Definition
Click-to-Registration (C2R or Click2Reg) is the percentage of eligible attributed advertising clicks that result in a completed registration within a stated observation window. It is a useful paid-acquisition metric, but it does not measure deposit quality, revenue or profitability.
Formula: C2R = (Completed attributed registrations ÷ Eligible attributed clicks) × 100%
Evidence-safe comparison
| Control | What must match | Why it matters |
|---|---|---|
| Traffic | Source, campaign, device, market tier and bot filtering | Prevents mix and invalid-traffic bias |
| Attribution | Click identity, window, deduplication and cross-device policy | Keeps numerator and denominator connected |
| Registration | Start and completion events, consent, KYC and verification rules | Prevents unlike funnel endpoints being compared |
| Outcome | Deposit, NGR, retention and player-protection measures | Tests quality and economics beyond registration |
An anonymised Turbo Stars case reports 59.5% C2R and comparison observations of 10.9% and 6.66%. These are first-party case figures, not market benchmarks. A publication-grade comparison requires dates, click and registration counts, traffic equivalence, event definitions, exclusions and source-system evidence; see the results page for the current claim context.
Why it matters: the compounding effect
As arithmetic, 59.5% versus 10.9% on the same 1,000 eligible clicks would produce 595 versus 109 registrations. That does not prove a platform caused the difference: campaign, market, device, filtering, attribution and event rules must also match.
Likewise, at an illustrative $100,000 spend and $0.50 CPC, 200,000 eligible clicks would yield 119,000 or 21,800 registrations at those respective rates. This scenario holds spend, click quality and measurement constant; real profitability still depends on deposit conversion, NGR, retention, compliance and servicing cost.
What drives C2R improvement
- Instrument the full funnel: validate click, landing, start, validation-error and completion events before changing UX.
- Test mobile flows: compare variants within the same eligible traffic; a PWA or shorter form is a hypothesis, not a universal uplift.
- Follow KYC and consent rules: timing and required fields are set by the relevant licence, AML and privacy obligations, not solely by conversion.
- Measure performance: use real-user and step-level evidence to connect load or interaction delays with abandonment.
- Keep campaign and page terms consistent: verify the offered terms and measure whether a controlled correction changes completion.
Related evidence: first-party results context → | SOFTSWISS alternative analysis →
Common questions
What is a good Click-to-Registration rate for a casino?
There is no defensible universal range. C2R changes with channel, campaign, device, market tier, consent and KYC flow, bot filtering, attribution window and registration event. Compare like-for-like cohorts against an internal baseline. One anonymised Turbo Stars case reported 59.5%, but that first-party observation is not an industry benchmark and needs its denominator, sample size and event definitions.
Why does Click-to-Registration matter?
C2R links attributed traffic with completed registrations. If the rate doubles while click volume, spend, filtering and attribution remain identical, cost per registration is mathematically halved. It does not establish traffic quality, deposit conversion, profitability or platform causality, so read it with downstream cohort outcomes.
What can cause low Click-to-Registration rates?
Possible causes include measurement changes, invalid traffic, page performance, device-specific UX, form errors, campaign-to-page mismatch, verification failures and legally required KYC or consent steps. Diagnose the step-level funnel and session evidence before assigning a cause. KYC timing must follow the applicable licence and AML obligations, not a conversion target.
How is Click-to-Registration calculated?
C2R = completed attributed registrations divided by eligible attributed clicks, multiplied by 100. State the attribution and observation windows, deduplication, invalid-click exclusions and exact completion event. Split by source and device only when those definitions remain identical.