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Salesforce Media and Entertainment Global

LIV Golf

Marketing Personalization

How LIV Golf is using Agentforce and Data 360 to bring fans closer to every swing. Why Nick Connor, SVP of Technology, chose Salesforce to connect data, AI, and fans – bringing richer stories, deeper context, and immersive experiences to viewers worldwide.

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How LIV Golf is using Agentforce and Data 360 to bring fans closer to every swing.

Reported impact

Business outcome

Reported outcomes include How LIV Golf is using Agentforce and Data 360 to bring fans closer to every swing..

  • Customer Experience
  • Revenue Growth

Solution

LIV Golf built its fan engagement roadmap on Data 360 so it could understand supporters across every physical and digital interaction before scaling agentic experiences. The platform unifies signals from ticket scans, RFID hospitality access, credit-card purchases for food and merchandise, streaming and article consumption, loyalty and fantasy programs, and sport-performance data such as player and shot information. With that shared profile in place, Agentforce becomes the conversational layer that can respond with richer context, personalize messages, and help fans discover stories, teams, and moments that match how they engage with the league. The design is intentionally real-time: as new tournament, retail, and engagement signals arrive, Data 360 refreshes the profile and makes those signals available for fan messaging, merch offers, and interactive experiences that feel closer to the action whether the fan is onsite or following highlights later.

Data flow

Ticketing, hospitality, commerce, streaming, content, loyalty, fantasy, and on-course performance data feed Data 360, which builds a live fan profile that Agentforce uses to power personalized fan interactions and content responses.

Solution architecture

2 components · 2 layers
  1. Storage
    • Data 360 Unifies enterprise and behavioral data so teams can turn unified fan data into personalized fan engagement and content with current context.
  2. Orchestration
    • Agentforce Runs the AI agent workflows that turn unified fan data into personalized fan engagement and content.

Architecture clues

  • Data 360 is used as the foundational fan profile before agent rollout.
  • The data model expanded with a 72-hole format that created more shots, swings, and story moments to activate.
  • The unified profile combines fan, player, sponsor, and operational data in near real time.

Evidence from the source

Building Two-Way Fan Engagement With AI
How LIV Golf is using Agentforce and Data 360 to bring fans closer to every swing.
Why Nick Connor, SVP of Technology, chose Salesforce to connect data, AI, and fans – bringing richer stories, deeper context, and immersive experiences to viewers worldwide.
Transparency Evidence & methodology 81/100 reference value · 92% 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 value81/100
  • 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 specificity16/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact15/25
    1 metric describe measurable impact.
  • Deployment scale5/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence92%
  • Source authority25/25
    The deployment is described by the adopting organization or a government source.
  • Claim traceability23/25
    11 of 12 key fields link to a named source.
  • Direct evidence15/20
    3 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency9/10
    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. Salesforce

    LIV Golf customer story

    First-party
    https://www.salesforce.com/customer-stories/liv-golf-nick-connor-interview/
    Source type
    Vendor-published customer story
    Published
    Feb 6, 2026
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date
  2. Companies House

    Group of companies' accounts made up to 31 December 2024

    Government
    https://find-and-update.company-information.service.gov.uk/company/13473438/filing-history/MzQ4MjkzMzA4MmFkaXF6a2N4/document?format=pdf&download=0

    The filing’s staff-costs note shows average monthly persons employed in 2024: Administration 83, Event staff 4, total 87.

    Source type
    Government filing
    Supports
    • Company size

Date evidence

  • Published on source page Feb 6, 2026 · Salesforce · First-party
    Open date source
Not separately sourced Industry, Region. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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