STUDIO / REFERENCE ARCHITECTURE
A martech reference implementation for sporting organizations
The whole fan-data lifecycle, from raw feeds to activation, running as one governed system.
The fan-data lifecycle
Log in once, scan at the gate, get a governed matchday message, then become the seed for a sponsor's audience extension package. Live backend, synthetic data.
Ticketing, CRM, app, web, and ad-platform feeds landing in one governed foundation.
For your data: Map your real feeds to a single orchestrated ingestion layer; the warehouse stays the source of truth.
One fan resolved across ticketing, app, email, and ad IDs, with provenance retained.
For your data: Deterministic resolution with survivorship rules, so a fan is one person across every system.
Consent states, purposes, and suppression lists, honored before anything activates.
For your data: Privacy-first by construction: suppression overrides inclusion, consent gates eligibility.
One live profile from every source, with field-level provenance, consent by purpose, and the grounding agents need.
For your data: One profile every channel and agent reads, with the rule that won each field on show.
Describe a cohort in plain English or compose it across 16 dimensions and fan-level scores, size it live, read its signature, expand with lookalikes, save and share.
For your data: The everyday segmentation workflow a marketer lives in, on governed first-party data.
Send only consenting fans to Google, Meta or CSV, with the rights matrix, consent and group size checked at send, and every run logged.
For your data: Activation is the missing verb most stacks never close; here it runs from the same surface.
Exposed-versus-holdout lift on a KPI, so a campaign proves it moved the number.
For your data: Measurement that an executive and an agent can both trust because the foundation is governed.
Natural-language audiences and an agent that picks the best audience, offer, and channel.
For your data: Agentic operations land safely once resolution, consent, and lineage are already visible.
The toolkit: start from your problem
We do not know who our fans are
Identity graph and fan profile
First output: One record per real person, with the rule that won each field
Consent is a checkbox, not a control
Consent console and export by purpose
First output: Exports that check consent for their purpose at the moment they run
We cannot prove what a sponsor got
Clean room and measurement
First output: Overlap and lift a sponsor can renew on, with small groups withheld
The board cannot see progress
Board scoreboard
First output: A short set of numbers, each with a direction, a target and a reason
Too many systems and no one owns the feeds
Integration map
First output: Which feeds have a data contract, an owner and a known delay
We do not know what to buy
Club blueprint configurator
First output: A blueprint for your type of club, league or ownership group
The numbers a club board should review, each with a direction, a target and the reason it is there.
The source systems of a composite club: how each one syncs, who owns it, and whether it has a data contract.
Configure a six-layer fan-data blueprint for a club, league, or ownership group.
Dated, sourced martech and adtech findings mapped to each Studio module and roadmap item.
How I would do this for your first-party data
The unglamorous parts are the point: identity resolution with retained provenance, consent that gates eligibility, lineage an executive and an agent can both trust, and activation that honors suppression every time. That is the work most vendors skip and most buyers have been burned by. I lead these as the primary integration partner, from foundations through activation and the operating model around them.
About this Studio
Most fan-data stacks are fragmented: ticketing here, the app there, CRM somewhere else, and ad platforms downstream of all of it. This Studio shows the whole lifecycle resolved into one governed, activated system, using the 4,291 metros of the ranking dataset as a stand-in first-party audience.
Every pattern is real. The consent states, identifiers, scores and destination syncs are synthetic, labeled as such, and included to make governance and activation demonstrable without an NDA. Credibility comes from the patterns being correct, not from faking live integrations.