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● Performance Marketing · Analytics Infrastructure · Measurement
Most campaigns scale noise.
I build systems that measure
what actually drives growth.
I’m Sarthak — a marketer who works where paid media meets measurement. My work starts from a simple premise: you cannot optimize what you cannot see. I handle Meta and Google campaigns, analytics infrastructure, and structured experimentation — so decisions come from signal, not from timing coincidences dressed up as attribution.
3+
Years running paid media
across Meta & Google
across Meta & Google
6
Custom behavioral signals
engineered for intent tracking
engineered for intent tracking
7
Stage measurement cascade
from content view → purchase
from content view → purchase
0
Campaigns optimized on
coincidence-as-attribution
coincidence-as-attribution
01
// Problems I Solve
You’re scaling campaigns on broken attribution
Traffic spikes. Revenue bumps. You call it the campaign. It might be seasonality, organic momentum, or a coincidence with good timing. Without proper measurement architecture, you’re optimizing guesses.
↳ GA4 + GTM custom event taxonomy · CAPI implementation · Lift studies
Paid media performs until it doesn’t — and nobody knows why
You’ve found a creative that works. ROAS looks good. Then performance decays and the team is back to guessing at new angles. The problem is structural: no experimentation framework to isolate what actually moved the needle.
↳ Structured A/B testing · Creative experiments · Meta lift studies
Your analytics stack illuminates the last click. Nothing else.
Standard GA4 shows page views, add-to-cart, purchase. The behavioral territory between entry and conversion — where most of the real persuasion happens — is invisible. You’re navigating on 20% of the available signal.
↳ Behavioral event framework · Intent scoring · Ghost lead detection
02
// How I Work
01
Diagnose the measurement layer first
Before touching campaign structure or creative, I audit what the analytics stack is actually capturing. Most performance problems are measurement problems wearing a campaign costume.
GA4 · GTM
Tag audit
Event taxonomy
Tag audit
Event taxonomy
02
Build the infrastructure for real decisions
Clean tracking. Proper CAPI integration. Custom behavioral signals where standard events don’t capture intent. The goal is a measurement stack that tells the truth, not one that flatters the campaign.
CAPI · Pixel
Custom events
GTM logic
Custom events
GTM logic
03
Run campaigns with discipline, not instinct
Meta and Google campaigns managed against clear hypotheses — not vibes. Structured creative experiments. Controlled variable isolation. Results documented so the learning compounds, not evaporates.
Meta Ads
Google Ads
A/B testing
Google Ads
A/B testing
04
Optimize what the data actually says
With measurement in place, optimization becomes a different discipline. You stop asking “which creative looks good” and start asking “which behavioral pathway precedes a purchase.” That’s where compounding begins.
Reporting
Iteration
LTV analysis
Iteration
LTV analysis
/ RAW FIELD NOTES
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Initializing sequence…
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