Promotions, referral incentives, and coupon codes have become essential acquisition tools for fintech companies, marketplaces, delivery platforms, mobility apps, e-commerce and lately AI companies as well. When deployed intelligently, they accelerate growth and help companies win competitive markets. But these same incentives create a powerful economic opportunity for users and fraudsters who learn to exploit them.

Promotion abuse rarely triggers alarms in the early stages. On dashboards, it looks like success: new signups spike, referral usage grows, redemption rates climb, and acquisition costs appear to fall. Only later, when cohorts fail to convert, budgets are exhausted, and fraud signals surface, does the real cost become visible. In many cases, what teams initially celebrate as “high-performing” campaigns are actually driven by fake accounts, synthetic identities, and opportunistic behaviors designed to drain promotional value.

This article provides a strategic and technical overview of promotion abuse, how to recognize emerging patterns, the economics behind the problem, and the defensive architecture companies can put in place. It also explains how identity verification, particularly phone number verification via SMS/OTP, anchors many effective prevention strategies, and where a platform like Prelude fits within that architecture.

What Promotion Abuse Really Is? Why It’s Often Misunderstood ?

Promotion abuse encompasses any behaviour where users leverage incentives, promo codes, referral bonuses, free credits, sign-up rewards, in ways that fall outside the intended rules. The technical loopholes differ across industries, but the motivations are consistent: extract maximum value with minimal intent to become a genuine user.

There is a grey zone between clever bargain hunting and abuse, but three criteria typically separate the two:

• Intent: Is the goal to explore the service or purely to monetize promotional value?

• Scale: Is this a one-off edge case or a systematic, repeatable pattern?

• Eligibility: Does the behavior violate written rules or reasonable expectations?

From a risk and compliance perspective, promotion abuse sits adjacent to fraud. It may not always involve financial theft, but its economic and operational impact is real and in many companies, far greater than the visible loss associated with payment fraud.

Where Promotion Abuse Appears? Why Certain Promotions Attract It?

Although any incentive can be misused, abuse tends to concentrate in promotions that are:

• high in monetary value,

• transferable or resellable,

• loosely targeted, or

• easy to redeem repeatedly.

For example:

• Promo codes and coupons intended for specific segments but shared publicly

• Welcome bonuses that can be exploited by creating multiple fake accounts

• Referral programs where self-referrals, referral loops, and organized “invite farms” emerge

• Free trials are reset through new accounts, especially now with many AI services where users get free prompts.

• Loyalty programs where points can be manufactured or arbitraged

When incentives are highly liquid such as ride credits, promo cash and free deliveries, organised groups often industrialise heir exploitation, using virtual devices, pools of phone numbers, and automation tools to scale their operations.

A Closer Look at Common Abuse Patterns

Multiple Accounts and Synthetic Identities

The most widespread pattern involves users creating multiple accounts to repeatedly benefit from “new customer” promotions. Techniques range from simple email variations to more advanced approaches involving virtual numbers, VPNs, device emulators, or even synthetic identities. At scale, these operations are indistinguishable from coordinated fraud.

Referral Abuse

Referral programs are especially vulnerable because they reward both the inviter and the invitee. Abuse appears in several forms: self-referrals, reciprocal referral loops, and referral farms that generate large networks of low-value accounts. These inflows mimic viral growth but rarely convert into long-term revenue.

Coupon Leakage and Misuse

Discount codes intended for targeted users often leak via social media, affiliate sites, or employee channels. Once exposed, they can circulate indefinitely, enabling ineligible users to claim excessive value or stack codes in unintended ways.

Opportunistic vs. Organised Abuse

Opportunistic users may push the boundaries for small incremental gains. Organized fraud rings, on the other hand, use automation, coordinated devices, and identity manipulation to extract hundreds of thousands in promotional value. Both require different preventative strategies, but both must be addressed.

The Real Cost of Promotion Abuse

The impact of abuse extends far beyond direct financial losses.

1. Inflated Acquisition Costs

Promotions intended to acquire new users instead subsidize fake or duplicate accounts. CAC appears favorable but is artificially deflated by users who never intended to engage. Especially now, with many AI companies giving prompts as a free trial, the cost is a real hard expense compared to typical SaaS server costs.

