The Hidden Cost of Ad Fraud

Digital marketers have dealt the cost of ad fraud with bots and click-farms for years. Ad fraud creates frustration for companies who don’t know how to work around it. This comes at a massive cost both financially and strategically. But there are solutions marketers can use to ensure clicks are real people.

What is ad fraud?

Ad fraud, including bot usage, click-farm traffic, domain spoofing, and geo-masking, has a significant impact on creating erroneous data. Fraud operations have presented businesses and marketers with issues for years. They continue to grow more sophisticated, bypassing some of the industry’s most advanced filters and detection strategies. A few common motivations for fraudsters include improving rankings for social media accounts using fake engagement; inflating website traffic to attract buyers and advertisers; depleting competitors’ advertising budget and weakening their position in the market; and generating ad revenue by artificially boosting KPIs on the ads on their websites.

Ad fraudsters have a variety of technological tools at their disposal to accomplish their business goals. Bots are created by the thousands using emulation software to act as fake devices with spoofed identifier information. Click-farms are operations that recruit and compensate real people to click on ads. These individuals typically operate as many as dozens of devices at one time. Automated filters often fail to recognize such activity as fraudulent. Why? Because the traffic is not fake, but is also not coming from genuine customers.

Domain spoofing is used when one device is spoofed to resemble multiple devices. When spoofed devices interact with ads or other content, their actions count as multiple devices. This damages the quality of the data. Geomasking is another way of obscuring information. It occurs when the geographic location of an identifier is changed from a less desirable location to a highly-desired one. This form of ad fraud is particularly significant in targeted marketing campaigns that focus on attracting an audience from a certain geographic location.

The costly impacts of ad fraud

Ad fraud is one of the most significant issues facing the adtech industry today. It costs companies billions of dollars. In fact, the Association of National Advertisers’ data suggests that in 2019, ad fraud caused a global $5.4 billion loss in return on advertising spending. Not only does ad fraud cost companies money, but there is also an impact on productivity and decision making. Bad data wastes time and inhibits marketers from making sound strategic and tactical decisions.

BDEX analyzed more than 1 billion device identifiers sold in the U.S. market and found:

  • 20 percent of Mobile Advertising IDs (MAIDs) sold in the U.S. data market are invalid
  • 21 percent of Hashed Emails (MD5s) are linked to more than 10 MAIDs
  • 2 percent of consumer IP addresses sold in the U.S. are from non-U.S. countries, U.S. governmental IP addresses, or are otherwise invalid
  • 1.1 percent of email MD5s sold in the U.S. are invalid

Marketers can no longer fully trust their advertising data. The cost of ad fraud is too high. It’s less clear than ever who is a real person and whether you are tracking them properly. However, when you do, there are significant benefits as we found eliminating bad consumer data can improve Return on Advertising Spend (ROAS) by as much as 43%.

A major global media network engaged with BDEX to improve the quality of its internal identity graph used by 13 company-owned ad serving, streaming and attribution platforms. By improving the quality of their network and removing fraudulent data, it saved as much as 50% off its annual identity data budget.

In another instance, a top-tier data management platform engaged with BDEX to combat the ongoing propagation of bad identity data linked to ad fraud via bots and click farms. It removed bad data by validating all identity data, which led to saving hundreds of thousands of dollars.

Fighting bad data with better data

Fortunately, data can combat ad fraud because it has evolved as well. Marketing teams can now implement big-data tools with artificial intelligence (AI) to analyze their data and gain a new understanding of buying behavior as it happens. Existing data can be enriched by aligning with firms that can provide quality-scored data that is evaluated for fraudulent characteristics. This ensures campaigns and ads reach real target customers. Marketers can and should regularly check IP addresses for multiple hashed emails (MD5s), which can indicate fraudulent activity. Verifying data across multiple channels can also help prevent bad data from impacting the rest of the data pool.

False identifiers help create bad data. So being careful about which data sources companies use is a key step in preventing bad data from wasting time and marketing dollars. This is especially important to consider when working with data resellers. If a downstream data source or reseller has bad data, then the whole data pool is corrupt.

Ad fraud is not an issue that will ever fully go away. But the impacts only increase when companies ignore the problem. Overall, the best way to avoid the negative impacts of ad fraud is to have a plan, be proactive about analyzing your data, and use technology to inform your decisions. Your ad spend will thank you.