Modern Attribution & Incrementality Stack
by Yuriy Timen • Growth Advisor (Former Head of Growth at Grammarly) at Independent Advisor (Ex-Grammarly)
Yuriy Timen spent over 8 years leading growth at Grammarly, helping scale it into a household name. He now serves as a full-time advisor to high-growth subscription companies like Canva, Airtable, Otter.ai, and Flo Health.
🎙️ Episode Context
In this tactical deep dive, Yuriy Timen breaks down growth strategies for B2C and B2B subscription products. He discusses how to choose between Paid, Viral, and SEO channels based on business models, the shifting landscape of attribution in a post-iOS14 world, and why 'growth at all costs' is being replaced by efficiency.
Problem It Solves
Solves the 'blindness' caused by iOS14 and privacy changes where tracking pixel data is no longer reliable.
Framework Overview
Moving from deterministic tracking (cookies/clicks) to probabilistic modeling and causality testing to measure marketing effectiveness.
🧠 Framework Structure
Reject Last-Click Reliance: Acknowled...
Media Mix Modeling (MMM): Use statist...
Incrementality Testing: Run randomize...
When to Use
When annual marketing spend exceeds ~$1M or when using hard-to-track channels like Podcasts, TV, or TikTok.
Common Mistakes
Cutting efficient channels (like YouTube) because they look bad on 'last click' reports, or over-investing in attribution tools too early.
Real World Example
Using tools like Recast (MMM) or Measured (Incrementality) to justify spend on Podcasts or Out-of-Home ads.
The only way to determine causality is through real controlled experiments... incrementality testing.
— Yuriy Timen