Level B

Numbers without the warehouse

Executive summary

We check what is visible from the outside against your own numbers: a cumulative cut for an agreed period and GEO - period aggregates and lifetime totals per player. Funnel, bonus load, retention, deposit chain, VIP grades, segmentation and source structure. Individual transaction history - bets, payments, bonuses, withdrawals and sessions - is not opened. Player and affiliate contacts are not needed at any level.

From the outside you see friction, offers and hypotheses. On aggregates, facts appear that an ordinary player never observes - with recommendations and quick wins for each family:

  • which step of the funnel Reg → FTD attempt → FTD → Dep2 → Dep5 actually cuts volume, including failed FTD;
  • where bonuses dilute NGR across the package period - unlike the outward appearance of the offer on the site;
  • how the VIP grades' contribution is distributed - with no contacts;
  • where the retention curve shows a drop-off after FTD and whether the dip lines up with communication density.
TermValue
PrerequisiteScope includes Level A; the landscape snapshot shows which data is actually available in your stack, and the modules adapt to it
AccessPeriod aggregates and a per-player cumulative export (user_id, partner_id, lifetime totals, dates of first and last deposit and withdrawal, status and tags). No contacts and no event history
PeriodLast 9 months by default; deeper - by separate agreement
GeographyOverall picture across all GEOs plus a distribution across the top 3 countries and "the rest". GEO-dependent modules (locale, content, SWOT, trust, support) - for one target GEO, as at level A
Cost30,000 USD (per brand). If Level A has already been done - 15,000 USD
Turnaround~6 weeks from the start date, including the Level A scope. The exact timeline depends on the number of families in the package and how complete the fields turn out to be after the landscape snapshot

Contents · Level B

What's included

ResultB
B1 Player journey, cashier and games
Page matrix of key URLs (A)✓
Comparison of two registration scenarios: affiliate landing page vs organic (A)✓
Player journey map in four stages, with evidence (A)✓
Onboarding corridor map: registration → first deposit → first session (A)✓
Friction log with evidence (desktop + mobile) (A)✓
QA check log: stability, speed and interface correctness (A)✓
Cashier materials: methods, error texts, deposit variations 0 / 1 / 2 / 5 (A)✓
Breakdown of the “deposit failed” path (A)✓
“Deposit attempt → successful FTD” gap: failed FTD on aggregates✓
Deposit chain distribution: Dep1 / Dep2 / Dep3 / Dep4 / Dep5, Dep6-10, Dep10+✓
Money flow: deposits, withdrawals, HOLD✓
Game sample with opening timings and lobby remarks (A)✓
Breakdown of the search form, lobby structure and quick links (A)✓
Surface audit of game offerings: verticals and their discoverability (A)✓
“Vertical → retention / return” hypotheses (A)✓
Personal cabinet breakdown: navigation, account data, settings, documents / KYC status, history, security (A)✓
Withdrawal and KYC materials, or a record of the path's absence / blockage (A)✓
Timings and reports on actions and performance (A)✓
Actual funnel Reg → FTD → Dep2+✓
B2 Design, content and locale
Design findings and a WCAG 2.2 AA remarks register (A)✓
Assessment of triggers, CTAs and overload with a list of optimizations (A)✓
Editorial register for copy and graphics (A)✓
Register of format and locale errors; recorded language and currency (A)✓
Assessment of fit to the target GEO (A)✓
Check of tier-3 pages against an agreed list of sections✓
B3 Bonuses, loyalty and communications
Map of general bonuses with an assessment (A)✓
Bonus load and effectiveness on aggregates✓
Accumulated bonus issuance and the share of bonuses in GGR per player✓
Breakdown of the loyalty program and offer personalization (A)✓
Assessment of bonus-offer personalization after onboarding: welcome / FTD vs Dep2 / Dep5 (A)✓
Gamification assessment: mechanics composition, participation terms, reward visibility (A)✓
Gamification reach on aggregates: participant share, effect on session frequency and deposit-chain depth✓
14-day communications feed and personalization assessment (A)✓
Lifecycle chains and reactivation policies✓
B4 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✓
B5 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✓
COLD and LOST segments by deposit recency (excluding bets and withdrawals)✓
RFMVPS on the cumulative: M/P/S in full, R only by deposit date, without F and V✓
B6 VIP
VIP by grade and contribution to NGR✓
Reconciliation of the internal VIP list against actual revenue per player✓
VIP dynamics: new, returned, inactive and deactivated VIPs over the period✓
Breakdown of “sharks”: players with a negative contribution by withdrawal-to-deposit ratio✓
Churn rate in the VIP segment, separate from overall portfolio churn✓
B7 P&L, LTV and unit economics
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✓
Per-player unit economics on cumulative revenue, without cost allocation✓
Cohort revenue per FTD by entry cohort✓
B8 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) (A)✓
Top-level audit of the support service (A)✓
Top-level SEO findings (A)✓
Publicly available brand trust with growth points, including a distribution by complaint topic (withdrawals, bonuses, support) (A)✓
Comparison of reputation tone with 3 competitors (A)✓
Product SWOT against 3 competitors: every point backed by a screenshot, a link and an observation date (A)✓
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)✓
A “product vs competitors” comparison table for every axis, marked stronger / on par / weaker, including a table of deposit and withdrawal limits (A)✓
Opportunities and threats: unoccupied niches, risks of mechanics being copied, dependency on individual providers and payment methods (A)✓
B9 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✓
Compare levels

