Marketing is undergoing a monumental shift as third-party cookies are phased out, and the spicket on mobile data is down to a trickle. For most marketers, this ever-changing privacy and identity landscape is leading to seismic shifts in how marketers look at attribution and measurement.
Fortunately, technology companies are investing heavily in alternate identity solutions to be the backbone of future attribution and measurement platforms. In fact, according to the American Marketers Association, over $2 billion is slated to be invested by a host of players to help solve the impending measurement conundrum as cookies and device data are all but phased out.
Identity and measurement bracing for impact
The real impact won’t be felt until 2023 when Google starts phasing out cookies. But, even now, changes led by Apple across both devices and Safari are putting marketers on their back foot as they scramble to decipher attribution and conduct effective measurement studies.
Success in this new unchartered world of measurement will rely on identity and measurement companies to work together to understand channel mix contribution better and devise new tools and methods to associate and attribute conversion data accurately. This already daunting challenge is poised to get exponentially more difficult as the channel mix expands, and tracking signals look less like a spoke and wheel and more like a spider’s web.
In this new web-like framework without cookies, marketers will depend heavily on identity and measurement companies to map, ingest and correctly assign credit to all the different modes and channels in a marketer’s advertising arsenal. At the core of all this, marketers, identity providers, and measurement teams are huddling to find news ways and new IDs to identify, track and make sense of every channel’s contribution to a marketers internal and external channel media mix.
Overcoming identity and measurement obstacles
Right now, that aspect is becoming increasingly opaque with severe limitations for deciphering when a particular person has viewed an ad, let alone assigning the correct attribution by channel. As part of that $2 billion dollar industry investment, though, a whole host of long-standing measurement players and new entries are making headway.
The Prohaska Group, a New York-based digital advertising consultancy, is leading the charge to create a landscape of attribution and measurement companies. Working with Prohaska, the below graphic is a snapshot of a larger measurement landscape The Prohaska Group will be releasing later this quarter.
While Technology companies like those listed here are peddling fast to come up with alternate solutions for measurement and attribution, it’s important to note that according to a recent IAB research study, only 34% of marketers are currently delving into and testing new measurement strategies. The fatigue over this ever-changing identity and measurement landscape is real.
What marketers can do now to get ahead of the changes
Simplify models. To start, marketers should steer clear of creating multiple models for assigning credit to outside channels and a separate model to give credit within their organization. For you, the marketer, this translates to conducting a sort of marketing mix audit to ideally identify and stop buying from external channels if fair credit for that placement can be found internally.
This can be a hard sell if your team, like most, is focused on meeting overall KPIs and accurately assigning internal credit as part of the same goal. No one wants to potentially upset the apple cart, even if it’s not working optimally.
Align teams and channels. Further, it’s critical to align all the teams on the definitions of internal versus external channels. For instance, is there a clear and agreed-upon understanding within your divisions to separate video orders on a desktop from video orders viewed on a mobile device? Successful marketers are working hard across silos to get their divisions aligned and aiming to synchronize reporting to capture the most accurate attribution model possible.
Another way marketers are taking charge of their measurement strategies is increasing the investment in data. This data-driven mindset helps build more accurate attribution and measurement models and utilizes more consumer data and modeling to create a more complete picture of your converting audiences.
Audience profiling. Moreover, a data-rich approach better equips marketers to assess and assign the lifetime value (LTV) of a consumer better.
This deeper dive into audience profiling and enrichment is proving to deliver more actionable insights on which audience profiles makes one conversion type more valuable from a lifetime value perspective.
Bidding. Data helps accomplish this by taking into consideration short-term and long-term LTV and targeting those customers or prospects appropriately. Further, these insights related to LTV can be used to train bidding algorithms that favor internal attribution over external channels yielding a higher overall LTV, and less waste on media spend.
By adopting a more standardized, holistic attribution and measurement strategy, marketers can land on best practices that will set them up for even more success as the Identity and Measurement companies bring more sophisticated solutions to market. Until then, marketers who get their marketing mix house in order now will have a running start as we all head into the murky measurement waters of 2023.
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Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.
About The Author
A leader in the data-driven AdTech space that spans 20 years across both the US and the EU. Ken Zachmann’s worked on the ground floor of a data start-up that yielded an eight-figure exit and served as VP and SVP for two leading digital data firms and saw them through to acquisition in 2017.
In 2018 Ken launched his first consulting firm focused on identity-based solutions and helping companies navigate a cookie-less future. Ken’s background in data and identity resolution, paired with his experience of living and working in both the US and Germany, has afforded him a unique understanding of the complexities of sourcing and building data, identity and measurement solutions.