Fraudster (n.) – a bad guy scheming up new ways to steal your marketing dollars, right now.
Ad Fraud is a growing issue. Just how much of an issue isn’t exactly known –estimates of fraudulent traffic range anywhere from 3% to 57%* – but it’s clear that any brand, or agency, that isn’t on the lookout is setting themselves up for trouble.
At Ovative Group, we believe that one of the best ways to protect yourself from ad fraud and the nefarious villains who commit it is to carefully and intentionally equip yourself with the measurement tools required to identify and reduce fraud from your media portfolio.
Why You Should Care
If you’re purchasing programmatic display media at scale, the question isn’t, “Am I paying for fraudulent impressions?”, but rather, “How many?”. This is not to say that display is not a worthwhile investment. Instead, it is saying that your company can only benefit from taking precautionary action against such fraudulent activity.
The presence of ad fraud can reduce the return on ad spend (ROAS) of your media and even negatively affect the bottom line. It can also inflate your cost-per-conversions significantly. This is particularly egregious for display media when evaluating performance on non-enterprise KPIs. If optimizing to click-through, site activity, or app download KPIs, it becomes likely not only that fraudulent behavior will go undetected, but that you may be inadvertently increasing the amount of fraud being committed against you.
Types of Ad Fraud
To protect your brand against ad fraud, you need to have a good understanding of what types of ad fraud exist. Broadly speaking, ad fraud falls into two categories:
- Impression fraud: any scam designed to show ads fraudulently
- Click fraud: any scam set up to drive fraudulent traffic (this includes click farms, fake app downloads, or fraudulent account creation)
Unfortunately, a permanent solution for eliminating fraud isn’t as simple as designing mechanisms that look for fraud tactics or behavior typical of botting. Every time a new technical methodology is designed to catch bots, bot designers go the extra step to make their bots harder to detect. As machine learning and artificial intelligence continue to evolve, it is unlikely that the ability to detect bot behavior will outpace the ability of bots to simulate human behavior any time soon.
How to Protect Yourself: Revenue-Based Enterprise Measurement
Fraudsters operate by one simple, constant principle: the desire to make money (by generating fraudulent consumption of ad inventory). Because fraudsters are constantly coming up with new ways to commit fraud undetected, the way to beat them is to evaluate your media in such a way that it doesn’t make financial sense for fraudsters to design their bots to go undetected.
Sound complicated? It’s simple. By using an enterprise measurement solution, you’re able to evaluate and optimize your media at a granular level, using revenue-based KPIs. Fraudsters would need to generate your business revenue at a profitable ROAS to go undetected.
Weeding fraud is a natural consequence of granular enterprise optimization. When you discover which media sources have the most significant amount of fraud, you are able to reallocate some of the money spent there to a more effective source. This process helps you simultaneously combat fraud while optimizing your media to the enterprise. Simple testing can be completed to determine which source will give you the highest return. At Ovative Group, we refer to this as incrementality testing.
In order for your fraud prevention mechanism to work effectively, you need access to the following:
- Granular reporting – Sufficient granularity at which media is being optimized to, such that transitioning media buys from fraudulent sources can be done with precision & low friction
- Customer-level enterprise measurement – The capability to tie enterprise performance to media exposure at the customer-level. This is easiest to accomplish for clients with a large e-commerce presence, or for clients that have a conversion event directly associated with a revenue impact.
Other strategies to detect and prevent ad fraud include:
- Demand traffic transparency from display partners (pre-campaign)
- Manually review traffic that appears too good to be true
- Build website whitelists and blacklists (mid-campaign)
- Partner with a fraud-prevention tech company, such as DoubleVerify or WhiteOps
The reality is that some level of fraud is always going to exist, and that’s okay. The key is taking the proper precautions and reinvesting your money where it matters. This process should be as integral to your campaign as setting effective KPIs.