I was recently barraged with messages from industry colleagues about the news of Uber suing Fetch for ad fraud. I wasn't surprised, to say the least, as I was waiting for this knee-jerk reaction from them. I was privy to what happened two months ago, thanks to a meeting I had with a friend of mine.
My first reaction was to jump and tell the world "I told you so; now see what happens!" After I mulled over it a bit, I realised the need of the hour was to actually gain more awareness about what ad fraud is rather than be taunting.
Understanding Ad fraud better
In simple words, anytime a brand spends INR 100 for advertising and a lesser amount reaches the actual consumers, for whatever reasons, it's considered fraudulent. Unlike popular belief that all ad frauds are related to non-human traffic, it can very well be the result of human error or judgement. Ad fraud impacts efficiency by as high as over 50 percent if not systematically monitored and stopped. What marketers need to understand is that there are multiple types of ad fraud and no single solution to address all of them. It becomes important for brands to understand this space better, identify which type of fraud has the maximum impact on their business and then implement the right solution.
There are eight or more different types of ad fraud that brands should be aware of in today's rapidly evolving ecosystem. Some are complex while others are straightforward. Here is a look at a few types of ad fraud:
Ad stacking is one of the oldest tricks in the book. This form of fraud happens when ads are stacked or placed one on top of another, resulting in impressions and advertising outflow, but no real impact for the business. The popup ads from the good old days were highly susceptible to this.
Making advertisers think fake sites are those of reputable publishers; this is primarily seen in ad network and programmatic buys. In the recent past, a Russian hacker group made away with millions of dollars in a week replicating popular domains in a programmatic funnel.
MRC guidelines state that 50 percent of the pixels of the creative need to be viewed for 1 second for banners and 2 seconds for a video for the ad to be considered as 'viewed'. Now imagine when the entire ad is squeezed into a space of just 1x1 pixels. That's what pixel stuffing is all about and how it impacts advertising spends.
Bots are non-human user agents producing HTTP web traffic. Illegal bots not only impact viewability but also affect clicks, installs, security, customer data and so on.
A few years ago Facebook removed millions of profiles as they were recognized as the work of click farms. There are also cases when millions of clicks are received from Bangladesh, China and African countries which are a result of click farms, mobile farms, etc. These are low-cost resources which are employed just to clicks on ads, like posts, and install mobile apps.
Google takes a large piece of the pie when it comes to the advertiser budget. In such a scenario, hackers or fraudsters create fake websites using very relevant keywords (stuffing) to create high relevance in SERP. Once the brand ads are placed on these keywords, the fraudster walks away with money for irrelevant clicks.
Fraud can also occur in the implementation of the campaign by targeting wrong demographics as well as geographies leading to higher clicks but no ROI. This is primarily human error from the implementation team.
When an ad is served but not seen it is considered invalid or fraudulent. In India, the average viewability ranged from 40 percent to 80 percent depending on the report and publisher you are referring to. Either way, it is safe to assume that a brand loses money due to low viewability rates in India.
Besides these ad frauds, there is another level of fraud in the form of inventory buys, which is primarily a trading practice followed by various vendors who buy and sell inventory at different rates. This also needs to be checked. To put it in the words of ex-digital media chief who wrote anonymously on DIGIDAY, "It's all one massive arbitrage system".
Fighting ad fraud is complex
The first step is to accept that no brand is safe against this menace and to start considering the cost of fighting ad fraud as an investment to safeguard spends rather than an extra marketing cost. Fighting ad fraud in silos is not enough. It is equivalent to washing away your spends. It needs to be a comprehensive approach as listed below:-
A holistic fight against ad fraud includes usage of tools as well as manual intervention:
1. Verification tools: Brands need to consider verification tools like Sizmek and MOAT in their marketing mix as these safeguard the investment against bots.
2. Target match tools: Nielsen's DAR is an effective tool that identifies the discrepancy it's targeting during the campaign and thus improves on efficiency.
3. Viewability: Tools like Sizmek, MOAT and IAS can help brands identify the current level of viewability for a campaign. It is estimated that an increase of 15 percent in viewability gets a positive 10 percent increase in business.
4. Website bot detection tools: Comscore VCE, Omniture or an in-house tool that we have developed, also help brands identify the level of bots and their sources.
5. Media Audit: Buying into the tools is important, but getting everything audited by a third party ensures that all the implementation is on track and there is a positive impact on efficiency.
It is important that a brand create guidelines to ensure that all partners working with it are compliant with the tolerance level that is set by the brand against ad fraud, viewability et al. The process and guidelines need to be checked on a periodic basis as the ecosystem itself is evolving at a rather fast pace. Fraudsters are getting smarter and the solution that has been implemented may become redundant in a year. In other words, brands need to have an agile approach towards fighting ad fraud.
(The author is founder and chief executive officer, What Clicks, a digital media audit and strategy firm)
For feedback/comments, please write to firstname.lastname@example.orgFirst Published : October 06, 2017