campaign-optimization

Optimize paid campaigns using a phase-driven framework from learning through scale.

2|Updated Apr 15, 2026

Search Tags:#scaling #latam #campaign optimization #paid media #budget allocation #creative testing #learning phase

Ready to run

npx skills add https://github.com/DojoCodingLabs/GTM-Engineering-Command-Center --skill campaign-optimization

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: campaign-optimization
Source: https://github.com/DojoCodingLabs/GTM-Engineering-Command-Center/tree/main/skills/campaign-optimization
Command: npx skills add https://github.com/DojoCodingLabs/GTM-Engineering-Command-Center --skill campaign-optimization

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Campaign optimization provides a structured, phase-driven framework to optimize paid acquisition campaigns from learning through scale, reducing manual guesswork and improving CPA/ROAS.

Core Features & Use Cases

Phase-based playbooks for learning, testing, and scaling
Guardrails like 70/20/10 budget allocation and learning-phase rules
LATAM-aware optimization and cross-channel expansion

Quick Start

Start Phase 1 by setting up 2-3 ad sets with varied audiences at $20-30/day and following the Week 1-2 learning phase guidelines.

Frequently Asked Questions about campaign-optimization

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

What's the best way to optimize paid media campaigns for scaling?▼

Campaign optimization uses a phase-driven framework from learning through scale to improve CPA and ROAS. It enforces guardrails like minimum data thresholds and a 70/20/10 budget allocation across Meta, Google, TikTok, and LinkedIn to reduce manual guesswork.

How do I structure a learning phase for paid acquisition campaigns?▼

Start Phase 1 by setting up 2-3 ad sets with varied audiences at $20-30/day. The structured learning phase enforces minimum data thresholds and weekly review checkpoints before scaling budgets to ensure algorithmic stability.

Does this campaign optimization framework support LATAM paid media?▼

Yes, this framework applies LATAM-aware optimization nuances to paid acquisition campaigns. It structures cross-channel expansion across Meta, Google, TikTok, and LinkedIn specifically accommodating LATAM market dynamics during scaling.

How do I allocate budget for creative testing during scaling?▼

Apply a repeatable 70/20/10 budget distribution for creative testing and scaling. This disciplined allocation routine pairs with a scheduled creative refresh cadence and weekly review checkpoints to maintain ROAS.

Why does my CPA spike when scaling paid campaigns across channels?▼

CPA spikes often occur when learning phase guardrails and minimum data thresholds are bypassed during cross-channel expansion. This framework prescribes phase-based playbooks with routine weekly checkpoints to stabilize CPA before scaling budgets.

When should I not scale my paid campaigns?▼

Avoid scaling paid campaigns when minimum data thresholds are unmet or learning phase rules are violated. This framework enforces strict guardrails and escalation rules, requiring stable CPA and ROAS metrics before expanding budget allocations.