It's Time for a Consistent Cross-Media Measurement Solution

12月 31, 2017

Since the advent of digital advertising, agencies and brands alike have searched for a way to measure campaign success across delivery platforms. The vastly different delivery objectives of media like TV, digital, and even print and radio have made it nearly impossible to find a unified solution.

For example, traditional TV is measured through metrics like ratings, share, and GRPs. However, this is not an effective way to measure digital - the goal of a traditional TV-based campaign is awareness, and at any given time, a brand knows what the total viewing audience is. For digital, goals are often more lower-funnel and engagement-focused, so total views, click-throughs and completed views are more widely accepted.

A solution may be coming soon. Recently, Adweek published an article discussing Unilever's plan to create a cross-media measurement model aimed at measuring campaign effectiveness. It is supported by top tech players like Facebook, Google, and Twitter and involves Kantar and Nielsen as measurement partners, and the system will attempt to bridge the siloed gap between the TV and digital ecosystems.

This is long overdue - in the last five years alone, there's been an explosion in digital advertising that has seen it surpass broadcast TV as the top medium in terms of ad spend. We've also seen that there are 6.58 connected devices per person, and 88% of TV viewers report simultaneously using a digital device while watching TV according to Nielsen's Q2 Total Audience Report. Users are viewing content on many devices; it's time for the ad industry to present a consistent measurement solution.

Here are three problems that must be addressed for a successful cross-media measurement model:

Better multi-channel attribution models: While 87% of U.S. companies utilize digital "last-click” attribution models, just 58% use multichannel models according to eMarketer Pro. With brands becoming more cognizant of the full consumer purchase journey, last-click attribution leaves a lot to be desired. With multi-channel models, brands can see every phase that the consumer went through on the path to conversion and pull insights from this data.

For example, consumers could be buying on their desktops, but a multichannel model could show that this happened far more often if ads were shown on Connected TV first and then mobile devices prior to the desktop ad coming into play. Last-click attribution doesn't bring enough insight, and data-driven marketers agree that new measurement models must address this.

Accurate audience profiling: This relates to multi-channel attribution models - knowing where consumers are seeing ads allows brands to de-duplicate reach and know that they are reaching unique users with their campaign. This also allows for more successful sequential messaging, which GlassView creative research has shown drives a +3.4x increase in purchase intent.

Better Organizational Communication: We live in an age of rapid digital disruption. According to Accenture Research, $1.97 trillion will be spent on digital transformation initiatives in 2022, and the ad industry is not immune. We've seen the rapid growth of CTV and OTT in the past couple years, and we've started to see ads on IoT devices as well.

This has caused gaps in communication across departments, especially in large organizations where sharing of data could diminish the roles of some departments in the company. There must be company-wide unification to successfully create an accurate cross-department measurement strategy, as the organization as a whole will benefit in the long-run.

With the biggest players in advertising getting in on the action, a cross-media model could soon be on the horizon - let's hope the ad landscape still looks similar when it's completed.