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Maximize Your ROAS: Cutting-Edge Attribution Strategies for Mobile Gaming

Last month, the ad network, AppLift hosted the webinar, “Breaking Down Fraud Perceptions,” in which our CEO, Charles Manning, participated. An insightful Q&A ensued that we thought worthy of publishing to provide clarity as the industry matures in fighting mobile ad fraud. The Q&A is reprinted below.


 

Q: Does Kochava publish their Blocklist?
We do not openly publish the Blocklist, but it is available in one of two ways:

  1. Existing Kochava customers can use the Blocklist by activating the feature directly in our UI.
  2. Publishers who want to use Fraud abatement tools during “pre-bid” efforts can license our Fraud technology (Kochava Fraud Console for Networks) and they will be given a real-time API access to the Blocklist.

Q: Why are attribution partners afraid to name fraudulent affiliate networks?

I can’t speak for other attribution companies, but in the case of Kochava, we would rather focus on those publishers who have demonstrated the absence of fraud versus focusing on those who have more of it. We talk about how our role is to “let the data drive the story”—not to label a particular ad network. Because our customers have the Fraud Console, they know which networks are the worst offenders, and in this way, Kochava gives them a competitive advantage (over those using tools other than Kochava). Adding to this point, one of my biggest complaints about the other attribution company “performance leaderboards,” which are published quarterly, is that those leaderboards are never qualified against fraudulent traffic. As such, it is doing a major disservice to the industry by celebrating “high performing ad networks” without accounting for the fraud that partly makes up those performance stats. Because of our leadership in fraud monitoring and abatement, we have a different view about performance, and it’s driven around true traffic, accurately attributed conversions and, ultimately, ROAS.

With regard to standards, I believe the best thing that can be done to fight fraud via “standards” is to publish actual package names and web page locations versus site ID aliases under each ad network. This would stop bad sub-publishers from jumping around to various ad networks to masquerade as authentic media sources.

Q: Given the prevalence of fraud via all ad networks, campaign optimization has turned into a game of whack-a-mole. Given that, why should an eCommerce brand continue to deploy resources and budgets in networks versus deploying their entire budget towards Apple Search Ads, Facebook, or to a lesser extent Google universal app campaigns (UAC)?

Because of scale and because of cost. Smart money finds audiences across the full ecosystem of inventory. Smart money also has tools to help them with automated fraud abatement, measured incrementality, and an understanding of reach versus frequency when hitting audiences. These are the things that an eCommerce brand cares about.

Q: If you are detecting networks that have fraud why do you still support them? Why do you not ban them from being measured on your platform?
It’s not about the networks as much as it’s about the sub-publishers. The solution is full transparency across all ad networks with package name or domain associations versus site identifier aliases.

Q: Someone said earlier: “lots of red flags but good purchase rates.” Be careful when looking at attribution system data only, while measuring purchase data. We saw cases where those attribution systems got compromised and those purchases couldn’t be validated with the App Stores. The purchases never happened.

Kochava provides out-of-the-box receipt verification on all installs and in-app purchases. This is an important signal to determine real purchase data versus spoofed.

Q: If you have the information about the approximate fraud percentages of networks, what is the reason behind not outing them and letting the advertisers know?

The Kochava Fraud Console very much shows those networks and related sub-publishers that are offenders. While we don’t publish this publicly, our advertisers know and it impacts their buying patterns.

Q: If someone is sending 15% to 20% (fraudulent activity) each month why continue to work with them due to their loose policies?

We see these percentages “without our industry leading fraud abatement technology.” The data shows that it comes from various sub-publishers, and while we don’t have a way to validate the identity of those publishers, without full transparency from networks, we protect our customers from their (the sub-publishers’) behavior when they use Kochava. Given the protection we provide, I suspect that the rest of the marketers that are not currently using Kochava will be the most impacted. This is because we are not openly publishing stats and only providing our insights to our customers—the impact will be on those marketers using other tools that do not protect them. We have been told by an agency customer that when using Kochava versus using another measurement tool (two separate marketer clients)—they were only able to hit their KPIs with Kochava on the exact same inventory and in the exact same vertical. This highlights the point about how the toolset is a key difference maker for the marketer that wants to be efficient and scale.

We show our customers the irresponsible sites, enable our customers to remove those sites from the attribution waterfall, and clearly highlight which networks they’re associated to via our dashboards or reports. We even provide real-time alerting where customers can be alerted as soon as bad behavior starts. If we took the position that we simply wouldn’t work with any ad network that has any history of fraudulent behavior from one of its sub publishers, there would be no ad network to buy media from. The key here is having the right tools to protect your ad budget while enabling the marketer to push for scale. Kochava provides this.

Q: It is obvious that my account manager is able to see the extremely low conversion rates but not warn us until we raise the fraud flag. (No problem with the deductions also.) This is particularly hard because I am working with over 20 sources, and it sometimes gets overwhelming to figure out and catch them all. Why do you think networks wait for the acquisition managers to raise the flag?

Kochava is licensing the Kochava Fraud Console for Networks to address this problem. My personal belief is that many ad networks don’t have the tools, and they’re relying on display fraud abatement tools which really don’t do a good job on mobile. We’re trying to solve this problem by providing this capability. For those ad networks that license the Fraud Console for Networks, we provide an extra badge for that ad network in our Media Guide so that marketers know that they don’t have to use the Blocklist on those networks because the network is taking the steps themselves.

Q: Is there any other way to figure out the incent exploit (e.g., Android video networks like AdColony and Vungle) other than checking the cohorts?

Blended incent traffic with non-incent traffic is something we detect.