BFCM Measurement Framework 2025
πŸ“Š Pre-BFCM (October): Get Your Baseline
  • Run MMM to understand your saturation curves
  • Pick ONE channel you're suspicious about (we chose branded search)
  • Test it in 15% of geos for 2 weeks
  • Finding: Only 10% incremental at normal spend β†’ likely 2% during BFCM
Here's the key: Use October findings to optimize BFCM in real-time:
  • Branded search barely incremental? β†’ Cap it at 1x while others scale
  • Found your breaking point at 2x spend? β†’ Don't chase 3x vanity metrics
  • Retargeting only 15% incremental? β†’ Reduce frequency from 10x to 3x
  • That's $300K saved to reallocate to channels that actually drive growth
πŸš€ During BFCM: Embrace the Chaos (Strategically)
Two approaches that don't hurt revenue:
Option 1: Natural experiments Your budget caps, geo differences, and inventory constraints create natural tests. Use them.
Option 2: Positive scale test 80% of geos: Normal 3x scaling 20% of geos: Aggressive 5x scaling Compare the incremental difference
πŸ“ˆ Post-BFCM: Connect the Dots
Compare your elasticities:
  • October baseline: 0.25
  • During BFCM: 0.08
"But what if we miss revenue by testing?" Fair concern. That's why we suggest positive scale tests or using natural variance. No revenue loss.
"This seems complex during our busiest season" It's really just 3 analyses: October MMM, BFCM documentation, December comparison. Plus, October tests give you a real-time playbook - not more work, just smarter decisions.
"How do we know this applies beyond BFCM?" BFCM is like a stress test for your marketing. The patterns you discover apply to every promotion, product launch, and peak period.
The Bottom Line:
You're going to spend millions during BFCM anyway. Why not know which parts actually work AND optimize while you're spending?
Pre-BFCM tests aren't just measurement - they're your optimization playbook. Same effort, 30-40% better efficiency.
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Vinay K
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BFCM Measurement Framework 2025
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