PwC Media and Entertainment United States

Seattle Mariners

Marketing Personalization · Real-time Analytics

The Mariners wanted to grow fan engagement and ticket sales, but their marketing still relied on six broad segments, annual survey responses from about 50,000 fans, and disconnected CRM, ticketing, and engagement systems that teams could not easily use for daily decisions.

1.15 million fans tracked across disparate data sources
10%+ uplift in ticket sales expected season-over-season
49 fan microsegments defined- up from six
About 50,000 fans responded

Reported impact

Business outcome

The platform gives the Mariners a unified 1.15 million-fan view, expands targeting from six segments to 49 microsegments, reduces campaign analysis work from days or weeks to minutes, and is expected to drive 10%+ year-over-year ticket sales growth while making outreach more personal and relevant.

  • Customer Experience
  • Productivity Improvement
  • Revenue Growth

Solution

PwC and the Seattle Mariners built Mariners Intelligence, an AI platform on Microsoft Azure that consolidates data from CRM, ticketing, and fan-engagement systems into a unified view of 1.15 million fans. PwC used Claude Code and Azure during delivery, then deployed three machine-learning models that score fan demographics, prior engagement, and propensity to engage so the club could replace six broad segments with 49 microsegments. Anthropic-powered agents sit on top of that data and model layer in an agentic harness with end-user interfaces for marketers and revenue teams. The system analyzes game context, identifies which fans are most likely to attend a specific game, and generates ready-to-review campaign recommendations and draft outreach for email, text, or other preferred channels. Human teams stay in the loop through decision traces and daily operational review.

Data flow

Fan data from CRM, ticketing, and engagement systems is piped into Microsoft Azure and unified into Mariners Intelligence's 1.15 million-record fan view. Three machine-learning models score demographics, past behavior, and propensity to engage; Anthropic-powered agents then interpret those signals, generate campaign recommendations and draft copy, and send outputs to marketing and revenue teams for human review and execution across email, text, and other channels.

Solution architecture

3 components · 3 layers
  1. Compute
    • Anthropic Powers the AI agents that analyze model outputs, generate campaign recommendations, and draft fan outreach.
  2. Serving
    • Mariners Intelligence Provides the internal decision-support application that turns fan data and model outputs into campaign recommendations and daily targeting workflows for marketing and revenue teams.
  3. Uncategorized
    • Microsoft Azure Hosts the data pipelines, unified fan dataset, machine-learning workloads, and deployed agentic harness behind the platform.

Architecture clues

  • Anthropic-powered AI agents run through an agentic harness with end-user interfaces and full decision traces.
  • Outputs can generate recommendations and draft fan outreach for email, text, and other preferred channels.
  • The platform unifies CRM, ticketing, and fan-engagement data on Microsoft Azure.
  • Three machine-learning models use fan demographics, past engagement behavior, and propensity-to-engage signals.

Evidence from the source

It's built with and powered by Anthropic, deployed on Microsoft Azure, and capable of orchestrating AI agents that analyze models and generate campaign recommendations that are ready to execute.
That allowed us to move from six broad segments to 49 actionable microsegments-a game-changer for precision targeting.
Together with PwC, they built Mariners Intelligence-an AI-powered platform that brings more than a million fans into focus, and is designed to turn data into daily, game-by-game decisions.
We expect this to fuel at least 10% growth in our ticket sales year over year.
We used Claude Code and Azure to unify 1.15 million fan records and develop three machine-learning models based on fan demographics, past engagement behavior, and their propensity to engage.
What would've taken our marketing team days or weeks to assemble, Mariners Intelligence is designed to deliver within minutes.
Transparency Evidence & methodology 90/100 reference value · 95% confidence · 2 sources

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value90/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact15/25
    1 metric describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence95%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability25/25
    12 of 12 key fields link to a named source.
  • Direct evidence20/20
    6 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency10/10
    2 source references document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. PwC

    Seattle Mariners AI fan engagement platform: PwC

    First-party
    https://www.pwc.com/us/en/library/case-studies/seattle-mariners-building-ai-platform-to-win-fans-fill-seats.html
    Source type
    Vendor-published customer story
    Published
    Aug 31, 2026
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • Business outcome
    • Metrics
    • Architecture
    • Publication date
    • evidence quotes
  2. Highperformr

    Seattle Mariners: Headquarters, Global Offices & Leadership Team

    Independent secondary
    https://www.highperformr.ai/company/seattle-mariners

    The profile lists “Total employees” as 1080 and says the team is “based in Seattle, Washington.”

    Source type
    Structured company profile
    Supports
    • Company size
    • Region

Date evidence

Not separately sourced Industry. Treat these normalized attributes as lower-confidence until a dedicated source is added.