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Unmasking the True Cost of Loyalty: A Technical Deep‑Dive into Transparent Gaming Economics

By October 12, 2025September 16th, 2026No Comments

In an industry where “free spins” and “no‑deposit bonuses” glitter like neon, the real economics of loyalty programmes often stay hidden behind glossy UI screens. Players assume that points earned for every wager are a pure gift, yet every increment is underpinned by cost structures that affect bankroll safety, RTP calculations, and ultimately the player’s exposure to risk. When operators obscure these fees, they undermine responsible‑gambling safeguards and erode trust in the broader iGaming ecosystem.

A clearer view of loyalty economics helps regulators enforce limits on wagering and assists players in making informed choices about how much capital they truly allocate to an online betting app versus what is being siphoned for rewards. For those seeking a practical reference point, the site singapore online betting offers a neutral repository of guidelines that can be consulted when evaluating program transparency. By dissecting each component—from points accrual to tiered incentives—this article equips operators, auditors, and players with the metrics needed to spot hidden costs before they translate into problem gambling behaviours.

1. The Anatomy of a Loyalty Programme in iGaming

Loyalty schemes in modern online betting platforms resemble tiered frequent‑flyer clubs more than simple point buckets. At their core they consist of three interlocking parts: (1) points earned per unit of wagering, (2) tier thresholds that unlock progressively richer reward palettes, and (3) redemption options ranging from free bets to exclusive tournament seats. Operators price each element through a blend of direct cash outlay (e.g., $10 free bet), implied cost (higher house edge on specific games), and indirect expenses such as increased customer‑service load or compliance reporting.

Points are usually calibrated as a percentage of stake—commonly 0.5 % on slots with an RTP of 96 % and 0.2 % on live dealer tables where volatility is higher. Tier upgrades are triggered by cumulative turnover or net loss thresholds; moving from Bronze to Silver might require $5,000 in net wagers within a calendar month, prompting the operator to allocate an additional 2 % discount on rake for blackjack or lower wagering requirements on casino cash‑back offers.

These mechanisms interact with other cost drivers: bonuses inflate expected player lifetime value but also raise churn risk if not balanced against rake recovery; transaction fees from payment processors add another layer that is often amortised across the loyalty pool rather than shown as line items.

1.1. Points‑Earned Mechanics

Players accumulate points at a rate defined by game type and bet size:
– Slots ≥ $0.10 bet → 1 point per $2 wagered
– Live roulette ≤ $100 bet → 0.8 point per $2 wagered
– Sportsbook parlays → 1 point per $5 stake

The operator translates these points into monetary equivalents using a redemption factor (e.g., 10 points = $0.25 free bet). The hidden cost emerges when high‑RTP slot wins generate large point balances that must later be funded from the operator’s profit margin.

1.2. Tier‑Based Incentives

Tier systems create elasticity in player spend:
| Tier | Monthly Net Wager | Key Perk | Incremental Cost* |
|——|——————-|———-|——————-|
| Bronze | <$3k | Standard points accrual | — |
| Silver | $3k–$7k | +10 % points multiplier | +0·8 % gross margin |
| Gold | $7k–$12k| Dedicated account manager, faster withdrawals | +1·5 % gross margin |
| Platinum| >$12k| Free entry to high‑roller tournaments, bespoke promotions | +2·3 % gross margin |

*Cost expressed as additional percentage of gross gaming revenue required to sustain the perk.

2. Calculating the Hidden Expenses Behind “Free” Rewards

At first glance a £20 free spin appears costless; mathematically it represents several intersecting expense streams:

1️⃣ Direct Monetary Outlay – The platform must set aside cash reserves equal to the advertised value ($20). This is immediately recorded as liability on the balance sheet.

2️⃣ Opportunity Cost – Funds earmarked for free spins cannot be deployed elsewhere—such as improving RNG security or funding responsible‑gambling tools—resulting in an implicit loss measured against potential returns from alternative initiatives.

3️⃣ Capital Retention – When players gamble with bonus credit instead of personal bankrolls, their deposited capital stays idle longer within the operator’s vaults, generating interest or enabling better liquidity management.

4️⃣ Churn Adjustment – Not every rewarded player will convert into repeat revenue; industry benchmarks suggest only ~35 % redeem free bets beyond initial use before dropping off—a churn factor that inflates effective cost per retained user.

