Conversion fraud

Conversion fraud is a deceptive practice where bad actors artificially inflate conversion metrics on digital advertising campaigns. This type of ad fraud occurs when fraudsters complete fake conversions like form submissions, purchases, or sign-ups. The goal is usually to drain advertising budgets or manipulate performance data.

How conversion fraud works

Fraudsters use various techniques to generate fake conversions. They might employ click bots, click farms, or automated scripts. These tools can fill out forms, create accounts, or simulate purchases. The fraud is designed to look like legitimate customer actions.

Common types of conversion fraud

  • Form filling fraud: Bots automatically complete lead generation forms
  • Account creation fraud: Mass creation of fake user accounts
  • Purchase fraud: Simulated transactions that never complete
  • Call fraud: Automated systems making fake phone calls
  • App install fraud: Fake installs and activations

Impact on businesses

Conversion fraud can severely impact digital marketing efforts. It wastes advertising budget on fake leads. It skews performance metrics and makes campaign optimization difficult. Many businesses make poor decisions based on fraudulent data.

Signs of conversion fraud

Several red flags might indicate conversion fraud. Watch for unusual spikes in conversion rates. Be suspicious of conversions happening at odd hours. Look for patterns in form submissions or similar user data.

Prevention methods

Businesses can take steps to protect against conversion fraud. Using CAPTCHA systems helps block automated form submissions. IP validation can identify suspicious traffic patterns. Fraud detection tools can monitor for unusual behavior.

Connection to click fraud

Conversion fraud often works alongside click fraud. Fraudsters first generate fake clicks on ads. They then complete fake conversions to make the traffic look legitimate. This combination makes the fraud harder to detect. It also increases the potential profit for fraudsters.