Paid Ad Funnel Optimization
Rebuilt a multi-channel paid funnel and its attribution model — cutting ad spend 60% while growing revenue 42% and lifting blended ROAS to 4×.
From fragmented spend to a clean growth engine.
The business was spending aggressively across Meta and Google, but fragmented ad accounts and broken UTM tracking meant no one could say which channels actually produced customers. Spend was climbing faster than revenue, and budget decisions were guesswork.
I consolidated the accounts into a single, UTM-clean attribution model, then pruned the bottom-quartile audiences and reallocated budget strictly by ROAS — scaling retargeting and lookalikes while cutting wasted top-of-funnel spend. Reporting moved from vanity metrics to cost-per-customer and contribution.
- Consolidated fragmented ad accounts into one clean attribution model
- Rebuilt the UTM taxonomy → trustworthy source / medium reporting
- Cut bottom-quartile audiences; reallocated budget strictly by ROAS
- Scaled retargeting + lookalikes; killed wasted top-of-funnel spend
What changed, measured.
Spend, efficiency and conversion across the program. Figures are sanitized and indexed — trajectories are illustrative; the endpoints are the exact, verified outcomes.
Spend down, revenue up
Both indexed to 100 at program start
Blended ROAS reached 4×
Return on ad spend over the program
Cost per customer
Indexed CAC, declining
Contact → lead → customer
≈ 51K paid-social contacts tracked
≈ 7% contact-to-customer at peak — efficient spend compounds down the funnel.
UTM attribution
Share of tracked contacts by source / medium
Net result: ad spend down 60%, revenue up 42%, blended ROAS at 4×, and $500K+ in attributed revenue impact across ≈ 51K tracked paid-social contacts.