Adtech was built as an open ecosystem — for better and worse.
On the plus side, the industry experienced a staggering arc of innovation, centered primarily on being able to use data to intelligently auction, tailor, and optimize marketing touch points in near real-time. Any data owner could plug in via pixel, script, or transfer, and use that data to fuel intelligence across channels, surfaces, or contexts.
The negative side of all this? The pipes were too open, data use went too far, trust was lost, and the fallout is upon us. With the death of the cookie, the changes in regulation, and the walled gardens opportunistically seizing this moment to build bigger moats under the banner of privacy, marketers are faced with new realities that will force them to adapt.
A More Effective, Strategic Approach Emerges
The other trend that has been unfolding in parallel is the rise of the data-driven marketing organization. Marketers, like most professionals, have embraced the growth of analytics and data science.
“[Data science] is a young profession and academic discipline. The term was first coined in 2001. Its popularity has exploded since 2010, pushed by the need for teams of people to analyze the big data that corporations and governments are collecting.” This is according to Wikibooks.org.
In contrast to just a few years ago, more and more marketing leaders now have data scientists on their teams who universally agree that better data is far, far more important and impactful than the better algorithm. And so, not-so-new questions come to the forefront yet again
- Who has the data I need to tell an accurate and comprehensive measurement picture for me?
- Is there a way we can collaborate and utilize that data?
To answer the first question (‘who has data with the right signals for us?”), innovative marketers are thinking about the funnel and are hand-curating a set of data collaboration partners who will provide a full view of the customer journey, from awareness to consideration, all the way down to intent and conversion. At the top of the funnel, awareness signals come in the form of ad exposure data from media platforms and individual publishers.
Consideration and intent signals is where I am seeing marketers cross the chasm and break down barriers that have prevented strategic data collaboration in the past.
Marketers are calling endemic publishers who can provide data about consumers reading up on the marketers’ products, as well as products from competitive brands in the same categories. Not long ago, such a conversation would have stopped dead in its tracks.
The perceived risk to an endemic publisher was well known and a blocker:
“Why would I give you my data if it will allow you to buy my media against my audience elsewhere for far less than I charge you today for your media buys?”
Similarly, a marketer’s distribution channel partners (i.e., retailers for CPGs) had real reasons to be worried about the competitive risks of being transparent with their data.
But data clean room technology offers a path to sufficient transparency and control to find mutual alignment and common ground with these strategic partners.
With fine grain controls on data access, usage, and governance, it is easy for a partner to say “Yes, you can use my data for purpose X, as long as it cannot be used for purpose Y.”
We’re seeing car companies and auto publishers coming together, insurance companies and banks, retailers and CPG partners, gaming companies and gaming platforms, and beyond. And with this renewed success, marketers are waking up to a world where they really can successfully curate a set of partners to provide a robust and comprehensive view of what happens after people see ads.
A Privacy-Compliant Path Ahead
As the industry is certainly in a state of flux, I’m betting on marketers to prosper. Early adopters are finding a place of zen and realizing that the wave of changes to our industry are yielding clarity on what a future-proofed, privacy-compliant path ahead looks like.
Backed by their data-driven cultures, marketers are realizing they are empowered and can be successful building out their own curated data stacks. I encourage your team to follow suit.
If you are wondering how your team might be able to be successful with this type of data collaboration, contact Habu. We’d love to hear from you!
