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Sponsored


HOW AUDIENCE-BASED DSPS ARE OFFERING MARKETERS IMPROVED PERFORMANCE AND
FUTURE-FORWARD APPROACHES

Sponsored by Marketecture  •  October 12, 2023  •  4 min read  •
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Produced in partnership with Marketecture

The following article highlights an interview between Tim Vanderhook, co-founder
and CEO at Viant and Ari Paparo, founder and CEO of Marketecture. Register for
free to watch the discussion and learn more about how audience-based DSPs
improve advertisers’ performance and offer future-forward targeting approaches. 

Brands and the agencies that work with them are always looking for more
efficient ways to reach their target audiences at scale via unique,
privacy-compliant targeting methods. However, identifying tools that will
accomplish these goals is a perennial challenge.

For example, demand-side platforms (DSPs) promise powerful outcomes. Yet, many
DSPs use identifiers that aren’t compatible across technologies or vendors and
aren’t future-proofed for the evolution of privacy legislation. The way forward
for advertisers is increasingly focused on technology rooted in an
audience-based model, with machine learning and a more forward-thinking
universal ID to provide teams with better performance, a wider range of
targeting methods and a more robust DSP.


To help unpack what that tech looks like, Tim Vanderhook, Viant’s co-founder and
CEO, recently spoke with Ari Paparo, founder and CEO of Marketecture; they
discussed building audiences, using machine learning and paths toward a new
universal ID. 




HOW MACHINE LEARNING AND AUDIENCE-BASED MODELS DRIVE BETTER PERFORMANCE FOR
ADVERTISERS  

Brands and agencies want efficient ways to reach their target audiences and can
do so effectively with audience-based models. If they couple this method with an
audience-based DSP, they can leverage additional tech capabilities, such as
machine learning, to maximize performance.



The best way to get started is with a known group of their customers. This
allows the DSP to tell them much more information than the old way of creating a
fictitious demographic that might like the company’s product. 

By beginning with those who have purchased already, the team can work with the
audience-based DSP to reach additional similar audiences. 

From here, advertisers have a couple of options. They can use the platform to
build lookalike audiences based on their known ones, but there’s also a machine
learning element that adds something new to the equation. 

“The historical way of retargeting past website visitors or with any
publisher-based buy meant banner burnout or video performance burnout,”
Vanderhook said. “The performance starts very high, then it degrades over time.
But, when you’re running these machine learning segments, you don’t experience
those same effects when going after these audiences. With machine learning, it
figures out who that next person is before they come to your website, and it
takes away that lack of performance over the course of time.” 



Meanwhile, more traditional retargeting methods meant collecting a large group
of users and exposing them to ads. Some would convert, but the performance would
wane until new-in-market consumers appeared. The machine learning method added
onto an audience-based model within an audience-focused DSP allows advertisers
to see steady performance throughout a campaign.


MAKING THE CASE FOR A NEW, ‘ULTIMATE’ UNIVERSAL ID 

While the industry has shifted to using some form of digital identifiers, with
guidelines and restrictions now targeting these identifiers, advertisers are
pursuing new options. Some have taken to utilizing hashed email addresses, but
consumers are only sometimes willing to register their email in exchange for
specific information, rendering the identifier useless.

Because consumers’ lives are increasingly hybrid — i.e., they are sometimes
getting products delivered and other times picking things up — home addresses
have become a data point regarding digital identifiers.

Vanderhook sees this as the future of the quest for the universal ID — a stable
element that offers numerous targeting capabilities and isn’t regulated by big
tech. It’s not something any tech group can take away from marketers or
publishers. Furthermore, the fidelity of the data is very high, adding to the
attractiveness for advertisers and publishers alike. 

“I think household addresses in some form is ultimately going to be the
universal ID that all of us are operating on,” Vanderhook said. “Especially
given the way that online and offline work together now and the many devices
that we all have, which we all call channels. I have been of the belief that the
universal ID for the industry to settle on should be households or home
addresses because It’s the only way to tie online and offline.”

Advertisers are finding that audience-based DSPs offer them a range of benefits
with the ability to bring known audiences, build lookalike ones, utilize machine
learning to target more effectively and for better performance — and access to a
future-forward ID that just might be the universal solution for which the
industry is looking. 

————————————————
Register for free to watch the discussion between Ari Paparo and Tim Vanderhook
and learn more about how audience-based DSPs improve advertisers’ performance
and offer future-forward targeting approaches.

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