For example, imagine a mid‑size sportsbook offering a $50 “first deposit match.” If only one third of recipients place further wagers averaging $200 with an average house edge of 5 %, expected net revenue equals $200 × 5 % × ⅓ ≈ $3.33 per player—far below the upfront $50 outlay once churn is accounted for. Adding transaction fees (~2 %) elevates total expense beyond $52, highlighting why operators price loyalty rewards conservatively and hide true costs behind promotional language.

3. Regulatory Pressures and the Push for Cost Transparency

Across Europe and Asia, regulators have begun weaving cost disclosure into responsible‑gambling statutes. In Malta’s Gaming Authority framework, operators must submit annual “loyalty expense reports” that break down cash allocated to bonuses versus net gaming revenue (NGR). The UK Gambling Commission now requires “clear value statements” alongside any incentive advertising so players can compare promised benefits against actual monetary impact.

In Singapore—the jurisdiction most associated with searching best online betting sites Singapore—the National Lottery Board has issued guidance encouraging platforms offering loyalty schemes to publish conversion ratios (points ➜ cash) on their terms pages outright rather than bury them inside fine print.

These mandates force developers to redesign back‐end accounting pipelines: loyalty ledgers must trace each point from issuance through redemption while tagging associated overheads such as fraud monitoring labor hours or AML checks triggered by high‐value redemptions. As compliance costs rise, some operators opt for flat‐rate discount models over complex multi‑tier programs because they are easier to audit and present less ambiguity to regulators.

4. Building a True‑Cost Calculator: Core Data Inputs

Creating an accurate calculator hinges on three data families:

Player-level metrics – Total betting volume per session, average stake size, win/loss ratio (W/L%), session duration, device type (mobile vs desktop). These illuminate how much capital flows through each touchpoint and where points accrue most heavily.

Programme-specific variables – Point accrual rates per game category, redemption ratios (points ➜ cash), expiry windows, tier upgrade criteria; essentially every rule governing reward generation should be digitised for computational import.

Operational overheads – Marketing spend devoted exclusively to loyalty communication (email automation costs), technology maintenance fees for CRM integration modules (~15 % of IT budget), compliance labor hours tracked via ticketing systems; all expressed either as fixed monthly amounts or percentages of NGR.

A concise spreadsheet can combine these inputs using:

TrueCost = Σ(PlayerVolume_i × PointRate_i × CashValuePerPoint)
          + RedemptionCost
          + OverheadAllocation

4.1. Data Collection Best Practices

  • Capture raw wagering logs directly from game servers rather than relying on aggregated reports; this reduces latency errors.
  • Tag each wager with product code (slot ID, live dealer table) so point multipliers apply automatically.
  • Validate data nightly against payment processor statements to reconcile any mismatched deposits or withdrawals affecting net capital calculations.

4.2. Normalising Metrics Across Markets

When operating across jurisdictions such as Europe’s regulated markets and Singapore’s emerging online betting scene there are divergent tax regimes and RTP expectations:

  • Convert all monetary values to EUR using daily FX rates for comparability.
  • Adjust house edge figures by local statutory caps—for instance Singapore may impose higher minimum RTP on certain slots.
  • Apply uniform time buckets (e.g., weekly active days) so churn analysis remains consistent despite differing weekend gambling habits across cultures.

5. Case Study: Deconstructing a Mid‑Size Operator’s Loyalty Budget

Scenario: “BetPulse,” an online betting platform operating in Malta and Singapore with ~45 000 active users across both markets; average monthly NGR = €9 million; loyalty programme features three tiers as outlined earlier.

Step 1 – Gather Input Data
– Aggregate monthly wagering volume: €18 million
– Average point accrual rate: 0.85 point/€ spent
– Redemption ratio: 12 points = €0.30 free bet
– Tier distribution: Bronze 55%, Silver 30%, Gold 13%, Platinum 2%

Step 2 – Compute Direct Reward Liability
Total points earned = €18M × 0.85 ≈ €15.30M points
Monetary equivalent = (€15.30M ÷12) × €0.30 ≈ €382,500

Step 3 – Add Operational Overheads
Marketing allocation = €120,000; CRM maintenance = €80,000; Compliance labour = €60,000. Total overhead = €260,000

Step 4 – Factor Opportunity & Churn Costs
Assume redemption rate of 38 %; unredeemed points represent tied capital costing ~1 % interest annually → (€382,500*0.​38×€0.< span >001 )≈ €144;

Estimated churn loss = (€382,< span >500 </ span >×(1−0.​38))×€0.< span >05 ≈ €11 ,< span >? .

