methodology for replication

🛡️ CVS Save

-56.2%

CTR decline caught early via fatigue detection—implemented 30-day pause protocol

Demographic Analytics

AI Subscriber Analysis

Looker Master Dashboard

Affiliate Revenue Tracking

Looker Analytics - Real-time

LIVE

Revenue/Email

$0.0183

12% Q/Q

Click Rate

0.60%

Unsub Rate

0.8%

-53%

looker_query.sql

● RUNNING

-- Finding dormant high-value subscribers...

SELECT email, total_ltv, days_inactive

FROM subscribers

WHERE days_inactive > 90

AND total_ltv > 500

AND engagement_score > 0.7

ORDER BY total_ltv DESC

LIMIT 10000;

✓ Query complete: 10,000 high-value targets found

✓ Zapier workflow triggered → Ongage campaigns

✓ Revenue decline reversed: +30%

_

📅 Weekly Revenue Heatmap Slot × Day Performance

	AM	MD	PM	TAR
Mon	$607	$1,204	$390	$430
Tue	$0	$1,726	$645	$640
Wed	$0	$1,588	$265	$796
Thu	$512	$2,103	$478	$689
Fri	$723	$1,891	$312	$445

Green = High RPE | Yellow = Medium | Red = Low | Gray = Skip

decision_algorithm.py

# Campaign Scheduling Decision Engine
DECISION_CRITERIA = {
  1: "Historical RPE by slot",
  2: "Days since last send (min 10)",
  3: "Brand conflict check",
  4: "Slot multiplier applied",
  5: "Day-of-week psychology"
}

SLOT_MULTIPLIERS = {
  "MD": 1.00,  # Baseline - premium
  "AM": 0.53,  # Morning secondary
  "TAR": 0.44, # Targeted segments
  "PM": 0.34   # Afternoon lower
}

# Output: $41K+ weekly projection
# Accuracy: 87% vs actual revenue

Revenue by Slot

Testing Framework

Campaign Scheduling 5 Properties $41K+/Week Projections

Data-Driven Campaign Scheduling: Turning Analysis Into Daily Decisions

📉 The Problem:

Campaign scheduling was guesswork. Offers got burned out, premium slots wasted on low performers, and nobody tracked why certain days outperformed others. We needed a system—not opinions.

🛠️ The System I Built:

5-Criteria Decision Algorithm

Historical RPE → Fatigue check (10-day minimum) → Brand conflicts → Slot multipliers → Day psychology

Revenue Heatmap Analysis

MD slot = 1.00x baseline (premium placement). PM slot = 0.34x. TOP_SHELF offers only go to MD.

Brand Conflict Prevention

No duplicate brands per week. Competitive offers separated by 3+ days minimum.

AI-Assisted Optimization

Claude for SQL query building, Gemini for pattern detection across 5 properties simultaneously

Affiliate Slot Management

99+ affiliate offers restricted to TAR/PM slots only (spam trap avoidance). RPC thresholds >$0.50, brand conflict separation by 3+ days

✅ The Output:

Weekly Projections $41K+

Revenue forecasting per calendar

Prediction Accuracy 87%

Projection vs actual revenue

Properties Managed 5

Simultaneous calendar coordination

Decision Speed 2hrs

Full weekly calendar build time

Key Insight: The methodology matters more than individual campaign wins. Once I built this system, calendar planning went from 8+ hours of guesswork to 2 hours of systematic data application.

Looker SQL (AI-assisted) Claude/Gemini Ongage Synergy/Everflow Google Postmaster

Crisis Recovery: 90% Revenue Drop Make.com Architecture Automated Verification

WagerBird: Automating $137K+ in Manual Revenue Workflows

📉 The Problem: Manual Execution Bottlenecks

The entire marketing operation relied on **100% manual execution**. Every link was checked by hand, every purchase was logged manually, and every segmentation tag was applied one-by-one. This human-dependency led to a **90% revenue collapse** when manual errors caused massive link failure and carrier blocks.

🔍 The Diagnosis: Lack of Scalable Infrastructure

The business was attempting to scale a $100K+ operation on a "broken manual engine." Without automation, high-intent windows like the **"Day 11 Danger Zone"** were missed, and $41.7K in dormant VIP revenue was ignored because there was no automated way to identify "Whales."

🛠️ The Fix: Full-Stack Automation Architecture

Automated Stripe → CRM Pipeline

Replaced hours of manual data entry with a real-time Make.com sync that instantly routes Stripe events to AWeber and HubSpot, ensuring zero data-lag.

4-Way "Hands-Free" Segmentation

Engineered a self-healing native lookup database that automatically segments "Whales" vs. VIPs, triggering high-touch recovery without a single manual click.

Automated Link & Compliance Audit

Built an AI-assisted automated verification system (Claude Code + Playwright) to audit 100% of links and carrier-banned copy before any broadcast is deployed.

$41.7K Dormant VIP Revenue Identified

85% Reduction in Carrier Blocks

Day 11 Automated Retention Trigger

100% Verified Link Accuracy

CORE_ORCHESTRATION_LOGIC.MAKE

MOBILE_UX.JPG

LIFECYCLE_FLOW.PNG

verify_links.py

$ python3 verify_links.py --campaign WB_SMS_0304

[SYSTEM] Fetching draft proposals...

