4+ years analyzing paid media performance, customer lifecycle behavior, and channel
attribution across Google, Meta, Amazon, Email, and GA4 — and translating those insights
into dashboards, reports, and recommendations that help marketing teams spend smarter.
Marketing Analytics
Voice of Datafor Marketing and Business Stakeholders
📊
Campaign Performance Analysis
I track, report, and optimize paid media performance across Google, Meta,
Amazon, and email — building dashboards and analyses that show what is working,
what is not, and where to move budget.
🎯
Attribution and Channel Measurement
I connect the dots between ad spend and revenue using attribution
modeling and incrementality analysis — so teams stop crediting channels that are
not actually driving conversions.
👥
Customer and Lifecycle Analytics
I analyze funnel performance, cohort retention, and customer
value to help teams understand who their best customers are and how to acquire and
retain more of them.
What platforms report vs. what actually drives revenue
Last-click attribution systematically over-credits bottom-funnel channels
and buries the channels doing the real work. This is the gap made visible.
Platform reported
True contribution
Google
▼ 2.8x — OVERSTATED
4.9x
platform
2.1x
true
↳ Overstated — budget redirected to higher-performing channels
Meta
▲ 1.3x — VALIDATED
4.8x
platform
6.1x
true
↳ Validated — scaled with confidence
Email
▲ 6.8x — UNDERVALUED
1.2x
platform
8.0x
true
↳ Undervalued in last-click — reallocated budget here
+18.4%
Revenue uplift projected
Same total budget. Smarter channel allocation.
Built at Baz Bros Wholesale Vintage Apparel
Work Project
AttributeIQ
Built in-role to solve a real attribution gap. Three models run side by side
across Google, Meta, and Email — Claude narrates where they disagree and
translates the delta into a concrete budget recommendation.
3
Attribution Models
4
Channels Tracked
$34.2K
Budget Reallocation
Claude API
AI Narration
Attribution Share by Model — Where Models Disagree
Google
Meta
Email
LAST-CLICK
58%
31%
11%
LINEAR
33%
34%
33%
TIME-DECAY
24%
38%
38%
± RANGE
±34pp
±7pp
±27pp
↳ Large swing = budget decision hiding in plain sight
✦ Claude AI Narration Output
"Email shows the largest model disagreement: Last-Click assigns 11% attribution share vs. 38% under Time-Decay — a 27 percentage-point swing.
This gap exists because Email primarily assists conversions upstream, which Last-Click ignores entirely.
At current spend levels, Email is likely under-credited by ~$18K.
Recommend shifting budget from Google branded to Email and Meta prospecting."
Built attribution reporting and campaign dashboards across Google, Meta, and Amazon.
Automated weekly performance reporting, reducing analysis time from hours to minutes and enabling faster
budget decisions.
Ran channel attribution and incrementality analysis revealing significant ROAS
overstatement in Google Display. Delivered media mix analysis projecting 18.4% revenue uplift from
budget reallocation without increasing total spend.
Analyzed customer lifecycle and funnel performance, uncovering a significant LTV gap
between segments. Redesigned targeting and email flows based on cohort behavior, achieving 4.8x Meta
ROAS and 30% online revenue lift.
