Top-Up Bonus Report — Analytics in IZI CRM

Top-Up Bonus Report — Analytics in IZI CRM

The Analytics → Top-Up Bonus report shows how your top-up bonus automation performs: how many times a rule fired, how much money flowed in from participants, whether average top-up amounts rose in the promo cohort — and most importantly, whether revenue per client actually changed compared to a prior period. This is the only place in IZI where you see not just “we paid out X in bonuses” but an honest signal of economic impact: ARPU uplift on the cohort, before and after.

To open the report: Analytics → Top-Up Bonus (Бонус за пополнение) → select a date range and location. All four blocks are on one screen, updating in real time.

KPI Cards — Quick Pulse of the Promotion

The top block gives you eight metrics at a glance. Half are volume metrics (how much happened); half are comparative (how the promo cohort compares to the full club).

Volume Metrics

Metric	What it counts
Operations	Number of rule triggers in the period: one client topping up three times = three operations
Top-Up Total	Total volume of top-ups that met the rule condition
Bonuses Paid Out	Total bonus amount accrued under the rule
Unique Clients	How many distinct players received a bonus at least once
Repeat Clients	How many of those players triggered a bonus rule more than once

How to read it: the ratio of Repeat to Unique clients shows whether the promotion builds a habit. If 60% of clients return to top up again — the rule is acting as a behavioral anchor, not a one-off incentive.

Comparative Metrics

Metric	What it counts
Club Average Check	Average top-up across all club transactions in the period, no promo filter
Promo Average Check	Average top-up only among clients who received a bonus
Difference	How much higher the promo average check is versus the club-wide average

How to read it: if the promo average check is higher than the club average, the promotion is either attracting clients who already top up more, or actively encouraging larger top-ups. This alone is not proof of causality — high-value clients may simply hit the threshold more often. For the honest answer, check the behavior-change block.

Parametric benchmark: if your club average check is B, expect the promo average check to sit near your first-tier threshold (roughly baseline × 1.2–1.5). If it falls below the threshold, part of your cohort is earning bonuses without actually topping up more — your threshold may be too low.

Cohort Behavior Change {#cohort-behavior-change}

This is the core analytical block of the report — and what separates it from a simple bonus payout counter.

IZI takes the cohort of clients who received a bonus in the current period and compares them against themselves in a prior comparison period. The logic: if the promotion genuinely changes behavior, the same clients should top up more and spend more — not just during the promo, but as a result of it.

Average Check Comparison

Metric	What it counts
Average Check — Comparison	The cohort’s average top-up in the comparison period
Average Check — Current	The same cohort’s average top-up in the current period
Average Check Uplift	Relative change: (current − comparison) / comparison × 100%

How to interpret:

Average Check Uplift	Signal
Negative	The cohort is topping up less — the promotion isn’t working, or the threshold is too high
0–5%	Near-neutral effect — regression to the mean may be masking real uplift
Above 10%	Promotion is encouraging larger top-ups — verify with ARPU
Above 25%	Strong signal — confirm there is no seasonal effect or selection bias

ARPU Uplift {#arpu-uplift}

Cohort ARPU is total top-ups minus refunds, divided by the number of clients. Unlike the average check, ARPU captures frequency: a client may top up more often rather than in larger amounts.

Metric	What it counts
ARPU — Comparison	Revenue per cohort client in the comparison period
ARPU — Current	Revenue per the same cohort client in the current period
ARPU Uplift	Relative ARPU change between periods

ARPU Uplift is the report’s primary honest signal. Growth in raw top-up totals or large bonus payouts does not mean the club earns more. If ARPU rose, the promotion genuinely increased per-client revenue. If ARPU is flat while bonus costs grew, the promotion redistributes money rather than generating new revenue.

Parametric ROI formula:

Promotion impact = ARPU Uplift × Unique Clients
Promotion cost   = Bonuses Paid Out × expected redemption rate

ROI = (Promotion impact − Promotion cost) / Promotion cost

Positive ROI means the revenue increase from the cohort exceeds the cost of issued bonuses. For a step-by-step breakdown of how to find your average top-up baseline in the CRM, see How to Calculate Average Top-Up.

