Level atrix
Compare levels and access
Contents · Level Matrix
Definitions
- Warehouse (DWH)
- the operator’s fact store (ClickHouse, BigQuery and equivalents): history of transactions and events (bets, payments, bonuses, withdrawals, sessions).
- Replica
- a read-only copy of the operational DB (Postgres and equivalents) or the affiliate platform DB.
- Exports
- agreed files in CSV / XLSX / Google Sheets (period aggregates, per-player cumulative, events).
- BI
- dashboards and aggregates from the operator’s management and product analytics (Tableau, Power BI and equivalents).
Show all terms
- user_id
- internal player identifier. Contacts (email, name, phone, address) are excluded on the client side before the export is handed over; user_id is sufficient at every level.
- partner_id
- affiliate identifier (Stag and equivalents). Affiliate contacts are not requested; partner_id is sufficient at every level.
- Casino back office
- the brand / platform admin panel on top of the operational DB (players, transactions, events and equivalents).
- Affiliate platform
- a tracking platform for affiliate marketing (Affilka, NetRefer and equivalents).
- Traffic tagging
- source type (SEO, PPC, FB and equivalents) and deal terms along the path to registration and FTD.
- CRM
- the player relationship management system: segments, statuses, communications and contact history (Customer.io, Optimove and equivalents).
- ISR
- the operator’s and platform’s internal management reporting. Needed to determine Royalty (Game Provider Fee, payment processing cost and equivalents) as a participant in the waterfall: GGR; - Bonus → NGR; - Royalty → Gross Profit; - ∑ CAC (PP) → Income.
- Payments back office
- the admin panel for the payments and cashier service, with methods, PSPs and transaction processing (PaymentIQ / DevCode, FinteqHub and equivalents).
- Session services
- session recording and behavioral heatmaps (Hotjar, MS Clarity and equivalents).
- Page tagging
- screen tagging for a proper CJM.
- CS back office
- the admin panel for the customer support service, with a ticketing system and live chat for players (Intercom, Live Chat and equivalents).
- Call Service
- an external outbound-call system (e.g. Vapi/Twilio).
- AF service
- an anti-fraud service cross-checking devices and accounts (Fingerprint and equivalents).
- SEO tools
- rankings, indexing and the link profile (Google Search Console, Ahrefs and equivalents).
- Review portals
- accounts on review and brand-mention portals (AskGamblers, Trustpilot and equivalents); access enables further integrations.
- Workflow regulations
- internal descriptions of marketing, CRM, support and product steps, used to build the process audit and the AI-rollout roadmap.
Data and access
We work under NDA and read-only - writes and integrations into your production systems are not part of the audit scope.
| Level | Access | Not required |
|---|---|---|
| Level A | Product URL, list of competitors, target GEO. Affiliate landing page - if available; otherwise a link from review portals or search results | Admin panel, CRM, BI, warehouse (DWH) |
| Level B | Level A scope + period aggregates and a per-player cumulative export (user_id, partner_id, totals). Landscape snapshot | Event history, CRM, full warehouse (DWH) |
| Level C | Level A scope + transaction/event history, CRM, affiliate platform under NDA. Additional/optional for the package: AF service, CS and Call Service back offices, payments back office, traffic and page tagging + session services, SEO tools | Review-portal accounts, workflow regulations |
| Add-ons | On top of package C | Player and affiliate contacts |
Level matrix
| Result | A | B | C | Extra access |
|---|---|---|---|---|
Player journey, cashier and games | ||||
| Page matrix of key URLs | ✓ | ✓ | ✓ | |
| Comparison of two registration scenarios: affiliate landing page vs organic | ✓ | ✓ | ✓ | |
| Player journey map in four stages, with evidence | ✓ | ✓ | ✓ | |
| Onboarding corridor map: registration → first deposit → first session | ✓ | ✓ | ✓ | |
| Friction log with evidence (desktop + mobile) | ✓ | ✓ | ✓ | |
| QA check log: stability, speed and interface correctness | ✓ | ✓ | ✓ | |
| CJM behavioral layer: clicks, rage clicks, on-screen returns, drop-off | — | — | ✓ | Page tagging + session services |
| CJM behavioral layer: continuous collection (integration) | — | — | Page tagging + session services | |
| Cashier materials: methods, error texts, deposit variations 0 / 1 / 2 / 5 | ✓ | ✓ | ✓ | |
