Cross-operator betting/gaming player-lifecycle dataset

Cross-operator betting/gaming player-lifecycle dataset: multi-touch marketing-journey records (paid media on Meta/Google/TikTok, performance/affiliate partners, native app) joined to downstream player monetisation — deposits, micro-transactions scattered across platforms, net gaming revenue accrual over months-to-years, retention and reactivation events, and 72-hour predictive lifetime-value scores. Trained on 'billions of first-party data points' and 'years of player data' pooled across tier-1 operators, segmented by US state/region.

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Coverage

Universe, instruments and categories.

Industry: Application SoftwareCasino and Gaming
Instruments: equities
Categories: AlternativeSentimentFundamental
Regions: USUKAPAC
Sample tickers: DKNGFLUTRBLXGANEGLEEGBNPUBM.LLVS

Dataset card

Type: not stated
Format: Tabular event/join data (marketing touchpoint × player × revenue outcome) plus model outputs (predictive LTV scores, attribution weights); delivered as SaaS analytics dashboards
Volume: 'Billions of first-party data points' explicitly stated as the training corpus for its LTV/attribution AI, spanning years of player data across multiple tier-1 operators and all major paid-media channels.
Users: N/A — B2B analytics SaaS, no registered-user base of its own; the population it measures is end-player cohorts belonging to its operator customers. Player journeys processed run to billions of first-party data points (page-stated).
History: 5 years
Update frequency: not stated
Growth: Active — site assets dated mid-2026, refreshed product messaging around AI/LLM-trained attribution, and a live SVP Revenue & GTM hire driving commercial expansion into the regulated US sports-betting market.
Launched: ~2015-2017 (company record predates 2016; the platform's marketing-attribution product predates the current US sports-betting wave)
Delivery: not stated
Entity mapping: not stated
Sample: not stated
Point-in-time: not stated
Licence: not stated

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