An anonymised comparison assembled from operator-provided production observations across five labelled platform cohorts. The figures are useful claims to inspect, not industry benchmarks: publication-grade reuse requires dates, denominators, event definitions, comparable traffic, exclusions and reproducible calculations.
Case-reported first-party values. They are not guaranteed outcomes or market-wide benchmarks; see the methodology and evidence limitations below.
No universal industry ranges are used here. Each first-party result has a publication gate that must be satisfied before external comparison or causal attribution.
Revolution Anonymised first-party observations; evidence pack pending. “No Data” means unavailable for that labelled cohort, not zero. Reuse requires cohort dates, denominators, event definitions, traffic provenance, exclusions and reproducible calculations; the table is not an industry benchmark or proof of causation.
The anonymised comparison reports Click2Reg of 59.5% versus 10.9% for one labelled comparison cohort. Without source-matched traffic, event definitions, denominators and a governed export, the gap cannot be attributed to the platform or treated as a portable benchmark.
The first-party comparison reports 170% 12-month ROI with month-five payback for one cohort and −24.3% for another. The evidence pack is pending; spend, CAC, NGR, cost, FX and censoring definitions must match before the values support a comparison.
The labelled cohorts report 4.1 and 2.8 deposits per player in month one. That difference does not establish which product feature caused it; traffic, payment eligibility, bonus treatment, cohort mix and event definitions need to be reconciled first.
The anonymised comparison reports $550 over 12 months for one cohort and $435 for another. Currency, NGR or contribution-margin basis, service costs, forecast method, cohort age and uncertainty must match before the figures inform acquisition limits.
The current table records anonymised first-party claims supplied from operator dashboards. “No Data” means unavailable, not zero. Before the table can function as a benchmark, its governed evidence pack must add cohort dates, brands and sample sizes, metric and revenue definitions, attribution windows, traffic/device mix, exclusions, FX and cost treatment, query or export provenance, uncertainty and anonymisation approval. Until then, do not infer market-wide rank or platform causality.
The three scenarios below are evaluation hypotheses. The first-party table can inform a test plan, but it does not by itself prove why an operator switched or which platform caused an outcome.
Paid and affiliate traffic can differ in intent, device and attribution. The comparison reports 59.5% versus 10.9% C2R for two labelled cohorts, but “same traffic” and registration-flow causality require source-matched cohorts, identical events and controlled evidence. Use the platform-fit guide to design that test.
Withdrawal-to-deposit cash flow, churn and payback require separate definitions and cohort windows. There is no defensible universal 30–40% withdrawal standard or 5–12 month payback rule. Compare player balances, withdrawals, realised contribution margin, retention and protection outcomes under like-for-like periods.
If spend, click volume, traffic quality and attribution are held constant, a C2R difference changes cost per registration mathematically. It still does not establish downstream profitability. Operators should require a governed measurement contract, matched test traffic and cohort contribution margin before platform selection.
There is no defensible universal Click-to-Registration range. One anonymised Turbo Stars comparison reports 59.5% and 10.9% for two platform cohorts. Those are first-party observations, not an industry benchmark or proof that platform UX caused the gap; comparison requires matching click and registration events, attribution, traffic mix, dates, denominators and exclusions.
There is no universal expected ROI. The anonymised comparison reports 170% 12-month ROI and month-5 payback for one Turbo Stars cohort, and -24.3% for a comparison cohort. These first-party results need cohort dates, spend, CAC, NGR and cost definitions, FX, sample sizes, exclusions and a reproducible calculation before publication-grade comparison.
There is no defensible universal Reg2Dep range. The anonymised comparison reports 43.2%, 34.1%, 27.1%, 15.2% and 13.7% across five labelled cohorts. Compare them only after registration, successful-deposit, KYC, payment eligibility, attribution, traffic mix and observation-window definitions are shown to match.
A defensible comparison pre-registers metric definitions and uses source-matched cohorts, identical observation windows, denominators, exclusions and uncertainty. Request Click2Reg, Reg2Dep, realised contribution margin, retention, LTV model assumptions and payback, then reconcile each figure to a governed source export. Production origin alone does not remove selection or measurement bias.
Within the anonymised first-party table, the Turbo Stars-labelled cohort has the highest reported values where comparison data is available: Click2Reg 59.5%, Click2Dep 16.8%, Reg2Dep 43.2% and month-one ARPU $110. This does not establish a market-wide best result or platform causality until comparable cohorts and the full evidence pack are available.
Payback depends on spend, CAC, realised contribution margin, cohort retention and the accounting definition. This comparison reports month-5 payback and month-one ROAS above 110% for one Turbo Stars-labelled cohort, and month-6 payback for one comparison cohort. Treat these as first-party case observations pending reproducible inputs, not an expected platform outcome.
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