Cohort Analysis — iGaming GlossaryCohort analysis groups iGaming players by a shared start event (usually FTD month) and tracks their behaviour over time to measure retention, LTV, and acquisition quality.

Cohort Analysis

**TL;DR:** Cohort analysis groups iGaming players by a shared start event (usually FTD month) and tracks their behaviour over time to measure retention, LTV, and acquisition quality.

What it means

A cohort is typically defined by FTD month, country, and acquisition source. Operators then watch metrics like Day 1, Day 7, Day 30, and Day 90 deposit retention, cumulative NGR, and active days. Cohort views are how BI teams answer "is this month's intake better than last month's?" — a blended KPI cannot.

Cohort analysis is also the backbone of CFO-grade UA decisions: payback period, LTV/CAC ratios, and channel-level economics only make sense at the cohort level.

Formula / How it's measured

For each cohort C defined at time t₀: Metric(C, t) = aggregate of metric across players in C measured at age t (days/weeks/months since FTD).

Example: Cohort = March 2026 FTDs in MX from affiliate channel A (n=2,400). Day 30 deposit retention = 28%. Day 90 cumulative NGR per player = $42. Compared to Channel B March cohort: 41% / $68 — Channel B is materially better despite higher CPA.

Why it matters for operators

Cohort analysis is the only honest way to compare acquisition channels, bonus structures, product launches, and CRM programs. Without it, growth teams chase blended KPIs that move for compositional reasons (mix shifts) rather than real performance changes.

Common benchmarks (2026)

Casino Day 30 deposit retention: 18%–35%
Sportsbook Day 30 deposit retention: 22%–42% (sport season dependent)
Day 90 cumulative NGR per FTD, casino LATAM: $30–$80
Day 90 cumulative NGR per FTD, sportsbook US: $80–$220
Payback period, healthy operator: 3–9 months