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    Measuring Post-Click Events: Best Practice Against “Fat-Finger Syndrome”

    Adriana Ullivarri
    Posted by Adriana Ullivarri on December 17, 2014

    Mobile marketing is a medium that is still considered to be quite new in comparison to more traditional mediums like the more established TV and online. As such, it is normal to feel some uncertainty or trepidation when marketers choose to invest in mobile marketing. The market’s lack of maturity means that there is a real coexistence of efficient and trusted solutions alongside some others which may be less proven or less appropriate to the reality of the mobile ecosystem.

    Often, a change of perspective is required to fully understand much of the mobile space; from the opportunities that the new formats present, to the pricing models that can provide a better fit for specific requirements and budgets. It is not appropriate to simply imitate models that have been applied in the online environment, because browsing the Internet from a mobile device is a totally different experience. In this context, the “fat-finger syndrome” – a phenomenon that we´ve come to recognise within the mobile advertising space – should be taken into consideration: Often users click on banners when they have absolutely no intention of doing so.

    Studies conducted over the last two years have claimed that up to 40 per cent of mobile ad clicks are either fraudulent or accidental, and have suggested that more than half of those are a result of fat finger syndrome. Another study found that just 12 per cent of smartphone users ever click on an advert intentionally and only 6 per cent actually go on to purchase following the interaction.

    A lot has been written about this “syndrome”, and often to the detriment of mobile advertising as a whole. It is true that it describes a reality that needs to be taken into account when we talk about mobile advertising, but the good news is that while this “syndrome” is maximised by the use of media buying technologies that just optimise CTRs, it also can be minimised by implementing the appropriate technology instead.

    We now have the capability to use technology, not only to measure impressions and clicks, but also to learn about user behavior with a more holistic approach. We can use advertising formats that require a “double click” or that include a distinct call to action, such as native ads, which reduce the fat finger errors. And, above all, we can measure what users do after they interact with banner adverts, and work with programmatic media buying platforms which use algorithms to take into account that all-important post-click behavior.

    There are technology platforms today, like mediasmart, that can track accurately almost any post-click event: from calls to a call center, to visits or registrations in a website, or installs and use of apps, etc. If a programmatic platform buys media in real time, impression by impression, depending on the probability each impression has of turning into a post-click interaction, by definition, it will not buy those impressions that generated non-intended clicks, simply because these clicks will rarely be followed by any interaction other than the closing of the ad.

    For example, we have seen campaigns with an airline driving flight ticket purchases though an app, or campaigns where a car manufacturer drives complete video views by unique users, in which certain publishers have been naturally “selected out” by the media buying algorithm due to low performance, in spite of very good CTRs. This is a clear indication of publishers or advertising formats with a high rate of unintentional clicks.

    In summary, the fat finger syndrome is a real issue, particularly in the mobile advertising world, and especially for platforms that only optimise CTR – which, precisely because of this syndrome should not be the sole indicator of success for any campaign. But the industry has now progressed. It is now a problem that can be minimised as much as to make it almost insignificant if you use the appropriate technology, or work with providers with the proper technology.

    Topics: attribution