The industry has been talking the talk on cross-screen advertising for some time now, but we’ve yet to see anyone truly walking the walk. However, there is light at the end of the tunnel, as Nick Reid, Managing Director UK for TubeMogul explains. Measurement, fragmentation and the plethora of teething problems will soon be a bygone memory. Nick will be speaking on day one of New Video Frontiers, London, Oct 20th-21st 2015, and this post is sponsored by TubeMogul.
Today, cross-screen advertising refers to the ability to plan and buy advertising across screens and formats and accurately measure reach, frequency and impact in a transparent and effective way.
It sounds amazing – but we’ve been eyeing this pie in the sky for some time now.
What has changed?
The Challenge: Fragmentation Across Viewers and Devices
The reality is that more consumption methods have been introduced in the last five years than in the past 35. Everyone knows that mobile consumption is increasing and ad spend is lagging – but not everyone knows that even though live TV is declining, over-the-top (OTT) viewership (content streamed from connected TVs, gaming consoles and devices like Roku) is poised to explode.
The Solution: Measurement has Finally Caught Up
There are three approaches to verify identities cross-screen:
● Panel-based. This approach leverages machine-learning techniques to marry multiple data sets from third-party firms like Nielsen, enabling brand advertisers to more accurately measure reach and frequency within – and across – channels, including TV, desktop and mobile. These techniques allow them to identify their target audience that was not exposed to a linear TV advertisement and retarget them digitally, improving incremental reach.
● Probabilistic. Most advertisers currently employ this methodology for cross- screen audience targeting. Companies like Tapad and Drawbridge provide device association data, matching desktop cookies to other desktop cookies as well as to mobile device IDs. These likely provide extremely good results (90%+ accuracy) at the household level.
● Deterministic. Using information provided by an individual like a login or email address to verify a user’s identity with certainty. Companies like Google, Facebook, Twitter and Pandora can do this because they have registration data.
To be exceedingly clear, it’s still early in the first period. While there are some interim solutions for graduating beyond reach and frequency and measuring viewability and ROI, there is no industry standard – and there likely won’t be for some time. But enough progress has been made over the course of the last six months that any marketer wondering “How do I reach my audiences and optimize my media spend to efficiently drive sales?” should expect, at the very least, compelling offerings that help them:
1. Measure true audience reach and frequency across all channels and screens
2. Make targeting data actionable by deploying across all environments
3. Provide the ability to optimise based upon media consumption across environments
We’re approaching a world where viewability, suspicious traffic, ad blocking and all the other headlines du jour take a backseat to the truly important issue: “How do I know my ads worked? How can I replicate whatever did work with the least effort and lowest cost?”
We think that the ability to accurately plan media and reach audiences across screens will be a critical component to answering those questions.
