Mashable recently reported that “ad fraud could become the second biggest organized crime enterprise behind the drug trade”. The Association of National Advertisers (ANA) estimates that advertisers will lose $7.2 Billion to bots globally in 2016. Over half way through the year, and likely about $4 Billion of ad fraud later, there has been no shortage of articles about the matter and initiatives attempting to resolve the issue.
Yet over a year after the Association of National Advertisers (ANA) and the American Association of Advertising Agencies (4A’s) formed a joint task force to investigate ad fraud and transparency issues, the advertising community is still grappling with this complex and ever-evolving problem. Stephan Loerke, Chief Executive of World Federation of Advertisers, was quoted at Cannes Lions last month, saying “ad blocking, ad fraud, transparency, ad viewability – all these are pretty fundamental questions that we need to be addressing as an industry collectively...”
According to David Perez, co-founder and former CMO of Convertro, “fraud has been a concern since the advent of digital marketing... What is new is simply the fact that, unlike during the original Internet heyday, we now have the technology to identify and put a stop to fraud before it does too much damage.”
How A Good Attribution Solution Is Inherently Anti-Fraud
Attribution technology uses science to determine what media are driving purchases, so advertisers no longer need to guess or waste their budget on channels that aren’t performing. With AOL Convertro’s attribution solutions, any bot or fraudulent activity not explicitly filtered by our software is heavily penalized by algorithmic attribution, due to showing very little or no ROI for that particular source.
Proportional crediting is key. In proper attribution modeling, credit is assigned proportionally to each touchpoint according to its influence on the customer’s purchase or conversion decision. The goal of attribution is to determine which touchpoints are producing a positive result, and, by using the cost of each touchpoint, an advanced attribution system can then show which touchpoints are profitable. This means marketers are inherently steered-away from fraud in a good MTA model, as fraudulent sources are basically “kicked out” of the credit path, since they don’t contribute to the final conversion event. For example, banners stuffed below the fold won’t drive conversions, due to lack of viewability, making viewability an inherent part of our solution.
It’s not just the monitoring or analysis of the customer path that is useful; advertisers can use the Spend Recommendation tool within the dashboard to allocate funds away from any underperforming or unnecessary channels.
Many retargeting solutions can be over-credited in last-touch attribution, because of their very nature of targeting an existing “hot lead” which may or may not have needed the additional touchpoint to convert. Touchpoints that don’t actually drive conversions are automatically not credited for the sale, regardless of their position as first, middle or last touch. Advertisers leveraging Multi-Touch Attribution (MTA) can effectively drive ROI and optimize efficiently even if campaigns are not on a conversion-based pricing model.
Knowing the complexity of organizational navigation, AOL Convertro offers Change Management and strategic guidance as part of the solution. Our strategy team is composed of industry veterans who can provide counsel on all aspects of the process: data policies, implementation, and more. We enable scenario planning for both MTA and UMAP clients and set out a strategic roadmap to ensure success.
In addition to helping your organization adapt to these important changes, we build custom attribution models based on client specifications. If you would like to define and use a customized attribution model, you can let your assigned Client Services representative know.
This post was written by Sr. Product Marketing Manager, Maryam Motamedi.
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