5 Questions with JC Goodrich, VP of Marketing at White Ops
Datorama sat down with JC Goodrich, VP Marketing of White Ops, the global leader in human verification technology. White Ops’ constant innovation in the fight against ad fraud and other forms of automated fraud has been instrumental in the industry’s understanding of and prevention of cybercrime against marketers.
Q: White Ops has published some groundbreaking research on ad fraud, both at the industry level and on specific threats such as Methbot. Can you give background on why this issue is so critical to advertisers today?
A: The biggest problem for advertisers is that ad fraud makes their marketing spend ineffective. Simply put, bots don’t make purchases, and every dollar spent on them is wasted, creating a drag on return on advertising spend (ROAS). This is also difficult for advertisers to spot because even though bots don’t make purchases they do try to mimic human behaviors as best they can by copying cookies, watching videos, etc. The outcome is fraudulent activity which suggests that campaigns are performing well and tricking marketers to re-invest their media dollars. By exposing invalid traffic, marketers can effectively evaluate true campaign performance.
Q: Why is online advertising such a target for cyber criminals?
I think it’s the perfect storm of three factors that provide a reasonably high potential benefit at fairly low risk and investment:
- Market Size: A huge market that’s growing quickly, cybercriminals can profit and still fly somewhat under the radar
- Value Chain Complexity: A complex value chain where cyber criminals can hide in between the layers of monetary exchange
- Low Operational Costs: an even half-technically savvy cybercriminal can get a botnet up and running with very little effort, beat some detection and make a few bucks
Q: How can marketers prevent ad fraud?
A: Our biggest insight in this year’s Bot Baseline report was that sophisticated ad fraud is still getting by conventional detection solutions. There are some fairly obvious practices that advertisers and their agencies can do to create more certainty they are reaching humans. For example, being careful with “too good to be true” programmatic deals – meaning that if the price on your buy seems far too low, there’s good reason to suspect it is fraudulent. That sort of common-sense fraud prevention is low hanging fruit – but other, more sophisticated cyber-criminals can be harder for the garden variety marketer to identify and avoid. This is, of course, why I work at White Ops. Our main focus is making sure our detection accuracy is world class and can continue to detect – and defeat – the world’s most sophisticated automated fraud operations. Remember, our job is to actually defeat and take down the fraud vs. just detect and build reports.
Other tips for marketers looking to mitigate and/or prevent sophisticated ad fraud include:
- Work with best in breed technology to measure all of your media across all platforms and channels.
- Utilize impression level data to run in depth analysis of high SIVT hotspots.
- Leverage curated blacklists to optimize your targeting strategies.
- Ask your buy side platforms if they have evidence based prevention technology to protect your campaigns.
Q: How does the Datorama and White Ops partnership provide value to marketers?
A: By combining White Ops’ ad fraud measurement with the monetary value of those impressions in Datorama, advertisers get a more accurate financial view of their campaigns. At White Ops we generate impression level determinations, but don’t attach the value of the impression to our dataset. Datorama is able to connect the dots here (among many others) and provide marketers with a more holistic view. Advanced marketers might even combine human verification with spend data and conversion data to discover the safest inventory sources for their buys.
Q: How does ad fraud differ on video and mobile?
We tend to see the highest fraud rates on video and the lowest on mobile. The reason has to do with the benefit cybercriminals see (i.e. the CPM of the medium) and the difficulty in attacking the device. The threat models we see in mobile are more difficult to crack and the CPMs haven’t risen enough to see massive cybercriminal investment. They’re too busy building bots to defraud video spend!