Step 5 – Summarise True Cost
True total expense ≈ €382 ,< span >500 + €260 ,< span >000 + €144 + €11 ,< span >? ≈ €642 ,< span >?

Insights:
– Loyalty accounts for roughly 7 % of BetPulse’s NGR—a figure comfortably above average industry benchmarks yet still sustainable given their robust profit margins.
– The Platinum tier consumes disproportionate resources relative to its user share; pruning its benefits could shave up­to €45k annually without materially affecting overall player retention.
– Aligning tier upgrades with responsible gambling checkpoints—such as mandatory self‑exclusion prompts after crossing £10k turnover—helps mitigate risk while preserving profitability—a practice recommended by resources like Puc Mn for operators seeking best practices without compromising compliance.

6. Leveraging Transparent Costs to Enhance Player Protection

When operators publish exact conversion rates between points and cash value inside their UI dashboards—as opposed to vague “value equivalent”—players gain actionable insight into how much real money lies behind each reward claim. This visibility empowers them to set personal limits based on true exposure rather than perceived freebies.

Data derived from true‑cost calculators can feed limit‑setting tools automatically: if calculated spend-to-reward ratio exceeds preconfigured thresholds (e.g., more than €150 spent per ₹200 reward), system alerts trigger mandatory pop-ups recommending session breaks or self‑exclusion links sourced from consumer protection bodies such as Puc Mn’s advice centre.

Furthermore,
– Risk flags: Sudden spikes in redemption frequency coupled with declining win ratios signal possible problem gambling behaviour; algorithms can then prioritize these accounts for outreach.
– Communication clarity: Displaying statements like “Your last £30 bonus equates to £27 actual play value after accounting for rollover” demystifies marketing jargon.
By grounding protective measures in hard numbers rather than abstract percentages researchers have found higher compliance among players who understand exactly what they are receiving versus what they are investing.

7. Future Trends: AI, Real‑Time Analytics,and the Evolution of Loyalty Economics

Artificial intelligence is poised to transform loyalty economics from static tables into dynamic ecosystems:

  • Predictive Modelling – Machine learning models ingest historical W/L ratios,
    session length distributions,
    and demographic markers to forecast each player’s lifetime value and risk profile simultaneously.
    Operators can then auto-adjust point multipliers—offering higher accrual during low‐risk periods while throttling rewards once volatility crosses predefined stress tests linked to responsible gambling limits.
  • Real-Time Personalisation – Streaming analytics enable instant recalibration of offers mid‑session:
    a poker player who just hit two consecutive large pots might receive an immediate “double points” nudge accompanied by a reminder about deposit limits.
    Such just-in-time interventions keep engagement high without overshooting exposure boundaries.
  • Regulatory Evolution – Anticipated EU amendments may require every promotional banner displaying bonus amounts also show a standardized “cost equivalence” metric calculated via approved algorithms similar to those described herein.
    Industry bodies are already drafting interoperable data schemas so platforms worldwide—including those hosting popular online betting apps—can exchange transparent cost metadata without proprietary lock‑ins.

Collectively these innovations promise smarter loyalty programmes that respect both profitability targets and player welfare—a balance increasingly demanded by authorities overseeing best online betting sites Singapore ventures.

Conclusion

Viewing loyalty schemes through a true-cost lens reveals that every point issued carries measurable financial weight—from direct cash liabilities through hidden opportunity expenses and regulatory compliances costs. Operators who embed transparent calculators within their tech stack not only sharpen profit forecasting but also furnish players—and watchdog entities like Puc Mn—with concrete data needed for responsible decision making. As AI-driven analytics mature and legislators tighten disclosure mandates, openness will shift from competitive advantage toward industry baseline expectation. Stakeholders eager eitherto implement such calculators or audit existing programmes should begin by mapping granular wagering data onto standardized cost formulas today; doing so lays groundwork for safer gaming ecosystems tomorrow.”

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