Growth Marketing resume example

• Designed acquisition campaigns with a defined eligible audience and conversion event; compared cost per activated customer rather than cost per click to avoid buying low-intent traffic.
• Ran experimentation on landing-page friction with predeclared success and guardrail metrics; stopped a conversion variant when it increased sign-ups but reduced completed onboarding.
• Specified experiment eligibility and a primary metric before launch, checked allocation and event loss, and reported the confidence interval and guardrail metrics with the result.
• Built an acquisition and activation experiment with separate new-customer segments, a recorded conversion window and a holdout group; used SQL analysis to distinguish first use from repeat value before expanding spend.
• Configured marketing automation from consented lifecycle events, tested suppression rules for active and unsubscribed customers, and revised message timing after checking delivery failures and downstream activation.
• Owned an acquisition test using audience segmentation and Google Ads holdouts, reduced cost per qualified conversion by 18% with the same attribution window.
• Released marketing-automation rules using event-level analytics, resolved duplicate messaging and documented the demand-generation experiment before expanding campaign spend.

• Launched a reactivation program triggered by product intent and prior value. Kept adoption moving without creating new support or operating load.
• Audited campaign tracking before reporting results, reconciled duplicate conversions across channels, and explained how the attribution window limited the interpretation of return on spend.
• Compared campaign landing pages with the promise in each ad or content placement, corrected inconsistent offers and broken tracking links, and checked the conversion event from a new visitor’s session before resuming spend.

• Modeled payback by channel, segment, and cohort for $1.6 million in quarterly spend
• Built a campaign measurement plan with synthetic spend and conversion records, stated the attribution window and exclusion rules, and checked how duplicate conversions changed the apparent return.
• Compared message variants against the same audience and offer, recorded the decision rule before reviewing results, and wrote a recommendation that distinguished a stronger signal from an inconclusive small sample.
• Owned the simulated campaign analysis using a fixed attribution window, resolved duplicated conversions and completed a sensitivity table separating channel mix from message effects.

Relevant coursework: Financial accounting, statistics, operations management, organizational behavior

• Published an independent campaign note using synthetic funnel data, explaining audience selection, excluded traffic and why an observed conversion change alone does not establish causation.