The Fraud Console shows ad networks the source of data abnormalities in campaign traffic in real-time before they pay for it and helps save on falsely attributed installs
Ad networks and marketers are up in arms against fraud traffic and are using abatement tools to save a lot of time and money by quickly identifying fraud traffic and not paying for it.
In the wake of this trend, Kochava, a holistic measurement solutions provider for connected devices, is now extending fraud abatement suite, Fraud Console , to ad networks, giving them the same access as marketers in fighting mobile ad fraud. It enables them to detect falsely attributed installs in real-time. The first ad networks to use this tool include FeedMob, Taptica, and Yeahmobi.
“The Fraud Console creates a valuable, neutral transaction space for both marketers and networks,” said Charles Manning, CEO, Kochava. The tool has changed the way business is done between marketers and ad networks. Through the use of 11 different real-time reports in the toolset, marketers can identify illegitimate traffic during a campaign flight, before paying for it, instead of post-campaign.
Networks see the same data points as advertisers
Marketers’ success with the Fraud Console has led Kochava to provide access to ad networks too. Until this development, the ad networks were not aware of the fraudulent traffic they carried. Only marketers had the advantage of detecting fraud in their campaigns which was after networks had already paid their sources for inventory while upholding any agreed upon make-goods with the marketer. Through the Fraud Console, networks earn marketers’ trust and also reduce time and money spent on make-goods and chargebacks by using fraud abatement tools.
Mobile Ad technology firm, Taptica’s GM – U.S., Galia Reichenstein, said, “The Kochava Fraud Console gives us a shared platform with our advertisers to look at the same data points in real time and make smarter decisions. It intuitively harnesses extensive data points, allowing for easy analysis that takes our mobile campaigns to a new level.”
Advertisers are paying for the right traffic
Game Developer, MobilityWare, has integrated the suite into its regular campaign analysis. Fraud Console caught networks that were stealing attribution from rightful networks of MobilityWare. “We were getting hit with extra costs from having an exorbitant high click volume and very few of those resulted invalid installs,” said Issei Shimizu, Senior Manager of User Acquisition, MobilityWare. “The Fraud Console shows us not just the data abnormalities in our campaign traffic but also where that activity is coming from. Using the Fraud Console has saved us thousands per month from falsely attributed installs.”
A month-long analysis of MobilityWare’s campaigns using the Fraud Console showed that approximately 5% of their total installs were from blacklisted sites. Of those, 80% were organic.
Proactive tools to filter fraudulent traffic
Marketers are just beginning to explore the benefits of the Fraud Console, which includes a customizable Global Fraud Blacklist. The Blacklist excludes known fraudulent entities recognized by the Kochava algorithms that have surpassed a certain threshold. Use of Traffic Verifier allows marketers to determine how to attribute unverified traffic.
Kevin Grimes, Ad Operations Manager, DoubleDown Interactive, said: “The Kochava fraud reports provided the solid evidence necessary to secure significant refunds for bad traffic. Now, with Traffic Verification and the Global Fraud Blacklist, we have two great front-end tools to help avoid the issue altogether.”
Fraud Console flags abnormal data
The Fraud Console reports flag abnormal and potentially fraudulent activity pulled from a network’s traffic for review. The reports include sites and device IDs with high click volumes, discrepancies in app launch times or locations, advertisement stacking and unverified app store installs and receipts, among other tactics.
“The Kochava algorithms scan the breadth of Kochava accounts. Our system records and passes billions of data points and recognizes when abnormal activity fits the definition for fraud and flags that data for review. This is where customers can take advantage of the learning of other accounts across the ecosystem,” said Manning.