Why We Must Fight the $7.2B Mobile Ad Fraud Threat
Ad growth on mobile has been steadily outpacing TV and desktop over the last few years, with mobile ad spends estimated to reach a whopping $70 billion by 2018.
But with losses estimated at $7.2 billion in 2016, the value of mobile advertising is threatened by the expanding and evolving nature of ad fraud.
The financial consequences are arguably only of secondary importance.
Ad fraud destroys advertiser value by grossly distorting and corrupting vital data that drives campaign decisions.
Taking a reactive, after-the-fact “detection” approach to mitigating fraud is not only time consuming, but an increasingly futile exercise in salvaging already spent marketing budgets.
Instead, ad networks and attribution partners should lead a proactive fraud prevention approach. The challenge is creating the truly cross-ecosystem effort needed from advertising and discovery networks, as well as mobile measurement and attribution players alike, to eliminate the threat.
A Proactive Fraud Prevention Approach
1. Proactive Efforts by Ad Networks
Marketers today worry about the authenticity of the media that they are purchasing, and the subsequent user interactions that take place once they’ve been acquired.
Given that only a portion of fraudulent traffic is identified at a later point in time with requests for reimbursement, networks must look closely to offer the unique selling proposition of “we have fraud-free traffic.”
Ad networks should proactively be on the lookout for any activity that is anomalous with normal behavior.
Catching this potentially fraudulent behavior requires a constant emphasis on data quality, and checks for reasonable behavior. This ensures fraud prevention at an ad request level to protect the value of marketing spends from both human error and malice induced errors.
For this to work, we’re proposing ad networks and attribution partners open themselves up to greater transparency and a willingness to be assessed by fraud reporting tools.
If more data attribution platforms are public about ad networks cooperating, this may convince networks to be proactive in their own preventative ad fraud initiatives, and ultimately, this will help all ad networks stay ahead of the game.
2. More Integrated Data Streams
The competitive mobile marketplace makes acquiring accurate, independent measurement-tracking and attribution data mission critical. Marketers need this data to make decisions and maximize return on investment.
As such, you need seamless integration of data streams between advertisers and networks, and data sharing agreements with third-party data protection safeguards and advertiser controls, i.e. a consistent feedback loop for negative, fraudulent traffic. This would deliver improved performance and optimization for marketers.
Both networks and tracking partners can protect marketer interests with strong collaborative efforts by initiating the shift towards a mobile ecosystem devoid of abuse and fraud.
Abuse of any form is usually detected by corroborating multiple data points around any given transaction. Ad networks can observe users and publishers at a fairly large scale — beyond the confines of any single ad campaign — to strengthen the learning process.
Trackers are in a similar position with their ability to observe user behavior from the first click, all the way into post app install events, across a wide variety of applications independent of the ad network.
This puts ad networks in a position to cut-off supply exhibiting bad behavior and trackers to decline attribution against a suspicious activity.
Having both data streams in place, and the negative feedback loop consistently deployed, would provide a comprehensive defense against abuse and invalid activities at all stages in the funnel, protecting and preserving advertiser value.
3. Non-standardized Fraud Filters
We’re in a territory that’s so new, that we haven’t yet defined standardized methods of identifying mobile ad fraud. Individual efforts by marketers, ad networks and attribution partners to troubleshoot will leave all parties scratching their heads, without identifying the problem.
All parties must be transparent about their filters and how they work.
We know this is a lot to ask, as fraud algorithms also represent significant investment into research and software development. Such friction can be reduced by having dialogues directly between analytics outfits and advertising partners.
This is the general experience we’ve had in our own conversations between adjust and InMobi, and we hope to expand those initiatives to further analytics solutions as well as advertising partners.
Combine Efforts for a Clean Mobile Economy
With ad fraud posing a billion dollar threat to every advertiser in the mobile industry, every player in the ecosystem must work together in battling fraud effectively. Otherwise, fraudsters will continue to exploit gaps in the system to perpetuate their attacks.
Thankfully, networks and tracking systems are accustomed to sharing conversion data, and with a push from advertisers, we can expect more collaboration and forward movement among advertising networks and attribution platforms in the future.
As the lead fraud specialist with mobile attribution and analytics company adjust, Andreas focuses on the dedicatedfraud prevention initiative, and finding the patterns and flaws that enable adjust to identify fraudulent traffic in real-time. Well versed in large-scale data analysis, Andreas brings more than eight years of experience working with advertisers in fraud prevention at multiple European leading ad networks including Zanox, Trademob and Glispa.
Arun Pattabhiraman is the vice president and global head of Marketing at InMobi, a mobile advertising and discovery platform. Arun is passionate about mobile and the internet and is fascinated by the myriad ways in which they continue to transform our lives.