Unifying the empire
Evoke PLC — Global iGaming & Sports Betting
Evoke PLC emerged from one of the most consequential mergers in the global iGaming industry — the consolidation of multiple independent, billion-dollar betting powerhouses including William Hill and 888 into a single operating entity. Each legacy brand brought its own deeply entrenched technology stack, competing BI systems, and incompatible data models.
The strategic vision was clear: consolidate these formidable brands into a unified, hyper-agile gaming conglomerate capable of dominating regulated markets worldwide. But the technological reality was far more complex. Data silos built over decades of independent operation created a fragmented landscape where even reconciling basic metrics across brands was an exercise in frustration.
The pain behind the numbers.
Post-merger, Evoke's leadership faced a crippling analytical bottleneck. Each legacy brand operated its own BI platform with conflicting KPI definitions, incompatible data models, and competing reporting systems. A single analytical insight cost an average of €600 and could take hours or days to produce — an unsustainable economics for a company that needed to move at the speed of live sports betting.
Management meetings were routinely derailed by conflicting numbers surfaced from siloed systems. Marketing teams in one brand defined "active player" differently from their counterparts in another. Finance could not produce consolidated revenue reports without extensive manual reconciliation. The cost was not just financial — it was strategic paralysis.
Cross-brand analytics was effectively impossible. Data science teams spent the majority of their time on data preparation and reconciliation rather than generating actionable intelligence. The fragmented landscape made it impossible to identify cross-selling opportunities, unified player segments, or consolidated risk profiles.
The solution in practice.
Lognormal — unified semantic layer
Engineered a comprehensive unified semantic layer and Single Source of Truth via Power BI. Eliminated siloed data models and unified KPI definitions across all legacy brands — establishing consistent metrics that every team could trust.
FalconDive — conversational analytics democratisation
Deployed as the democratisation layer with conversational NLP-to-SQL analytics, enabling decision-makers across the organisation to converse with their data directly instead of submitting IT tickets and waiting days for reports.
Cross-brand data science pipelines
Built robust, unified data pipelines enabling data science initiatives that span all brands — making cross-selling analysis, unified player segmentation, and consolidated risk profiling possible for the first time in the merged entity's history.
Self-service analytical fabric
Created an analytical fabric handling 6,000+ daily cross-functional queries seamlessly — from marketing analysts to C-suite executives — without requiring SQL expertise or IT intermediation.
Bottom-line results.
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