# Budget Optimizer

Optimize channel budget with diminishing-returns models.

- Repository: https://github.com/indranilbanerjee/digital-marketing-pro (921 stars)
- Category: Engineering
- License: MIT
- Last updated: 2026-10-29
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add indranilbanerjee/digital-marketing-pro --skill budget-optimizer -g -a claude-code -y`
Codex: `npx skills add indranilbanerjee/digital-marketing-pro --skill budget-optimizer -g -a codex -y`
Cursor: `npx skills add indranilbanerjee/digital-marketing-pro --skill budget-optimizer -g -a cursor -y`
Gemini CLI: `npx skills add indranilbanerjee/digital-marketing-pro --skill budget-optimizer -g -a gemini-cli -y`

## Description

Optimize channel budget with diminishing-returns models. Pacing → budget-tracker. \"is our channel split right\

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# /digital-marketing-pro:budget-optimizer

> **Script location.** If your host does not set `${CLAUDE_PLUGIN_ROOT}`, the scripts are in this plugin's `scripts/` folder, next to `skills/`. Run them with Python 3.10 or newer: `python`, or `python3` where `python` is not found (macOS, many Linux systems).

## Purpose

Data-driven marketing budget optimization across channels using performance data and industry benchmarks. Analyzes current spend efficiency, models diminishing returns per channel, and produces an optimized allocation with projected ROI improvement and a phased reallocation timeline.

## Input Required

The user must provide (or will be prompted for):

- **Current budget by channel**: How spend is distributed today (e.g., paid search, paid social, SEO, email, content, display, affiliate, events, etc.)
- **Performance data by channel**: Key metrics per channel, spend, revenue or conversions, CPA, ROAS, and conversion volume over the measurement period
- **Total budget available**: Overall marketing budget for the optimization period (monthly, quarterly, or annual)
- **Business goals**: Primary objective, maximize revenue, minimize CPA, hit a specific lead or revenue target, balance growth with efficiency
- **Constraints**: Minimum spend requirements, channel mandates from leadership, seasonal considerations, contractual commitments, or platform minimums
- **Measurement period**: Timeframe the performance data covers (last 30, 60, 90 days, or custom range)
- **Attribution model**: How conversions are currently attributed (last-click, first-click, linear, data-driven, or unknown)
- **Seasonality factors**: Upcoming seasonal peaks, promotional periods, or industry events that affect channel performance
- **Historical context**: Whether performance data reflects a typical period or was influenced by one-time events (product launch, viral moment, outage)

## Process

The rest: https://github.com/indranilbanerjee/digital-marketing-pro/blob/HEAD/skills/budget-optimizer/SKILL.md