[BROWSER] Visiting: https://wb.link/promo_A2 ... OK

[CHECK] UTM_Source: 'slicktext' ... MATCH

[IMAGE] Capturing screenshot: 'wb_verify_01.png' ... DONE

✓ All links verified. Dashboard updated.

Campaign-by-Campaign Revenue Reconciliation

UTM Tracking Implementation & Verification

Revenue Analysis Data Reconciliation Financial Accuracy

Uncovering Hidden Revenue Leaks Through Cross-Platform Analysis

📉 The Problem:

Revenue numbers weren't adding up. Our internal tracking showed one figure, the affiliate platform reported another, and nobody knew which was accurate.

Inconsistent revenue reporting between our system and affiliate partners
No systematic process for tracking discrepancies across campaigns
Financial reporting lacked confidence due to attribution gaps

🛠️ The Fix:

Campaign-Level Tracking: Built granular comparison system tracking every campaign's revenue across both platforms
Timeline Analysis: Mapped discrepancies over time to identify systematic patterns vs. one-off errors
Root Cause Investigation: Identified attribution timing differences and tracking pixel issues
Reconciliation Protocol: Established ongoing process to catch and resolve discrepancies proactively

Accuracy Improved

Established reliable reconciliation process

Issues Identified

Caught attribution timing gaps

Financial Trust

Restored confidence in reporting

Prevention Built

Ongoing monitoring protocol

Key Insight: Revenue discrepancies aren't always about wrong numbers—they're often about different measurement windows. Understanding the "why" behind mismatches is more valuable than just forcing numbers to match.

Track Record

How I Got Here

5+ years building automation infrastructure and scaling email operations — from Fortune 500 companies to high-growth startups.

Automation & Growth Architect (Contract)

WagerBird | 2025 - 2026

Architected and deployed a mission-critical SMS & Email automation infrastructure

Built an AI-assisted automated link verification engine using Claude Code + Playwright, eliminating 100% of broken link errors
Engineered complex Make.com orchestration connecting SlickText, AWeber, and HubSpot CRM
Integrated AI-driven quality control (Claude Code) for TCPA compliance and copy auditing
Developed a custom PHP/MySQL campaign approval dashboard with automated "Proof of Work" screenshots
Automated performance data sync to Google Sheets and Looker Studio for real-time ROI tracking

Email & SMS Coordinator

Tibrio | 2021 - 2025

Managing $4.2M+ annual email revenue operation with 23M+ subscribers

Built campaign analytics system analyzing 400+ campaigns per reporting cycle across 90-day windows
Reversed 30% revenue decline through data-driven fatigue analysis and strategic rotation
Configured trigger-based transactional flows using JSON data mapping and webhook integrations
Debugged HTML email templates across clients, troubleshooting rendering issues and inline CSS
Improved profit margins from 22% to 40% through strategic automation and AI
Reduced unsubscribes from 1.7% to 0.8% (53% reduction) through systematic fatigue prevention
Built complex Zapier workflows connecting Klaviyo, Looker, and Sinch
Ran 50+ A/B tests per quarter optimizing engagement
Managed 5 daily campaigns with 3.6M+ monthly sends across multiple domains

Marketing Automation Specialist

Various (UPS, RESTO) | 2019 - 2021

Improved UPS international email clicks by 17% through deliverability optimization
Built chat automations tracking $224K+ in conversions for restaurant industry client
Designed websites that increased conversions 14% over industry benchmarks

I Build the Automation Infrastructure Behind $4.2M Email Operations.

How I Built a $4.2M Email Revenue Engine

The Tools Behind a $4.2M Operation

Analytics & Code

ESP & Automation

Scale & AI Workflow

How I Analyze Email Revenue

Tier Classification

Fatigue Detection

Slot Multipliers

What I've Built — Real Revenue Impact

Building a $4.2M Revenue Engine That Runs on Autopilot

📉 The Problem:

🔍 The Diagnosis:

🛠️ The Fix:

Campaign Analytics System

Automated Revenue Optimization

Scale Operations

Affiliate & Monetization Operations

Deliverability & IP Recovery

✅ The Result:

🔍 Analytical Wins (Real Cases):

Data-Driven Campaign Scheduling: Turning Analysis Into Daily Decisions

📉 The Problem:

🛠️ The System I Built:

5-Criteria Decision Algorithm

Revenue Heatmap Analysis

Brand Conflict Prevention

AI-Assisted Optimization

Affiliate Slot Management

✅ The Output:

WagerBird: Automating $137K+ in Manual Revenue Workflows

📉 The Problem: Manual Execution Bottlenecks

🔍 The Diagnosis: Lack of Scalable Infrastructure

🛠️ The Fix: Full-Stack Automation Architecture

Automated Stripe → CRM Pipeline

4-Way "Hands-Free" Segmentation

Automated Link & Compliance Audit

Uncovering Hidden Revenue Leaks Through Cross-Platform Analysis

📉 The Problem:

🛠️ The Fix:

How I Got Here

Automation & Growth Architect (Contract)

Email & SMS Coordinator

Marketing Automation Specialist

I'm Ready to Join Your Team