Note on the sample: the block only covers clients who were active in both periods. The “calculated for N of M clients” note means M−N clients are excluded — typically new players with no comparison-period history. This is correct behavior: including them would inflate the apparent ARPU uplift.

By Rule

The By Rule table breaks results down by each individual automation rule configured for the club.

Column	What it shows
Rule	The rule name from automation settings
Clients	Unique clients who triggered this rule
Operations	Number of triggers
Top-Up Total	Volume of top-ups that matched this rule
Average Check	Average top-up size for this rule

How to use it: compare rules against each other. A rule with a high average check but few clients means the threshold is too high — almost no one reaches it. A rule with many operations but a low average check is functioning as a baseline tier; consider raising its threshold to encourage larger top-ups.

If you have configured a tiered structure (multiple levels), this table shows how the cohort distributes across tiers — most clients at tier 1, a handful at tier 3. That is expected: the upper tiers function as an aspirational anchor, not a mass instrument.

Parametric threshold guidance:

Tier 1: baseline × 1.2–1.4, bonus 4–6%
Tier 2: baseline × 2.5–3.0, bonus 10–14%
Tier 3: baseline × 5.0–6.0, bonus 18–22%

where baseline is your club’s average top-up (how to find it). Substitute your own currency amounts.

By Source

The By Source table shows which payment channel clients used when earning a bonus.

Source	Channel
App	IZI mobile app (online payment)
Card Terminal	Card payment at the club desk
Cash	Cash top-up via the register
Unknown	Channel not identified

Columns: Operations, Top-Up Total, Average Check.

How to use it: if most operations come via the card terminal but the app average check is noticeably higher, focus promotion communication on app users. If cash dominates, make sure staff are reminding clients about the promotion at the register. A spike in “Unknown” may signal a transaction attribution issue worth investigating.

Activity by Day

The daily chart shows per-day dynamics across the selected period: operation count and total top-up volume for each day. Use it to spot:

• activity peaks (weekends, paydays, holidays)
• unexplained drops
• the effect of external communications (if you announced the promotion on a specific day)

The CSV export button is in this block. Download per-day data to build your own reports or compare multiple periods side by side in a spreadsheet.

Practical Monitoring

Weekly Check (5 minutes)

1. Open Analytics → Top-Up Bonus, period — last 7 days
2. Check Operations — up or down versus the previous week?
3. Is the Average Check Uplift still positive?
4. If ARPU Uplift is negative — check whether rule settings or tariff conditions changed
5. In the By Rule table — is there a rule with zero operations? (it may have been accidentally deactivated)

Monthly Review (15 minutes)

1. Set current month and the equivalent prior month
2. Is ARPU Uplift stable, or was it a one-time spike?
3. Which rule tier is driving the bulk of volume?
4. Any channel imbalance in By Source?
5. Cross-reference Bonuses Paid Out against the Bonus Report — how much of what was issued has already been redeemed?

Signals and Actions

Indicator	Signal	Possible action
ARPU Uplift negative	Promotion not changing behavior	Revise thresholds or bonus percentage
Repeat Clients below 20%	No habitual refill pattern forming	Lower the first-tier threshold
Promo Average Check ≈ tier 1 threshold	Clients not progressing to higher tiers	Increase appeal of tier 2 (higher %)
Unknown source growing	Attribution error	Check payment integration settings
Zero operations on a rule	Rule inactive or threshold unreachable	Review automation configuration

Related Sections

• Bonus Report Metrics — overall loyalty program KPIs: accruals, redemptions, balance, conversion
• Bonus Report Operations — detailed log of every accrual and redemption per client
• Daily Analytics — daily revenue breakdown including bonus payments
• AOV in a Gaming Club — what average order value is and how to measure it
• Bonus Balance — how bonuses work in IZI: accrual, storage, redemption
• Raising Average Check via Top-Up Bonus — owner playbook: goal → formula → steps → measurement
• How to Calculate Average Top-Up — step-by-step metric walkthrough in the CRM