Rich Kahn is CEO and Co-Founder at Anura.io, a company he launched in 2017 to combat the kind of ad fraud he’d been observing for years across his own ad network. Today, Anura.io is one of the most capable ad fraud detection plans in the market, and so I was glad to score an interview with Rich to trade notes on ad fraud, how it’s evolving, the kind of costs it exacts on marketers today, and how AI may be strengthening the hand of ad fraudsters, even as it bolsters the efforts of ad fraud detectors such as Anura.io.
As Rich notes, ad fraud is a huge threat to every facet of a marketer’s operations. As noted in Anura.io’s own literature, “digital ad fraud accounts for an average of 25% of all paid online traffic, posing a substantial financial burden to businesses. In addition to the hard cost sunk in wasted advertising budgets, the hidden costs are even higher. Ad fraud diverts precious resources to pursuing bad leads and future marketing campaigns skewed by error-riddled analytics of past performance. It can also pose a huge risk to a brand’s reputation and their compliance with TCPA (Telephone Consumer Protection Act) regulations, which can result in hefty fines and legal fees.”
My interview with Rich covers many topics that will be of interest to anyone doing digital marketing today, especially those whose budgets are spent across programmatic advertising channels. These topics include:
- The challenge of identifying fraudulent impressions in programmatic advertising, given that the sheer magnitude of data makes it difficult to detect invalid clicks.
- How many of today’s ad fraud solutions suites are limited in their ability to detect fraud because of the way they use pre-bid scanning to classify traffic in real-time.
- How fraudsters are increasingly using advanced bots, malware, and human fraud farms to bypass detection methods.
- Why some advertisers are willing to accept a certain level of fraud, viewing it as a cost of doing business.
- Why small advertisers have a hard time seeking funds from large tech platforms when incidents of ad fraud are detected.
- The importance of verifying ad fraud detection software’s accuracy and not trusting it solely on the basis of claims made by its representatives.
- The challenges faced by ad fraud software vendors in terms of keeping up with new browser versions and their impact on fraud detection.
- How AI is allowing ad fraudsters to increase the output of bots and other systems designed to defraud advertisers, even as it is also making ad fraud detection systems more efficient and accurate.