2. Distorted KPIs and Misleading Cohorts

Promo abuse corrupts core growth metrics. Fraudulent or low-intent cohorts distort activation rates, retention curves, and LTV calculations. Leadership teams may scale campaigns that appear effective but are fundamentally unprofitable.

3. Customer Experience and Governance Risks

As abuse grows, companies often respond with stricter rules or verification that frustrate genuine users. In regulated sectors, the misuse of incentives can even intersect with KYC and AML concerns, particularly when incentives involve wallet credits or financial reward structures.

Case Studies: How Abuse Materialises in Practice

Food Delivery: A Referral Program Spiraling Outward

A major food-delivery platform launched an attractive referral program that initially appeared to be a success. Signups increased and referral usage surged. But fraud teams later noticed clusters of correlated accounts, one-and-done usage patterns, and referral instructions circulating on forums. After tightening device checks and clarifying eligibility rules, the company recovered an estimated $300,000 in prevented losses, according to a case study by Ravelin.

Crypto Exchange: Duplicate Accounts for Bonus Extraction

A leading global crypto exchange faced inflated registrations and repeated bonus redemptions. Investigation revealed synthetic identities, bypassed KYC controls, and a network of duplicate accounts exploiting sign-up incentives and referral rewards. A case study from Shufti Pro outlines how introducing device intelligence and mandatory OTP verification tied to biometric validation sharply reduced multi-accounting and restored reliable cohort quality.

E-Commerce: Industrialized Abuse During Flash Sales

Flash sales and cash-back multipliers attracted organized fraud rings using device farms, virtual numbers, VPNs, and automation scripts. Vendors such as TrustDecision and Incognia describe how combining device fingerprints, behavioural anomalies, and referral-graph analytics enabled platforms to disrupt these networks and recover promotional profitability. What initially looked like explosive campaign performance was, in reality, a concentrated form of promotion fraud.

These cases underscore a central pattern: abuse looks like growth until you zoom in.

Detecting Promotion Abuse: 5 Signals That Matter

Prevention begins with identifying the signals that differentiate legitimate users from coordinated abuse. These signals often reveal themselves across several dimensions:

Account Creation Patterns

Velocity spikes, multiple accounts from the same device or IP range, or unusual time-of-day patterns are early indicators of manipulation.

Device and Network Characteristics

Shared device IDs, emulator fingerprints, datacenter IPs, or high-risk ranges are common in industrialized abuse.

Geolocation and Behavioral Consistency

Users registering in one region but behaving like a cluster in another often signal coordinated activity.

Referral Network Structures

Dense, circular referral graphs are highly uncommon in normal customer behavior and are strong predictors of abuse.

Payment and Chargeback Signals

Users who exhibit heavy promotion usage and elevated chargeback rates often belong to fraudulent cohorts.

Individually, these signals are weak. Combined, they form a strong predictive model.

Building a Real-Time Detection Pipeline

Stopping abuse requires decisions made at the right moment in the user journey. Most companies intervene at four critical points:

1. Account creation

2. Referral acceptance

3. Promo code application

4. First order or transaction

A robust detection pipeline typically includes

Rules and Thresholds

Simple controls such as maximum accounts per device, per number, or per IP block low-effort abuse and opportunistic behavior.

Risk Scoring

Aggregating device reputation, IP risk, behavioral patterns, referral graph anomalies, and number intelligence into a unified score helps determine if a promotion should be granted.

Machine Learning Models

ML assists in identifying subtle, evolving patterns that static rules may miss, particularly in large networks.

Feedback Loops

Confirmed abuse cases feed back into rules, models, and dashboards, continuously improving detection accuracy.

This combination forms the backbone of most modern fraud defense systems.

Designing Promotions That Are Harder to Abuse

Technology is only half of the solution; promotion design matters just as much. Several principles consistently reduce abuse:

• Limit stacking of multiple high-value incentives

• Define “new user” precisely, including device, phone number, and payment method

• Set caps per user, household, and device

• Shorten promotion windows to reduce industrialized exploitation

• Design referral programs with clear rules on eligibility, bonus issuance, and fraud checks

• Keep terms and conditions explicit, reducing ambiguity and “gray-zone” behavior

The strongest programs are those designed with fraud risk in mind from the beginning and not bolted on as a reaction after losses appear.