Modules

B1 Player journey, cashier and games

What we do:

  • We walk the whole flow on test accounts (desktop + mobile) - from registration to withdrawal - and record friction and drop-offs across four stages: registration, deposit, play, withdrawal; we separately tag the onboarding corridor and two entry scenarios - via affiliate link and from organic
  • We run the cashier by target-GEO methods and cryptocurrency, including variations of 0 / 1 / 2 / 5 and separately the "deposit failed" flow; we check key scenarios for stability, speed and interface correctness (QA)
  • We assess the lobby, search and vertical discoverability, review the account area and the withdrawal path with KYC gates, and measure timings on money steps and on game opening
  • On aggregates we calculate what is only visible as a hypothesis from the outside: the actual funnel registration → first-deposit attempt → successful FTD versus failed FTD, then FTD → Dep2 → Dep5 on the 1 / 2 / 5 axes
  • We break the deposit chain down by Dep1-Dep5, Dep6-10 and Dep10+ steps and roll up the period's money flow: deposits, withdrawals, HOLD

Deliverable in the package:

  • Page-by-page matrix of key URLs; player journey map across four stages, with evidence; onboarding-corridor map; comparison of two registration scenarios
  • Friction log with evidence (desktop + mobile); QA check log
  • Cashier materials: methods, error copy, deposit variations; breakdown of the "deposit failed" flow
  • Game sample with opening-time measurements and lobby notes; breakdown of the search form, lobby structure and quick links; surface audit of game offerings; "vertical to retention / return" hypotheses
  • Account-area breakdown; withdrawal and KYC materials or a record of the flow being missing / blocked; timings and reports on actions and performance
  • Actual funnel Reg → FTD → Dep2+; "deposit attempt to successful FTD" gap on aggregates; deposit-chain distribution Dep1-Dep10+; money flow: deposits, withdrawals, HOLD

B2 Design, content and locale

What we do:

  • On the core paths we run a full WCAG 2.2 AA audit and assess the UI from the player's position: clarity of terms, statuses, errors, limits, bonuses and path steps
  • We check pressure signals (timers, scarcity, pop-ups), CTA hierarchy and screen overload
  • We editorially proofread copy and graphics; native-language fit is assessed only by native speakers, and offer, messaging and creative fit to the target GEO - by market residents
  • We check currency, amount, date and phone formats against the target GEO
  • We go beyond the core paths and check tier-3 pages against a list of sections agreed at the start: help, rules, promo landing pages, provider and category pages, legal texts. We record the scope as a list, not by click depth; no warehouse or third-party services are needed
  • The module is GEO-dependent: locale, content and offer fit are assessed for one target GEO

Deliverable in the package:

  • Design findings and a WCAG 2.2 AA issue register
  • Trigger, CTA and overload assessment with a list of optimizations - keep / simplify / remove
  • Editorial register for copy and graphics
  • Register of format and locale errors; recorded language and currency; assessment of fit to the target GEO
  • Design, WCAG, editorial and locale issue registers for the agreed list of tier-3 URLs

B3 Bonuses, loyalty and communications

What we do:

  • We inventory the visible bonus offer and assess it: terms transparency, wager, risk to the operator
  • We review the loyalty program and gamification (missions, levels, achievements, races, leaderboards, wheel / scratch) and compare welcome / FTD offer personalization against Dep2 and Dep5 after onboarding
  • We record the composition and timing of messages on test accounts - emails, inbox, push, in-product, SMS, calls - over a 14-day window
  • On aggregates we calculate what that offer actually costs: bonus cost, the share of bonuses in GGR and in deposits, NGR margin, bonus conversion and usage, accumulated issuance and the share of bonuses in GGR per player
  • We measure gamification reach: participant share, effect on session frequency and deposit-chain depth; we review lifecycle chains and reactivation policies against the period's actuals

Deliverable in the package:

