OnHub: TikTok Fraud Prevention

Block fraud clicks and optimize the Tiktok ads budget

Click tracking

Audience targeting

Fraud detection

Accurate reporting

Summary reports

Ad optimization

Conversion maximization

Settings customization

About OnHub: TikTok Fraud Prevention

Launched Sep 30, 2024

Built by NOVAON DIGITAL JOINT STOCK COMPANY

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Description

Block fraud clicks to automatically optimize the Tiktok ads budget and maximize revenue

The fraud filter is designed to detect fraud clicks in TikTok advertising campaigns. By analyzing user behavior and location, it blocks and prevents ads from being shown to suspicious audiences. This helps automatically target the exact audience on TikTok, optimizing both expense and campaign effectiveness. By eliminating fraudulent activity, it maximizes conversion rates and ensures accurate reporting, enabling users to make informed decisions without being misled by distorted results

Customize behavior and location settings to detect fraud clicks from TikTok ads
Prevent displaying ads to fraud audiences and distribute to exact target
Track details of each click, including IP address, country, operating system,...
Generate reports summarizing total and fraud clicks over specific time periods
Provide extensive reports to optimize the effectiveness of advertising campaigns

Pros

Effectively detects and blocks fraudulent clicks on TikTok ads, helping optimize ad budget
Analyzes user behavior and location to prevent ads from being shown to suspicious audiences
Automatically targets exact audiences, improving campaign effectiveness and conversion rates
Ensures accurate reporting, enabling better decision-making by avoiding distorted results
Allows customization of behavior and location settings for personalized fraud detection
Tracks detailed information of each click, such as IP address, country, and operating system
Provides comprehensive reports on total and fraudulent clicks over specified time frames
Generates extensive reports to aid in optimizing advertising campaign effectiveness

Cons

May require advanced understanding or setup to effectively customize detection settings
Potential for false positives, possibly blocking legitimate clicks and affecting reach
Reliance on accurate location and behavior data, which may not always be precise
Complexity might be challenging for users not familiar with digital advertising tools