| Breakdown of the “deposit failed” path | ✓ | ✓ | ✓ | |
| “Deposit attempt → successful FTD” gap: failed FTD on aggregates | — | ✓ | ✓ | |
| Failed FTD reasons (method / PSP / retry) | — | — | ✓ | |
| Acceptance Rate and success of cashier methods | — | — | ✓ | |
| Transaction cost and comparative findings by method | — | — | ✓ | |
| Extended cashier analytics | — | — | ✓ | Payments back office |
| Cashier alerting (integration) | — | — | Payments back office | |
| Deposit chain distribution: Dep1 / Dep2 / Dep3 / Dep4 / Dep5, Dep6-10, Dep10+ | — | ✓ | ✓ | |
| Distribution by time interval from registration to FTD and its effect on funnel depth | — | — | ✓ | |
| Share of players with deposits but no single bet ever – a product defect or a fraud pattern | — | — | ✓ | |
| Money flow: deposits, withdrawals, HOLD | — | ✓ | ✓ | |
| Game sample with opening timings and lobby remarks | ✓ | ✓ | ✓ | |
| Breakdown of the search form, lobby structure and quick links | ✓ | ✓ | ✓ | |
| Surface audit of game offerings: verticals and their discoverability | ✓ | ✓ | ✓ | |
| “Vertical → retention / return” hypotheses | ✓ | ✓ | ✓ | |
| Personal cabinet breakdown: navigation, account data, settings, documents / KYC status, history, security | ✓ | ✓ | ✓ | |
| Withdrawal and KYC materials, or a record of the path's absence / blockage | ✓ | ✓ | ✓ | |
| Timings and reports on actions and performance | ✓ | ✓ | ✓ | |
| External bot probes (registration, deposit, bets) within agreed limits | — | — | ✓ | |
| Reconciliation of test-account identifiers with internal tagging (bot / fraud / duplicate) | — | — | ✓ | AF service |
| Detection of multi-accounting and bonus abuse in the warehouse | — | — | ✓ | |
| Actual funnel Reg → FTD → Dep2+ | — | ✓ | ✓ | |
Design, content and locale | ||||
| Design findings and a WCAG 2.2 AA remarks register | ✓ | ✓ | ✓ | |
| Assessment of triggers, CTAs and overload with a list of optimizations | ✓ | ✓ | ✓ | |
| Comparison of triggers, CTAs and overload with the CRM chain: in-app windows, frequency and channel | — | — | ✓ | CRM |
| Editorial register for copy and graphics | ✓ | ✓ | ✓ | |
| Register of format and locale errors; recorded language and currency | ✓ | ✓ | ✓ | |
| Assessment of fit to the target GEO | ✓ | ✓ | ✓ | |
| Check of tier-3 pages against an agreed list of sections | — | ✓ | ✓ | |
Bonuses, loyalty and communications | ||||
| Map of general bonuses with an assessment | ✓ | ✓ | ✓ | |
| Bonus load and effectiveness on aggregates | — | ✓ | ✓ | |
| Accumulated bonus issuance and the share of bonuses in GGR per player | — | ✓ | ✓ | |
| Bonus Performance: which bonus and mechanic led to a deposit, wager progress, abuse patterns | — | — | ✓ | |
| Comparison of bonus load in the affiliate platform against the actual cost of bonuses in the warehouse; the size of the gap and its effect on NGR / RevShare | — | — | ✓ | Affiliate platform |
| Matching the terms of visible Level A offers against the warehouse facts | — | — | ✓ | |
| Breakdown of the loyalty program and offer personalization | ✓ | ✓ | ✓ | |
| Assessment of bonus-offer personalization after onboarding: welcome / FTD vs Dep2 / Dep5 | ✓ | ✓ | ✓ | |
| Effect of the welcome package on the chain FTD → Dep2 → Dep3 → Dep4 → Dep5 | — | — | ✓ | |
| “RFMVPS strategic segment → offer and message” matrix | — | — | ✓ | CRM |
| Automation of personal bonus offers (integration) | — | — | CRM | |
| Priorities for a personalized lobby and product by verticals and game types | — | — | ✓ | |
| Personalized lobby (integration) | — | — | ||
| Gamification assessment: mechanics composition, participation terms, reward visibility | ✓ | ✓ | ✓ | |
| Gamification reach on aggregates: participant share, effect on session frequency and deposit-chain depth | — | ✓ | ✓ | |
| Gamification return: which mechanic drives deposits and return, effect on LTV and churn | — | — | ✓ | |
| 14-day communications feed and personalization assessment | ✓ | ✓ | ✓ | |
| Lifecycle chains and reactivation policies | — | ✓ | ✓ | |
Traffic and affiliates | ||||
| Funnel cut: affiliate entry vs organic | — | ✓ | ✓ | |
| FTD / NGR cut by sources and affiliates, paid vs organic share | — | ✓ | ✓ | |
| Concentration of FTD and NGR among top affiliates and the leader's share | — | ✓ | ✓ | |
| Cohort distribution by affiliate: retention, churn, share of one-time depositors, bonus load, “whales and sharks” (from 50 FTD / month) | — | ✓ | ✓ | |
| Distribution by age, gender and geo; ARPU by demographic segment | — | ✓ | ✓ | |
