Business intelligence case study
iGaming KPI Dashboard
A decision-focused analytics experience connecting acquisition, player activity, revenue, retention and safer-gambling signals in one executive view.
Interactive overview
Executive performance cockpit
Change the period and market to explore the reporting scenario. Comparisons use the preceding equivalent period.
Daily net gaming revenue
90-day trend · all markets
Period movement+12.4%
GGR by product
Selected period contribution
€8.42Mtotal GGR
First-time depositors by channel
Volume and relative acquisition mix
Player wellbeing signals
Operational monitoring · not a clinical assessment
Deposit limits enabledShare of monthly active players28.4%
Reality checks usedSession reminder interaction rate14.7%
Review queueRule-based flags awaiting review126
90 days · All markets
Retention analysis
Monthly player cohorts
Each row follows a first-deposit cohort. Values show the share returning in each subsequent month.
| FTD cohort | Players | M0 | M1 | M2 | M3 | M4 | M5 |
|---|---|---|---|---|---|---|---|
| Jan 2026 | 4,280 | 100% | 46% | 38% | 33% | 29% | 27% |
| Feb 2026 | 4,610 | 100% | 48% | 39% | 34% | 30% | — |
| Mar 2026 | 4,940 | 100% | 51% | 42% | 36% | — | — |
| Apr 2026 | 5,180 | 100% | 53% | 43% | — | — | — |
| May 2026 | 5,420 | 100% | 55% | — | — | — | — |
| Jun 2026 | 5,760 | 100% | — | — | — | — | — |
LowerHigher retention
From metrics to action
Stakeholder insights
Hypotheses are separated from observations so decisions are not presented as proven causality.
Casino growth leads the period
Slots and live casino contribute 73% of GGR, while period NGR increases 7.2% against the previous comparable window.
Next stepValidate whether the lift is broad-based or concentrated in a small player group.
Onboarding may be improving
Later cohorts retain more strongly at M1. This could reflect campaign quality, product changes or seasonality; the dashboard alone cannot prove why.
Next stepRun a controlled cohort comparison by channel, market and welcome journey.
Balance growth with wellbeing
Commercial metrics are paired with limit adoption, reality-check use and review volume to keep safer-gambling monitoring visible.
Next stepReview alert service levels and segment exposure before scaling campaigns.
Build approach
From warehouse to decision
The case study models a repeatable BI workflow: define event grain, validate player and transaction keys, aggregate reusable daily facts, then expose governed KPIs to an executive layer. Real implementations would add role-based access, privacy controls, lineage, alert ownership and tested refresh SLAs.
SQLPython QATableauStar schemaData quality tests
01
Ingest and validate
Check event completeness, currency mapping, duplicates, timestamps and player identifiers.
02
Model the analytical grain
Build daily player-product facts linked to date, market, channel and product dimensions.
03
Define governed metrics
Document GGR, NGR, FTD conversion and retention with aligned filters and ownership.
04
Deliver and monitor
Publish the dashboard, test access, track refresh health and investigate material variance.
Continue exploring
Want to discuss the analysis?
I can walk through the KPI definitions, data model, dashboard decisions and how this concept could translate to a governed production workflow.