TOP-10 metrics a casino marketer should know

Introduction: metrics = language of money and quality

Casino marketing is measured not by clicks but by money and valid conversions. Basic principle: count metrics on a cohort basis (by date of FTD/registration), in UTC, in the currency of the report, and by NGR (net gaming revenue), and not by GGR. Below are ten metrics without which it is impossible to manage growth and payback.

1) CR (click → registration)

What is it: the proportion of clicks that have completed registration.

Formula: 'CR_c→r = Registrations/Clicks'.

Why: reflects the relevance of traffic and the "announcement ↔ landing" correspondence.

How to act: improve speed/UX landing, offer parity, localization.

Pitfalls: high CR with further failure can mask fraud/incident.

2) CR (registration → KYC)

What is it: the proportion of registered, verified.

Formula: 'CR_r→kyc = KYC Approved/Registrations'.

Why: real user willingness to play, onboarding quality and UX KYC.

How to act: cut extra fields, show understandable requirements and ETA, support 24/7.

Pitfalls: too soft KYC will worsen the risk profile and lead to chargebacks.

3) CR (KYC → FTD)

What is it: the proportion of verified who made the first deposit.

Formula: 'CR_kyc→ftd = FTD/KYC Approved'.

Why: The quality of the source/creative and the strength of the start-up onboarding/payments.

How to act: local payment methods, transparent bonus conditions, fast tutorials.

Pitfalls: artificially overclocking FTD at the cost of an aggressive bonus breaks the D30 economy.

4) 2nd-deposit rate

What it is: The proportion of FTD users who have made a second deposit.

Formula: '2nd _ dep _ rate = Users_with_2nd_dep/ Users_with_FTD'.

Why: An early indicator of traffic quality and future ARPU/LTV.

How to act: missions/calendar, honest promotional economy, personal RTP-independent values (service, tournaments).

Pitfalls: count according to the FTD cohort, not the calendar, otherwise the signal is blurred.

5) Retention D7 / D30

What is it: the proportion of players returning/active on D7/D30 day.

Formula (cochort): 'Retention _ Dn = Active_on_day_n/ Cohort_size'.

Why: LTV foundation; shows product value and CRM.

How to act: content calendar, tournaments, segmented fluffs/e-mail, responsible frequency ceiling.

Pitfalls: don't mix different GEO/payment methods - strong differences.

6) ARPU D7/ D30/D90 (on NGR)

What it is: Average net income per user for the period.

Formula: 'ARPU _ Dn = NGR_Dn/ Users_in_cohort'.

Why: The main entrance to Payback and LTV allows you to compare sources.

How to act: improve payment conversions, cohorts of VIP service, reduce fraud/refands.

Pitfalls: Count NGR (after bonuses/fees/taxes), not GGR.

7) Payback (payback day)

What it is: The day the accumulated NGR on the cohort equaled the cost.

Formula: 'Payback = min {n: Cum_ARPU_Dn ≥ CPA}'.

Why: Decides whether the bundle can be scaled.

How to act: work on CPA/creatives, geo-mix, optimization of pacing.

Pitfalls: Don't confuse CPA (total cost of attraction) with CPL/click-price.

8) LTV (90/180/365 horizon)

What it is: The expected NGR amount from the player over the horizon.

Formula (discounted):

'LTV = Σ_t NGR_t/( 1 + r) ^ (t/30) ', where t is the days, r is the monthly discount rate.
Why: strategic budget allocation, VIP planning.
How to act: VIP-segmentation, service, retention, secure personal offers.
Pitfalls: Don't align LTVs of different markets of the same curve - different behavioral tails.

9) ROAS/ROI (on NGR)

What it is: A return on advertising spending.

Формулы: `ROAS_Dn = NGR_Dn / Spend`, `ROI_Dn = (NGR_Dn − Spend) / Spend`.

Why: A rigorous assessment of channel performance.

How to proceed: budget transfer from low to high ROAS while maintaining quality (2nd-dep/Retention).

Pitfalls: compare on the same horizon (for example, D30) and cohorts.

10) Chargeback/Refund & Fraud rate + Approval rate (compliance package)

What is it: the share of returns/chargebacks/fraud and the share of approved ads.

Formulas:

`Chargeback_rate = Chargebacks / FTD`, `Fraud_rate = Fraud_flagged / Registrations`, `Approval_rate = Approved_ads / Submitted_ads`.
Why: The health of the economy and access to inventory.
How to act: anti-fraud (IP/ASN/velocity, device), transparent bonus language, Responsible Gaming, creative/landing page review.
Pitfalls: High Approval rate without traffic quality is an illusion of victory.

How to count everything correctly (short data frame)

События S2S: `registration`, `kyc_approved`, `ftd`, `second_deposit`, `refund/chargeback`.

Units: UTC time, idempotency by 'event _ id', report currency + exchange rate table for the date.

Cohorts: by FTD/enrollment date; comparison - only on an equal horizon (D7/D30/D90).

Privacy/compliance: Responsible Gaming, 18 +/21 +, no PII in the URL, parity "ad ↔ landing."

Common mistakes and how to avoid them

1. Click/EPC score instead of NGR/Payback/LTV → false winners.

2. Mixing GEO/payments in one report → "average hospital temperature."

3. GGR instead of NGR → inflated ROAS, risk of poor decisions.

4. Calendar metrics instead of cohort → "leakage" of meaning in comparing sources.

5. Lack of idempotency → FTD duplicates, "inflated" ARPUs.

6. Ignoring compliance → bans, CAC growth and loss of inventory.

Metric → Lever Mini-Table

'CR_c→r' → land speed, offer parity, localization.

'CR_r→kyc' → UX KYC, hints and SLA.

'CR_kyc→ftd' → payments, onboarding, honest bonus.

'2nd _ dep '/' Retention '→ content calendar, tournaments, CRM.

'ARPU/LTV '→ VIP service, payment methods, anti-fraud.

'Payback/ROAS '→ channel mix, betting/pacing.

'Chargeback/Fraud '→ filters, velocity, support training.

'Approval rate '→ compliance scan of creatives/landing pages.

Casino marketer checklist

Funnel: 'click→reg→KYC→FTD' (by source/creative/GEO/device).
Quality: '2nd _ dep', 'Retention D7/D30', 'Chargeback/Fraud'.
Economy: 'ARPU D7/D30/D90', 'ROAS/ROI', 'Payback'.
Compliance: 'Approval rate', reasons for deviations.
Technique: delay of postbacks, proportion of events without 'click _ id'.
Slices: FTD cohorts, VIP share, payment methods.

Example of a mini-case (simplified)

Spend = 50 000; CPA (on FTD) = 200; FTD = 250 → CPA = 200.

ARPU D30 (NGR) = 180 → Payback not reached, ROAS D30 = 180/200 = 0.9.

But the '2nd _ dep rate' rose from 28% to 36% after the localization of payments → ARPU forecast D90 = 260; Payback ≤ D90.

Solution: we hold the ligaments, strengthen retention and VIP-service, distribute the spend into creatives/geo with the best 'CR_kyc→ftd'.

These 10 metrics are the casino marketer's "dashboard." Consider them on an NGR basis, cohort-oriented and taking into account compliance. With this approach, every solution - from creatives to geo-mix - will rely on money, quality and sustainability: you find work bundles faster, avoid bans and build predictable Payback and long LTV.