Portfolio Pacing Rules

Portfolio Pacing Rules Skill

Purpose: Provides portfolio-specific pacing thresholds, budget tolerances, brand caps, and performance targets that auto-load when analyzing account performance.

Type: Domain knowledge skill (auto-invoked)

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Quick Reference: Pacing Thresholds by Portfolio

Portfolio A

• Budget Pacing: ±5% monthly tolerance (95%-105%)
• Brand Campaign Cap: 15% maximum of total account spend
• Primary KPI: ROAS (Conversion Value / Cost)
• Warning Zone: >±5% (investigate)
• Critical Zone: >±10% (immediate action)

Portfolio B

• Budget Pacing: ±8% monthly tolerance (92%-108%)
• Brand Campaign Cap: None (no restriction)
• Primary KPI: Cost per Conversion (testing ROAS on some accounts)
• Warning Zone: >±8% (investigate)
• Critical Zone: >±10% (immediate action)

Portfolio C

• Budget Pacing: ±8% monthly tolerance (92%-108%)
• Brand Campaign Cap: None (no restriction)
• Primary KPI: Cost per Conversion
• Warning Zone: >±8% (investigate)
• Critical Zone: >±10% (immediate action)

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Universal Pacing Rules (All Portfolios)

Critical Thresholds

• Critical: >±15% variance = Immediate investigation required (KPI miss, client escalation)
• High Priority: >±10% variance = Requires investigation
• Warning: >±8% variance = Monitor closely
• On Pace: Within portfolio tolerance = Acceptable

Month-Start Normalization (Days 1-5)

• Early-month variance is expected (budget ramp-up period)
• Reduce severity tier for pacing variance in first 5 days
• Full threshold rules apply after Day 5
• Note: "Early-month variance expected to normalize by Day 7"

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Portfolio Constraints

Portfolio A Accounts

Strategic Context:

• Budget pacing is non-negotiable (strict client KPI)
• ROAS optimization happens WITHIN pacing constraint
• Brand campaigns capped at 15% despite high efficiency (30-40x ROAS)
• AI campaigns (Pmax/DGen) are workhorses (60-70% of spend)
• Budget reallocation > budget cuts (maintain spend, improve efficiency)
• No shared budgets (need granular control for tight pacing)

Account Examples:

• Acme Plumbing (CID: [CUSTOMER_ID])
• Best HVAC (CID: [CUSTOMER_ID])
• City Dental (CID: [CUSTOMER_ID])
• Account D (multiple accounts)

When to flag:

• Pacing variance >±5%
• Brand spend >15% of total
• Any variance >±10% with ±8%
• Any variance >±10% with 80%)

Portfolio C

Strategic Context:

• Mid-tier accounts (NYC metro area)
• Similar constraints to Portfolio B (±8% pacing tolerance)
• 3 accounts total

Accounts:

• Portfolio C - Multi-region (CID: [CUSTOMER_ID])
• ProClean (CID: [CUSTOMER_ID])
• Quick Fix (CID: [CUSTOMER_ID])

When to flag:

• Pacing variance >±8%
• Any variance >±10% with one large increase (safer, more controllable)
• Client trust requires predictable, controlled spend changes

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Pacing Calculation (Reference)

Data Source: Pacing Dashboard sheet (auto-calculated daily)

Formula:

Pacing Variance = % Through Month - % Spent

Where:
- % Through Month = (Current Day ÷ Days in Month) × 100
- % Spent = (MTD Spend ÷ Monthly Budget) × 100

Example:

• Day 21 of 31 → % Through Month = 67.74%
• MTD Spend: $513 / Monthly Budget: $1,000 → % Spent = 51.30%
• Pacing Variance: 67.74% - 51.30% = +16.44% (UNDERSPENDING)

Interpretation:

• Positive variance (+X%): UNDERSPENDING (spent less than expected by now)
• Negative variance (-X%): OVERSPENDING (spent more than expected by now)
• Zero variance (0%): PERFECT PACING (spent exactly as expected)

IMPORTANT: This calculation is already done in Pacing Dashboard sheet (Column E). You don't need to recalculate it manually - just reference the sheet value.

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Related Documentation

• Your own portfolio context files — strategic context (names, pacing rules, client KPIs)
• Your own accounts map — account name → CID → portfolio mapping
• Your own dashboard/sheet config — tab schemas for pacing data

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Created: 2025-10-28 Last Updated: 2025-11-01 Extracted From: portfolio context files (Section II + III), underspending-investigation-agent.md Status: Active

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: fourteenwm
• Source: fourteenwm/ppc-ai-skills
• License: MIT

Install and usage instructions live in the source repository linked above.