  • Map of general bonuses with an assessment
  • Breakdown of the loyalty program and offer personalization; assessment of bonus-offer personalization after onboarding (welcome / FTD vs Dep2 / Dep5); gamification assessment
  • 14-day communications feed and personalization assessment
  • Bonus load and effectiveness on aggregates; accumulated bonus issuance and the share of bonuses in GGR per player
  • Gamification reach on aggregates; lifecycle chains and reactivation policies

B4 Traffic and affiliates

What we do:

  • We cut the funnel by entry type: affiliate link versus organic - across the whole path from registration to repeat deposits
  • We calculate FTD and NGR by source, affiliate and country: partner_id (Stag) sits in the cumulative player export, so the cut is built without access to the affiliate platform. We compare the share of paid traffic against organic
  • We calculate concentration: the top-5 affiliates' share of FTD and NGR and the leader's share
  • We review the quality of the incoming cohort for each affiliate with a flow of 50+ FTD a month - below that threshold the sample is not representative: retention, churn, share of one-time depositors, bonus load, and how many "whales" and "sharks" are in the flow
  • We build a demographic profile of the base: distribution by age, gender and geo and ARPU by demographic segment

Deliverable in the package:

  • Funnel cut: affiliate entry vs organic
  • FTD / NGR cut by sources and affiliates, paid vs organic share
  • Concentration of FTD and NGR by top affiliates (top 5 and leader's share)
  • Cohort distribution by affiliate: retention, churn, share of one-time depositors, bonus load, "whales and sharks"
  • Distribution by age, gender and geo; ARPU by demographic segment

B5 Retention and churn

What we do:

  • We calculate cohort retention on the D1 / D3 / D7 / D14 / D30 / D90 horizons (where fields are available)
  • We build the retention curve and early churn and single out the share of one-day FTD - players lost right after the first deposit
  • We calculate D7→D30 decay (and D30→D90 if both horizons are in the package), the share of one-time depositors against repeat depositors, and the distribution of closed accounts
  • We reconcile the communication density recorded on the outer surface against dips in the retention curve; we compare the curve against GEO expectations as domain experts
  • We tag COLD and LOST segments by deposit recency - excluding bets and withdrawals - and calculate RFMVPS on the cumulative: Monetary, Profitability and Security in full, Recency only by deposit date, with Frequency and Velocity unavailable at this data layer
  • We formulate recommendations for reactivating "dormant" players at the policy level - when to send a message and which offer type - with no list of user_id

Deliverable in the package:

  • Retention by cohort 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
  • Reconciliation of communication density with dips in the retention curve
  • Share of one-time depositors against repeat depositors; distribution of closed accounts
  • COLD and LOST segments by deposit recency; RFMVPS on the cumulative (M / P / S in full, R only by deposit date, without F and V)

B6 VIP - aggregates and grades

What we do:

  • We calculate the VIP share of the portfolio and the distribution by grade: headcount, deposits, contribution to revenue
  • We reconcile the internal VIP list against actual revenue per player - who the status describes in fact, and who only by name
  • We build the period dynamics: new, returned, inactive and deactivated VIPs
  • We single out "sharks" - players with a negative contribution by withdrawal-to-deposit ratio - and calculate the churn rate inside the VIP segment separately from overall portfolio outflow
  • We read the segment through RFMVPS grades on aggregates, without going down to the player level: the scoring itself is calculated in module B5

Deliverable in the package:

  • VIP by grade and contribution to NGR
  • Reconciliation of the internal VIP list against actual revenue per player
  • VIP dynamics: new, returned, inactive and deactivated VIPs over the period
  • Breakdown of "sharks": players with a negative contribution by withdrawal-to-deposit ratio
  • Churn rate in the VIP segment, separate from overall portfolio churn

B7 P&L, LTV and unit economics

What we do:

  • We roll up product activity aggregates: bet volume and count, average per player, bet-to-deposit ratio, game-category shares. We take RTP and Margin as a BI observation, not recalculated
  • We calculate LTV, ARPPU and the share of bonuses in GGR on the cumulative export
  • We build per-player unit economics on cumulative revenue - without cost allocation, which is only possible on the warehouse layer
  • We calculate cohort revenue per FTD by entry cohort

Deliverable in the package:

  • 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
  • Per-player unit economics on cumulative revenue, without cost allocation
  • Cohort revenue per FTD by entry cohort

B8 Market, support and reputation

What we do:

  • We inventory the product offer to the player: jackpots, lottery, referral, VIP program, tournaments, app, mobile, gamification, knowledge base, catalog composition and providers, presence of sportsbook / prediction markets - with no functional audit
  • We check support-service channels and discoverability on the public surface, against competitors
  • We collect reputation from gambling portals and forums: complaint topics and tone relative to 3 agreed competitors - with no survey of your own base and no paid media monitoring
  • We assess the product's readiness for top-level SEO: indexability, robots / sitemap, speed of key URLs
  • We build an eleven-axis SWOT against 3 competitors, every claim backed by a screenshot, link and observation date