How Top Apps Confirm User Authenticity Without KYC

Identity verification has always been essential, and it remains a critical counterweight to multi-accounting and synthetic identities. Among the lighter-touch methods available, phone number verification using SMS OTP stands out as one of the least invasive and most broadly effective. In the AI era, where synthetic identities can be generated in seconds, SMS OTP is making a comeback because it relies on real, physical telecom infrastructure. It ties digital identity to something AI cannot instantly fabricate: a real phone number on a real network, providing a lightweight yet highly reliable signal of user authenticity.

Verifying a phone number introduces several advantages:
• Ensures the user controls a real, reachable number
• Blocks many disposable or one-time-use numbers
• Raises the cost of creating mass fake accounts
• Creates a persistent, low-friction binding between user and identity

But this step is only effective if your OTP provider can detect SMS fraud attacks such as SMS pumping. Delivery alone is not enough. A modern verification flow requires a provider that can:
• Spot unusual OTP request spikes
• Identify suspicious routing patterns
• Flag or block potentially fraudulent SMS requests before they become costly

When paired with device intelligence and risk scoring, SMS OTP becomes a strong anchor point for preventing promotion abuse and limiting synthetic account creation. It does not eliminate abuse entirely, but it significantly increases resistance at scale.

This is where a provider like Prelude fits into the verification layer. Prelude manages the infrastructure behind the scenes: delivery quality, compliance such as 10DLC and DLT, routing intelligence, and fallback channels. It also provides fraud-detection signals that highlight abnormal traffic patterns, ensuring that verification flows are not only fast and globally reliable but also protected against modern fraud mechanisms.

FAQ: promotion abuse prevention

What is promotion abuse?

Promotion abuse refers to any behavior where users exploit marketing incentives (promo codes, sign-up bonuses, referral rewards, free trials) in ways that exceed their intended use or violate the terms of the offer. It often involves multiple accounts, fake identities or organized schemes to extract as much promotional value as possible without genuine engagement with the service.

How is promotion abuse different from traditional fraud?

Traditional fraud often focuses on direct financial theft (e.g. payment fraud, chargebacks), whereas promotion abuse targets marketing incentives and acquisition budgets. However, both may share similar techniques: fake identities, bots, stolen credentials, device emulation. In many organizations, promo abuse is handled by the fraud or risk team because its financial impact can be significant.

Which promotions are most exposed to abuse?

Any high-value, easily transferable or stackable incentive is at risk: large sign-up bonuses, free credits convertible into goods or services, referral programs with cash-equivalent rewards, and promo codes that can be widely shared. Offers with broad eligibility and weak verification are particularly attractive to organized abusers.

How can I detect promotion abuse in my programs?

Start by monitoring signals such as account creation velocity, the number of accounts per device or phone number, abnormal referral graphs and unusually high promo redemption rates. Implement real-time rules and risk scores at key steps (sign-up, referral acceptance, promo application) and compare the behavior of users who mostly use promotions with that of your regular customer base.

How does SMS/OTP verification help prevent promo abuse?

SMS/OTP verification ensures that each account is linked to a real, reachable phone number. This raises the cost and complexity of creating multiple fake accounts, especially at scale. When combined with device fingerprinting, IP analysis and behavioral monitoring, OTP checks become a powerful barrier against promo abuse while remaining relatively frictionless for legitimate users.

Conclusion

Promotion abuse is often invisible until it becomes expensive. It can drain acquisition budgets, distort analytics, and create operational pressure across marketing, risk, finance, and support. But it is neither unpredictable nor unmanageable.

Companies that effectively counter promotion abuse tend to follow a consistent playbook. They design incentives with risk controls in mind, monitor the right behavioral and technical signals, enforce identity verification, and invest in real-time decisioning capabilities. They integrate verification infrastructure through reliable providers such as Prelude directly into their sign-up and promo flows, raising the cost of abuse without creating friction for legitimate users.

The goal isn’t to eliminate abuse entirely. It’s to ensure that promotion programs reward real customers, not exploitation. Protection isn’t a constraint on growth; it’s a prerequisite for sustainable growth.