Gainbridge: Product Manager, Data and Measurement

Built the instrumentation layer that made performance trustworthy — before optimization.

Data ArchitectureMeasurement StrategyEvent TaxonomyIdentity ResolutionAttribution Systems

Challenge

New leadership shifted focus to profitability and CAC reduction
Siloed optimization: teams optimized local KPIs with no shared funnel definition
Unclear event definitions/timing broke performance analysis across tools
Data quality + tool confusion eroded trust in dashboards and attribution
No end-to-end journey: discovery/consideration were invisible and attribution started too late

Stepped in as de facto owner for data architecture and measurement
Partnered with marketing, data engineering, product, and operations
Audited tooling, pipelines, and dashboards end-to-end
Translated technical findings into business implications and demos for leadership
Mandate: build a foundation that makes CAC reduction operational, not theoretical

systems thinking → tooling audit → taxonomy freeze → identity architecture → attribution proof

Reframed growth as a systems problem

Started from decisions we needed to make, then worked backward to the signals required and where the system lost them.

Clarified what each tool actually did

Mapped the stack (Segment, GA4, FullStory, Braze, Pendo, Snowflake, ad platforms) and made contracts explicit.

Paused event expansion until definitions were fixed

Stopped “add events now, figure it out later” to prevent schema debt and bad data being operationalized.

Designed an identity-first architecture

Rebuilt around Segment for identity/routing, Snowflake as system of record, FullStory for pre-enrollment behavior.

Proved value with a concrete attribution model

Built a starter multi-touch model and walked leadership through real journeys from first ad click to funding.

CAC discussions moved from opinion to evidence by grounding debate in reliable signals
Leadership aligned on data clarity as a prerequisite to profitability work
Marketing and product shared a unified end-to-end journey model
Activation strategies (suppression, re-engagement, bidding) became possible with confidence

Growth metrics are meaningless without lifecycle context
Most analytics problems are definition + ownership failures, not tooling failures
Pausing instrumentation can unlock more value than adding it
A data PM’s job is to prevent bad decisions from scaling

Growth Strategy (One-pager)
Built the decision infrastructure behind D2C growth by aligning acquisition, education, and attribution around behavioral signals
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Customer Journey × Data Flow Architecture
Connected customer journeys to data flows to surface identity fragmentation and delayed activation caused by partial attribution and unclear customer profiles.
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Attribution Starts Before Conversion
Reframed attribution as an identity and data-visibility problem, not a reporting problem.
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