About MOAR

MOAR is a digital company focused on creating and marketing online products, operating primarily through a dating affiliate program in the adult industry. As a performance-driven advertiser, the company acquires traffic through multiple affiliate networks and compensates partners largely on a per-lead basis, rewarding actions such as email signups and subscriptions.

Operating in a high-volume affiliate environment means traffic quality is directly tied to business performance. Accurately identifying legitimate users while filtering out fraudulent or low-quality traffic is a critical part of day-to-day operations.

The challenge: Fraud and limited traffic visibility

Like many advertisers operating within affiliate networks, MOAR faced ongoing fraud challenges and limited visibility into their traffic. With traffic passing through multiple partner layers, MOAR had limited context about their users, making fraudulent and automated activity difficult to identify until after it impacted revenue and partner ROI. Much of this traffic consisted of bots, scripts, or repeated account creation, generating cost without real business value.

Prior to implementing Fingerprint, MOAR's fraud analysis relied on manual investigation, including exporting lead data, reviewing patterns, and diagnosing performance anomalies. The approach was effective but time-intensive.

At the same time, fraud tactics were becoming more sophisticated, including bot traffic, repeated device usage, proxy and VPN manipulation, and inconsistencies between IP and device signals. These patterns were difficult to evaluate quickly and provided limited diagnostic insight.

As volumes scaled, investigation overhead began to impact efficiency. MOAR needed a solution that improved fraud visibility and reduced detection and investigation time without increasing operational burden.

Why MOAR chose Fingerprint

As more of MOAR's affiliate traffic began arriving through backend API integrations, their previous fraud tool could no longer properly scan or analyze most of their leads. As a result, the ability to monitor and analyze traffic coming through these integrations became a critical requirement.

Fingerprint was selected for its ability to integrate cleanly into MOAR's infrastructure and support its operational needs. Key decision factors included:

• Seamless integration into their backend lead flow
• Fast implementation with minimal engineering overhead
• Competitive pricing relative to traffic volumes
• Clear fraud indicators and reasoning, not just risk scores

Rather than replacing internal reporting systems, Fingerprint was introduced as a high-signal device intelligence layer that strengthened the company's existing fraud analysis processes.

Operational efficiency through device intelligence

MOAR uses Fingerprint as an important part of its broader traffic quality analysis and decision-making processes. Device-level signals associated with elevated risk — including automation, repeated device activity, proxy and VPN usage, and traffic inconsistencies — help the team evaluate campaigns and affiliate partners more efficiently without disrupting existing workflows.

By reducing the time spent on manual investigation, Fingerprint enables faster analysis and supports continued scaling as traffic volumes grow. With plans to expand into more preventive use cases, MOAR sees Fingerprint as a trusted partner in maintaining control over fraud risk while supporting long-term growth.

Improved traffic visibility also helped MOAR better identify high-quality traffic sources and support more efficient scaling across trusted partners.

Scale your traffic with confidence.
Add device intelligence to your fraud stack and gain deeper visibility into traffic quality, fraud risk, and user behavior. Get started with Fingerprint.