The Dark Side Of Mobile

stevelathamData-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Steve Latham, CEO at Encore Media Metrics.

First, here’s the good news: Mobile will be the freight train that drives the media industry.

Now, the bad news: The lack of data availability and transparency will cost marketers billions of dollars.

Since the iPhone’s 2007 introduction, the media industry has deemed every year to be “The year of mobile.” It took longer than expected to mature, but desktop’s awkward little brother is about to dwarf big bro. It surpassed desktop in consumption in 2014 and will surpass it in spending in 2016. EMarketer predicts mobile media will reach $65 billion by 2019, or 72% of digital spending.

But as we move toward a “mobile-first” world, we need to address a very big problem: We still can’t accurately measure performance. The ability to target customers in new and innovative ways outpaces the ability to measure effectiveness of those tactics.

Mobile’s Measurement Problem  

The digital media ecosystem was built on cookies to target, track and measure performance. Cookies are imperfect but good enough to develop accurate insights into customers’ journeys. Using cookie data to assemble and model conversion paths, marketers can use fractional or multitouch attribution to optimize media campaigns much more effectively than with last-click metrics.

In mobile, third-party cookies are blocked on most devices and privacy regulations limit device tracking. Consequently, traditional ad servers are limited to reporting on last-click conversions where possible.

For brands seeking to drive app installs, mobile attribution companies like Kochava, Tune, Appsflyer and Apsalar can track the click that led to the download in Apple or Google stores. Some are working on post-click and post-view reports, but these will be of limited help to advertisers seeking actionable insights.

The lack of mobile data means advertisers cannot quantify reach and frequency across publishers. They also cannot measure performance across publishers via multitouch attribution. The cost and complexity of device bridging further obfuscates user-level engagement.

Rays Of Light

Mobile data and measurement challenges won’t be solved overnight, but a convergence of factors point to a less opaque future. Here are my predictions:

  1. Ad servers will adapt to device IDs

Conceptually, a device ID is not unlike a cookie ID, privacy issues notwithstanding, but it takes time and money to introduce a cookieless ID system. Following the lead of Medialets, traditional ad servers will introduce their own anonymous IDs, instead of cookies, that map to probabilistic and deterministic device IDs. Like cookies, these IDs will allow them to log user-level data that can feed fractional attribution models. We’ll probably see some early announcements before the end of year, with more to come in 2016.

  1. Data unification will become readily available

To date, demand-side platforms, data-management platforms, tag managers and data connectors have fixated on using data to help advertisers target, retarget, cross-sell and remarket. The same data that is used to drive revenue can also be used to connect user-level data for measurement purposes. Companies, such as LiveRamp, Signal, Exelate and Mediamath, are already unifying data for analysis. More will follow.

  1. Device bridging will become ubiquitous

To date, connecting devices across publishers has been a luxury afforded by the largest advertisers. In time that will change as wireless carriers, and possibly some publishers, offer device graphs exclusive of media and standalone vendors, such as Tapad and Crosswise, will reach economies of scale. At the same time, ad servers and data connectors will build or license device graphs and offer bridging as an extension of their service.

As ad delivery, data management and device bridging become more integrated, costs will come down and advertisers of all sizes will be able to measure engagement across devices.

  1. Mobile attribution vendors will be forced to evolve

As ad servers and data connectors incorporate device-level conversions in their data sets, including app installs, mobile attribution companies will have to expand their offerings or risk becoming redundant. Some may stick to their knitting and delve deeper into mobile analytics and data management. Others may pivot toward media and expand into desktop or addressable TV. Others may just be acquired. Regardless, it’s unlikely this category will remain as-is for much longer.

  1. Last-touch attribution may finally go away.

We’ve been predicting the end of the click as a key performance indicator for years. But inertia, apathy and a continuous stream of shiny objects have allowed last-touch metrics to survive while brands and agencies fought other battles.

Now that we’ve tackled video, programmatic, social, native, viewability, fraud and HTML5, the new focus on insights and big data may finally drive the roaches away. The click will be hard to kill, but as we become smarter about measurement, it will become much less visible.

Follow Steve Latham (@stevelatham), Encore Metrics (@encoremetrics) and AdExchanger (@adexchanger) on Twitter.

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  1. Steve, I don’t think anyone in this day and age views last-click or last-view attribution as an ideal solution – unfortunately it’s a necessary evil for app-focused marketing today. The reason mobile app attribution companies ‘like Kochava, Tune, Appsflyer and Apsalar’ leverage last-click/view models is because the largest mobile media sources (together accounting for well over 50% of global app traffic) provide only last-click (sometimes last-view) data to their exclusive set of integrated 3rd-party attribution tracking partners, by policy. This is obviously different than the desktop you’re used to, where cookies track all views/click touch points throughout a user’s path to conversion or non-conversion.

    You’re an expert, so I’d be interested in your take: how would a fractional/algorithmic/causal attribution model account for such data incongruence – complete click/view paths from a few media channels, complete click paths for other channels, and solely last-click data for a majority of traffic? I’m no data scientist, but my understanding is that such a lack of uniformity in the dataset would skew results in favor of those partners reporting more touch points, and unfairly diminish the contribution from those publishers/networks without complete tracking.

    None of your ‘Rays of Light’ change the root cause: mobile media providers do not enable the tracking required for improvements to mobile advertising measurement.

  2. Justin- good question. Quick answers are:
    1. Mobile attribution (conversion) vendors can get device-level impression and click data from the “Open” publishers (i.e. Excluding the Dark pubs like FB and Google).

    2. Armed with conversion path data from the a Open pubs, You can back into the contribution or lift from The dark pubs by isolating them in controlled tests.

    Everything is measurable if you are willing to do the work.