Deliverable in the package:

  • Map of player-facing offers and features
  • Top-level audit of the support service; top-level SEO findings
  • Public brand trust with growth points, including a distribution by complaint topic; comparison of reputation tone with 3 competitors
  • Product SWOT against 3 competitors and 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
  • "Product vs competitors" comparison table by axis, including a limits table; opportunities and threats: unoccupied niches, risks of mechanics being copied, dependency on providers and payment methods

B9 Outcome, data and decision

What we do:

  • We roll up the period's status for management: registrations, FTD and FTD share of registrations, GGR, NGR, bonus share of GGR, withdrawal-to-deposit ratio, average revenue per depositor, active depositors, 7- and 30-day retention - cut by GEO and top countries
  • We agree the landscape snapshot of the systems: which fields and families your BI actually returns - the package composition adapts to that
  • We reconcile external-surface hypotheses against the period's actuals as pairs of "outside observation to inside metric": entry and cashier friction → weak registrations and FTD; an opaque offer → weak NGR while GGR holds up; "no return after the first session" → high churn; an easy or broken withdrawal → withdrawal-to-deposit ratio
  • We consolidate the findings of all B1-B8 modules into a single report: we rank tasks by operational payoff and implementation complexity, and separate what the period's numbers confirm from what needs the warehouse layer
  • We give a qualitative assessment of how proposed new mechanics and tools would affect conversion, LTV and trust

Deliverable in the package:

  • Period status summary cut by GEO (top 3) and key metrics; executive summary
  • Systems landscape snapshot
  • Priorities confirmed by the numbers; a list of priority tasks (quick wins)
  • Proposals for long-term strategies based on the SWOT; a hypothesis-testing plan
  • A "Level A observation to Level B / C KPI family" map and a list of diagnostic pairs for the next level
  • Proposals for integrating new mechanics and tools with a qualitative forecast of their effect on conversion, LTV and trust; recommendations for raising brand trust
Explore Our Methodology

What to provide

Required

  1. Level A inputs: product URL, link to the affiliate-link registration landing page, target GEO, a short brief on problem areas, and a list of 3 competitors - the Level A scope is included in Level B.
  2. An updated landscape snapshot.
  3. Period - last 9 months by default, the same for every family in the package. Geography - all of the brand's GEOs: country in the export acts as a cut, not a scope limit. The top-3 countries for the cut are determined by scoring on depositor count and stable deposit sum, not set in advance.
  4. A PII-free aggregate package per the field list below - tables, dashboards or read-only BI.
  5. Confirmation that the metric names in your dashboard match the canonical ones - we reconcile this together during validation.

Minimum field set for package B

The full list, not "the funnel and the rest":

  • period (last 9 months by default); country as a cut field - across all of the brand's GEOs, with no pre-filtering;
  • registrations;
  • FTD; first-deposit attempts and failed attempts;
  • Dep2 and Dep5 counts;
  • GGR; NGR;
  • bonus cost or bonus_used with a note on its match;
  • deposit sum; withdrawal sum;
  • bet volume and count;
  • active depositors (Depositors);
  • sum and count of first deposits;
  • withdrawal count;
  • retention D1 / D3 / D7 / D14 / D30 / D90 (where available);
  • FTD cut: affiliate entry against organic.

Plus a per-player cumulative export - one row per user_id:

  • user_id and partner_id (Stag);
  • deposit sum and count; withdrawal sum and count;
  • bet sum and win sum; GGR and NGR per player;
  • accumulated bonus and the share of bonuses in GGR;
  • dates of the first and last deposit and withdrawal - without them, Recency is calculated from account login rather than from money, and half of the segmentation loses its meaning;
  • registration date, last login date, account status, operator tags (VIP grade, risk flags), country and language; date of birth and gender.

Not required at this level

  • Player and affiliate contacts - email, name, phone, address. Not needed at any level: a player is identified by user_id, an affiliate by partner_id (Stag).
  • The full warehouse (DWH), replica, CRM and affiliate platform - these are Level C access items.
  • Cost and expense line items, LTV - calculated at Level C.

FAQ

Do I need to order A separately?

No. Level B includes the scope of A; the price of B includes A.

What is a landscape snapshot?

Agreeing which fields and families your BI actually returns - package B's modules adapt to that.

Is the warehouse opened?

No. B works on period aggregates and the per-player cumulative export, with no event history.

Do you need player contacts?

No. Only user_id and partner_id (Stag).

Why Level C?

Transaction history, operator P&L, CAC/payback, full RFMVPS and warehouse-level anti-fraud are not covered by the cumulative.

Contact us

Your message will be sent to contact@ipulse.top.