budget-tracker

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Track advertising spend pacing in real time across connected ad platforms (Google Ads, Meta, LinkedIn, TikTok) — produces a budget dashboard with daily burn rates, end-of-period projections, overspend/underspend alerts, and dollar-specific reallocation recommendations backed by CPA/ROAS context. Monitors and recommends only; it never edits platform budgets. Triggers on "/digital-marketing-pro:budget-tracker", "are we overspending this month", "how is our ad budget pacing", "track spend across platforms", "will we blow through the budget cap". Reads budget targets from the brand profile, runs scripts/ad-budget-pacer.py, and saves snapshots for trend history; pairs with /digital-marketing-pro:budget-optimizer.

AI & Automation 809 stars 134 forks Updated 4 days ago MIT

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Skill Content

# /digital-marketing-pro:budget-tracker ## Purpose Track advertising budget in real-time across all connected ad platforms. Analyze spend pacing against targets, project end-of-period totals, flag overspend risks and underspend inefficiencies, calculate daily burn rates, and recommend budget reallocations to maximize ROI within the remaining budget window. Designed for media buyers and marketing managers who need a single view of where money is going and whether it is being spent effectively. ## Input Required The user must provide (or will be prompted for): - **Budget period**: This month, this quarter, or a custom date range (e.g., "Feb 1 - Mar 31"). Determines the pacing denominator and projection horizon - **Ad platforms to include**: All connected platforms or specific ones (e.g., "Google Ads and Meta only"). Defaults to all connected ad MCPs - **Budget targets per platform** (optional): Specific spend targets per platform for the period. If omitted, targets are pulled from `profile.json` budget_range and any saved platform allocations - **Total budget** (optional): Overall budget cap for the period. If omitted, pulled from `profile.json` budget_range - **Alert thresholds** (optional): Custom thresholds for overpace (default: >110% of expected pacing) and underspend (default: <70% of expected pacing) flags - **Include efficiency metrics** (optional): Whether to pull CPA, ROAS, and conversion data alongside spend. Defaults to yes ## Process 1. **Load br...

Details

Author
indranilbanerjee
Repository
indranilbanerjee/digital-marketing-pro
Created
7 months ago
Last Updated
4 days ago
Language
Python
License
MIT

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Testing & QA Listed

budget-tracker

Track advertising spend pacing in real time across connected ad platforms (Google Ads, Meta, LinkedIn, TikTok) — produces a budget dashboard with daily burn rates, end-of-period projections, overspend/underspend alerts, and dollar-specific reallocation recommendations backed by CPA/ROAS context. Monitors and recommends only; it never edits platform budgets. Triggers on "/digital-marketing-pro:budget-tracker", "are we overspending this month", "how is our ad budget pacing", "track spend across platforms", "will we blow through the budget cap". Reads budget targets from the brand profile, runs scripts/ad-budget-pacer.py, and saves snapshots for trend history; pairs with /digital-marketing-pro:budget-optimizer.

0 Updated 3 weeks ago
teachskillofskills-ai
AI & Automation Featured

budget-optimizer

Reallocate marketing spend across channels using performance data and diminishing-returns modeling — produces a current-vs-optimized allocation table, projected ROI ranges with confidence intervals, a phased 4-8 week reallocation timeline, and a 10-15% testing reserve. Recommends shifts only; it never changes spend on any platform. Triggers on "/digital-marketing-pro:budget-optimizer", "optimize my marketing budget", "which channels should get more spend", "reallocate budget based on ROAS", "is our channel split right". Reads the brand profile and guidelines, runs scripts/budget-optimizer.py, and pairs with /digital-marketing-pro:budget-tracker for in-flight pacing.

809 Updated 4 days ago
indranilbanerjee
Data & Documents Listed

budget-optimizer

Reallocate marketing spend across channels using performance data and diminishing-returns modeling — produces a current-vs-optimized allocation table, projected ROI ranges with confidence intervals, a phased 4-8 week reallocation timeline, and a 10-15% testing reserve. Recommends shifts only; it never changes spend on any platform. Triggers on "/digital-marketing-pro:budget-optimizer", "optimize my marketing budget", "which channels should get more spend", "reallocate budget based on ROAS", "is our channel split right". Reads the brand profile and guidelines, runs scripts/budget-optimizer.py, and pairs with /digital-marketing-pro:budget-tracker for in-flight pacing.

0 Updated 3 weeks ago
teachskillofskills-ai