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03/15/17

Best Practices for Combating Click Fraud [Data Series, Part 2]

In our second post on digital advertising best practices, we’re tackling click fraud.

As digital advertising spend continues to climb, so do concerns about how much of that spend is being wasted on targeting bots. According to the Association of National Advertisers (ANA), click fraud is estimated to cost advertisers more than $7B globally in 2016. White Ops, Inc. and the ANA released a study estimating that while bots accounted for 17% of programmatic placements, the percentage ranged from 3% all the way to 31% depending on the campaign. So it’s important to monitor and block bot traffic to keep your campaigns closer to the smaller end of the spectrum.

Approach #1 – User agent

The simplest approach to monitoring bot clicks is to block clicks generated by self-proclaiming bots. Some bots — such as those adopted by Google — scour the web to collect information. These bots often purposely communicate to other parties that they are bots through their user agent, a means by which a web browser tells a website information about itself. The common convention is to include the term “bot” in your user agent when employing a bot. Other terms we’ve found useful to monitor include “crawler” and “spider”.

Approach #2 – Click-through rate

One of the most effective approaches to monitoring bot clicks is using click-through rate. Humans typically click on less than 5% of display ad impressions they observe. If you notice an IP address clicking on ads an inhumanly large percentage of the time, that’s a clear indicator that the IP has been compromised by a bot. However, humans may open up a page with a few ads, click an ad, then end their browsing session. Because of this, in order to confidently use click-through rate for bot detection, some minimum threshold of clicks per time period must first be observed.

Approach #3 – Frequency

Another commonly used bot monitoring approach is actions — such as clicks — per time period. This is useful for covering cases where bots mimic human click-through rates but instead rely on volume to create sizable fraud. Humans typically click on less than 10 ads in a given minute. If you notice a cookie clicking many times per minute, that’s a clear indicator that the cookie has been compromised by a bot. Keep in mind that IPs may comprise a large number of devices, so attempts to count frequency by IP would need to be done conservatively.

In part three of the series, we’ll provide an in-depth review of how only half of display ads are ever viewed and the corresponding impact on ad performance for vendors who charge for or attribute to unviewed ads.

Data Best Practices, a 4-part series:
The Importance of Data Fidelity in Advertising [Part 1]
Best Practices for Combating Click Fraud [Part 2]
Why to Incorporate Ad Viewability Into Your KPIs [Part 3]
Attribution Is Key to Successful Performance Marketing. Here's Why [Part 4] - Coming soon!

Categories: Performance Marketing