| Hidden fraud – cohort anomalies, incl. time-interval metrics, relative to the average of the relevant market (benchmark: tier 1 GEO) | — | — | ✓ | Traffic tagging |
| Click funnel: click-to-registration and click-to-deposit conversion by affiliate and source type | — | — | ✓ | Affiliate platform + traffic tagging |
| Three CACs: full, PP, blended – with the denominator stated | — | — | ✓ | Affiliate platform |
| Three actual CACs (full, PP, blended) with a reconciliation bridge: FTD, bonuses issued vs used, NGR | — | — | ✓ | Affiliate platform |
| Three payback periods: NGR, Gross Profit, Income – on both layers (affiliate platform and actuals) | — | — | ✓ | Affiliate platform |
| Funnel and payback broken down by affiliate, source type and target country (from 50 FTD / month) | — | — | ✓ | Affiliate platform + traffic tagging |
| Payback by deal terms and price corridors (CPA / RevShare / Hybrid) within the affiliate × source type × target country combination (from 50 FTD / month) | — | — | ✓ | Affiliate platform + traffic tagging |
| Cumulative scale / cut / hold / renegotiate map by affiliate, source type and deal terms (from 100 FTD) | — | — | ✓ | Affiliate platform + traffic tagging |
Retention and churn | ||||
| Cohort retention: D1 / D3 / D7 / D14 / D30 / D90 (where fields are available) | — | ✓ | ✓ | |
| Retention curve and early churn, including the share of one-day FTD | — | ✓ | ✓ | |
| D7→D30 decay (and D30→D90 if both horizons are in the package) | — | ✓ | ✓ | |
| Reconciliation of Level A communication density with dips in the retention curve | — | ✓ | ✓ | |
| Share of one-time depositors vs repeat depositors | — | ✓ | ✓ | |
| Distribution of closed accounts | — | ✓ | ✓ | |
| Volume distribution by provider, category and vertical | — | — | ✓ | |
| Link between a specific player's vertical and their retention and return | — | — | ✓ | |
| Tournament participation: effect on the next deposit and retention | — | — | ✓ | |
| Churn with a comparison baseline and the implied daily outflow | — | — | ✓ | |
| Churn prediction – ACTIVE / RISK segments (by recency) accounting for behavioral patterns | — | — | ✓ | |
| Link between Churned and touches and offers: which messages did or did not bring activity back | — | — | ✓ | CRM |
| COLD and LOST segments by deposit recency (excluding bets and withdrawals) | — | ✓ | — | |
| Churned by the last change to the real balance: deposit, withdrawal or bet | — | — | ✓ | |
| RFMVPS on the cumulative: M/P/S in full, R only by deposit date, without F and V | — | ✓ | — | |
| Segment distribution on the full RFMVPS (Recency, Frequency, Monetary, Velocity, Profitability, Security): six axes – including deposit-chain speed and behavioral security | — | — | ✓ | CRM |
| RFMVPS (integration) | — | — | CRM | |
VIP | ||||
| VIP by grade and contribution to NGR | — | ✓ | ✓ | |
| Reconciliation of the internal VIP list against actual revenue per player | — | ✓ | ✓ | |
| Speed of becoming VIP: distribution of days/deposits from registration to VIP status, by entry cohort | — | — | ✓ | |
| VIP dynamics: new, returned, inactive and deactivated VIPs over the period | — | ✓ | ✓ | |
| VIP behaviour: session and betting behavior, behavior-based churn risk, personal offers | — | — | ✓ | CRM |
| “VIP grade → offer and message” matrix | — | — | ✓ | CRM |
| Breakdown of “sharks”: players with a negative contribution by withdrawal-to-deposit ratio | — | ✓ | ✓ | |
| Share of the personal bonus budget going to the VIP segment, and its return | — | — | ✓ | |
| Churn rate in the VIP segment, separate from overall portfolio churn | — | ✓ | ✓ | |
| Reactivation of dormant and lost VIPs: share of returners, the return's contribution to NGR, effectiveness of reactivation campaigns by grade | — | — | ✓ | CRM |
P&L, LTV and unit economics | ||||
| Operator P&L: waterfall GGR → NGR → Gross Profit → Income | — | — | ✓ | ISR |
| Cost of bonuses, Royalty (PSP / providers / WL) and marketing | — | — | ✓ | Affiliate platform + ISR |
| Cost distribution by provider fee groups and an assessment of how effectively the negative-GGR buffer is managed | — | — | ✓ | ISR |
| Negative-GGR buffer management assistant, incl. alerting (integration) | — | — | ||
| Product activity aggregates: bets, average per player, bet / dep, RTP and Margin as a BI observation | — | ✓ | ✓ | |
| LTV, ARPPU and the share of bonuses in GGR | — | ✓ | ✓ | |
| LTV on the 7 / 30 / 60 / 90 horizons | — | — | ✓ | |
