Budget Allocation Optimizer

Pro v1.0.0 1 view

Analyze historical marketing channel performance and get actionable budget reallocation recommendations to maximize ROI.

What You Get

Get data-driven recommendations to optimize your marketing budget across channels. Analyzes 3-6 months of historical performance data to identify underperforming channels and recommend specific reallocations that maximize total ROI.

The Problem

Marketing teams struggle to allocate budgets across channels optimally. Without systematic analysis of historical performance, budgets often remain static even when channel efficiency changes, leading to wasted spend on underperforming channels and missed opportunities to scale high-performers. Teams need clear, data-driven guidance on where to shift budget to improve overall marketing efficiency.

The Solution

This skill analyzes historical ROI/ROAS data across marketing channels over 3-6 months, assesses data quality to ensure confident recommendations, normalizes metrics for fair comparison across different channel types, ranks channels by cost efficiency, identifies optimization opportunities (underperformers and budget mismatches), generates specific reallocation recommendations with conservative and aggressive scenarios, estimates expected impact on conversions and blended metrics, and transparently documents all assumptions and limitations. The output includes efficiency rankings, specific dollar-amount recommendations, multiple scenarios with confidence levels, expected impact projections, implementation timelines, and honest documentation of what the analysis doesn't account for.

How It Works

  1. 1 Assess data quality and determine if sufficient for confident recommendations (minimum 3 months, ideally 6+ months)
  2. 2 Normalize metrics across channels for fair comparison (convert to common metric like CAC or ROAS)
  3. 3 Calculate channel efficiency metrics and rank channels by performance
  4. 4 Identify optimization opportunities (underperformers, top performers, budget mismatches)
  5. 5 Generate specific reallocation recommendations with conservative and aggressive scenarios
  6. 6 Estimate expected impact on key metrics with confidence levels adjusted for data quality
  7. 7 Document assumptions, limitations, and factors not accounted for
  8. 8 Create phased implementation timeline with monitoring plan

What You'll Need

  • Historical performance data for 2+ marketing channels (minimum 3 months, ideally 6 months)
  • Monthly spend amount for each channel
  • At least one outcome metric per channel: conversions, revenue, CAC, ROAS, CPA, or leads
  • Current monthly budget allocation

Get This Skill

Requires Pro subscription ($9/month)

Have Feedback?

Help us improve this skill by sharing your ideas and suggestions.

Request Improvements

Examples

B2B SaaS Multi-Channel CAC Optimization

Analyzes 6 months of performance across Google Ads ($180 CAC), Facebook ($290 CAC), and LinkedIn ($520 CAC) for a B2B SaaS company. Demonstrates clear efficiency ranking, identifies LinkedIn as severe underperformer (2.9x more expensive than Google), and recommends reallocating $7K-$11K to Google Ads. Shows how to improve total conversions by 12-29% while reducing blended CAC by 12-25%. Includes conservative and aggressive scenarios with confidence-adjusted projections.

View example

E-commerce ROAS-Based Channel Reallocation

Evaluates 5 months of e-commerce marketing data using ROAS metrics: Facebook 3.2x, Google Shopping 5.8x, TikTok 1.9x. Identifies Google Shopping as severely underfunded (33% of budget despite 5.8x ROAS) and TikTok as underperformer (1.9x ROAS consuming 22% of budget). Recommends shifting $10K-$18K to Google Shopping from TikTok and Facebook. Projects 24-47% revenue increase and blended ROAS improvement from 3.78x to 4.65x-5.20x. Demonstrates handling of ROAS metrics vs CAC and provides detailed scaling guidance for each channel.

View example

Small Budget Lead Generation Optimization

Analyzes 3 months of data (minimum threshold) for a small $6.5K/month budget across SEO, PPC, and email marketing using lead-based metrics. Identifies email as severely underfunded ($500/mo generating leads at $63 CPL - 56% better than average) while PPC is overfunded ($4K/mo at $182 CPL). Demonstrates proper handling of limited data by adjusting confidence levels (60-70% vs typical 75-85%) and providing conservative recommendations. Shows operational guidance on what to do with reallocated budget (hiring email marketer, content creation). Includes rollback triggers and risk mitigation specific to small budgets.

View example
View all examples