- Human Defense Platform
Many marketers don’t see marketing fraud as a large problem in the industry—a perception that’s partially the result of how difficult it is to identify the effects of these elusive attacks. But its impact can cost your organization millions. Here's how to get protected.
Marketing fraud is a relatively new and often misunderstood form of cybercrime. Unlike ad fraud—in which cybercriminals use bots to drum up false ad clicks—marketing fraud targets the entire life cycle of a digital marketing campaign. Sophisticated bots that can uncannily model human behavior are deployed to engage in click fraud, lead fraud, retargeting deception, and competitive assaults. These bots can be used to secure payment for fraudulent data research, sales leads, or ad referrals, resulting in squandered marketing budgets and lost revenue. According to our Bot Baseline Report, fraudulent marketing schemes may be responsible for the loss of 24 percent of a campaign’s ad budget. Fraud can also impact a company’s market advantage as bad bots dilute the efforts of targeted campaigns and real customers are converted by competitors.
Marketing fraud is very difficult to identify, which means losses often go undetected and lost revenue is never retrieved.
Rival companies use bots to boost traffic and engagement metrics so that their websites and apps are more attractive to agencies and advertisers. They also use bots to directly target competitors’ giveaway campaigns, extracting cost-per-form (CPF) payouts and weakening customer databases. In some cases, sophisticated bots have been used to create look-alike audiences that are then sold to brands trying to expand market reach.
The digital marketing industry spent a third of a trillion dollars in 2019, and that number is likely to have increased in 2020 as companies shifted to more digital customer interactions during the COVID-19 crisis. This makes marketers a prime target to fraudsters because fraud follows the money.
How does marketing fraud impact the bottom line? Marketing fraud tactics siphon off ad spending, waste budgets and time, skew metrics, and infect marketing databases with false names and leads. Many companies are unaware just how many fake contacts have infected their first-party databases, which means they’re spending money to generate false contacts—and then continue to spend money to target them.
A luxury automotive brand HUMAN worked with once launched a large lead generation campaign through social media, search, mobile, and display advertising, but found that it failed to boost sales conversion rates. HUMAN’s analysis discovered that roughly 17 percent of new traffic driven to the company’s site was fraudulent. The brand was wasting $36,000 a month attracting these bots. After HUMAN helped redesign the campaign’s strategy and tactics, there was a 600 percent increase in digital conversion rates.
As bots have become better at mimicking human behavior, HUMAN has developed sophisticated tools that can detect automated engagement quickly and effectively. HUMAN’s BotGuard for Growth Marketing examines traffic data and uses machine learning to determine “bot or not” activity in real time. It then deploys downstream decision-making tools that automatically prevent these non-human actors from engaging with ad targeting and marketing systems.The workhorse of HUMAN’s anti-marketing fraud defense, the Human Verification Engine, is a cutting-edge detection technology that combines technical evidence, machine learning, and a capacity for continuous adaptation that can identify traffic as “human or not” with speed and accuracy—without creating real human user friction.
HUMAN’s anti-marketing fraud protection is proactive, not just reactive. HUMAN’s Satori Threat Intelligence and Research Team seeks out large-scale attack networks, which has resulted in the taking down of multiple bad actors every year. These efforts reduce the number of criminal networks in operation while providing the security team with additional information on bot development—which HUMAN can reverse engineer into its detection systems to help further improve BotGuard’s ability to identify which of its clients’ users are bad bots, and which are the real-life customers they hope to reach.