| Per-player unit economics on cumulative revenue, without cost allocation | — | ✓ | ✓ | |
| Unit economics with cost allocation per player and per product | — | — | ✓ | |
| Cohort revenue per FTD by entry cohort | — | ✓ | ✓ | |
Market, support and reputation | ||||
| Map of offers and features for the player: jackpots, lottery, referral, VIP program, tournaments, app, mobile, gamification, knowledge base, catalog composition, presence of sportsbook / prediction markets (no functional audit) | ✓ | ✓ | ✓ | |
| Top-level audit of the support service | ✓ | ✓ | ✓ | |
| Ticket load, SLA, CSAT / NPS, staffing and script QA; improvement backlog; conversion to deposit and churn after contact, broken down by contact topic | — | — | ✓ | CS back office |
| Distribution of outbound calls by segment and their effect on deposit conversion | — | — | ✓ | Call Service |
| Support analytics automation and alerting (integration) | — | — | CS back office | |
| Top-level SEO findings | ✓ | ✓ | ✓ | |
| Rankings and organic visibility | — | — | ✓ | SEO tools |
| Publicly available brand trust with growth points, including a distribution by complaint topic (withdrawals, bonuses, support) | ✓ | ✓ | ✓ | |
| Comparison of reputation tone with 3 competitors | ✓ | ✓ | ✓ | |
| Reputation monitoring (integration) | — | — | Review portals | |
| Product SWOT against 3 competitors: every point backed by a screenshot, a link and an observation date | ✓ | ✓ | ✓ | |
| SWOT comparison axes: localization, USP, UX / UI, registration form, cashier and payment methods, deposit and withdrawal limits, providers visible at onboarding, the player offering, bonuses and the loyalty program, support service, brand trust | ✓ | ✓ | ✓ | |
| A “product vs competitors” comparison table for every axis, marked stronger / on par / weaker, including a table of deposit and withdrawal limits | ✓ | ✓ | ✓ | |
| Opportunities and threats: unoccupied niches, risks of mechanics being copied, dependency on individual providers and payment methods | ✓ | ✓ | ✓ | |
Outcome, data and decision | ||||
| Systems landscape snapshot | ✓ | ✓ | ✓ | |
| “Level A observation → B / C KPI family” map | ✓ | ✓ | ✓ | |
| List of diagnostic pairs for the next level | ✓ | ✓ | ✓ | |
| Executive summary for management | ✓ | ✓ | ✓ | |
| Priorities confirmed by the numbers | — | ✓ | ✓ | |
| List of priority tasks (quick wins) | ✓ | ✓ | ✓ | |
| Proposals for long-term strategies | ✓ | ✓ | ✓ | |
| Hypothesis-testing plan | ✓ | ✓ | ✓ | |
| Proposals for integrating new mechanics and tools, with a qualitative forecast of their effect on conversions, LTV and trust | ✓ | ✓ | ✓ | |
| Recommendations for raising brand trust | ✓ | ✓ | ✓ | |
| AI discovery: map of manual steps, a shortlist of use cases, a list of the data needed | — | — | ||
| Workflow audit (marketing, CRM, support, product), an AI-rollout roadmap and an action plan naming the points of impact on margin | — | — | Workflow regulations | |
FAQ
What do the marks in the table mean?
- ✓ the result is included in the Level A package.
- ✓ the result is included in the Level B package.
- ✓ the result is included in the Level C package.
- an add-on on top of package C, ordered separately.
- – the result is not included at this level.
Can I order just one row from the table?
No, the package is ordered as a whole level (A / B / C). Individual rows are not sold one by one, except add-ons.
Do I have to go through A and B before C?
No. A is always included in C. The B aggregate layer is included in C if B was not ordered separately.
What are add-ons?
Integrations on top of package C: a standing loop in the CRM, product or platform instead of a one-off cut in the report - AI discovery, reputation monitoring, cashier alerting, the RFMVPS integration and others. Marked with ● in the table.
Are add-ons included in the price of C?
No, they are ordered as a separate proposal after the audit.
What if a task doesn't fit into any level?
There are tasks and questions that fall outside the Level A / B / C catalog - non-standard requests specific to your product or business. These cases are not covered by a ready-made level package and are not priced from the catalog - we discuss them separately, after the main audit, and make an individual proposal for that specific task.
Where do I start if I'm not sure which level I need?
Start with Level A - it shows what is visible from the outside and gives an initial picture of the brand's "health". If you order a deeper audit later (B or C), the cost of A is credited toward it.