What was a cookie-less future has become the cookieless-now.
What does a cookie-less future look like for CMOs? There is much to consider when it comes to your teams, your MarTech/Data stack and how to navigate the ‘cookie-less present’.
Scrutiny to hold dollars to account for marketing objectives is as challenging as it's ever been. CMOs are facing very material increases in spending across both digital and non-digital, and inflationary pressures are shrinking the value per dollar spent in the market. In addition to this, there exists a Paradox between Data Accessibility (what Companies need) and Security (what consumers and law-makers crave). These create interesting new-ish headwinds for a CMO.
Accessibility: On one hand, as consumer behavior becomes increasingly fragmented across digital and physical environments, customer-centric companies need to collect more sensitive data so they may address consumers across channels and in a well-governed way. The continual barrage of IDs, attributes, and behaviors requires an investment in advanced technology from multiple partners to unlock the full potential of that data.
Security: Consumer privacy and trust has become a critical requirement for marketing organizations - driven by consumer preferences, but also by law. Companies need the data, but the actionable and granular data they crave is at stake. Modern and evolving laws along with browser/OS advents have made it harder to secure data that is accurate, that you can trust, and that allows for addressability. Traditional targeting and measurement is being challenged.
Data Clean Rooms. Slotted under the Modern Marketing approach, as a beacon of hope to help CMOs continue to build high performing programs. Data Clean Rooms have been around since at least 2017 (at least commercially), when Google launched its Data Clean Room Ads Data Hub. Even before that, back in say 2014-2016, some advertisers were testing compliant ways to measure and target users within Walled Gardens. There is significant evidence that this approach is gaining steam. Ad Week cited a Gartner study that, while dated, may hold some truth. It reported “80% of advertisers with media budgets of $1 billion or more will utilize data clean rooms by 2023.” Pressure to leverage Data Clean Rooms to compete in a highly competitive media/ad landscape will lead to adoption. More adoption will drive an increase in economies of scale. All signs point to growth in this area especially if the cost to advertisers decrease in time.
Defined by InfoSum, and summed up well, a Data Clean Room is “a secure environment where multiple data sources are matched and analyzed, without sharing or compromising the data itself. The safety and security of data combined with the power and intelligence of multi-party computation have put the data clean room at the top of the must-have list for any organization that handles customer data.” The components of which include Identity resolution, First Party Data Onboarding, Audience Enrichment, Media Planning, Activation, and Measurement.
Here are some use cases and potential payoffs (not an exhaustive list):
More Targeting and Protected Data
According to a recent article by AdExchanger, Foursquare, who is a measurement and data partner in the new Roku Clean Room, can overlay its first-party location data with Roku’s data set to target households in a certain area that stream sports programs along with validation that a man between the ages of 25 and 45 years old lives in that house.
Drive Optimizations and Efficiencies
Another could be a CPG example. This may be one of the more common use cases. Since CPGs are a few degrees away from customer data, and have had to create data partnerships to understand their own advertising and marketing initiatives impact on sales, where the sales happen in POS systems they don’t control or own; Data Clean Rooms are a naturally good fit here and enable that level of accountability and measurement that breeds insights that ultimately drive optimizations and efficiencies.
As a CMO, especially one with a Global remit, there’s another reason Data Clean Rooms are becoming the next big thing. They provide the privacy-compliant model that advertisers and media companies must adopt for consumer and regulatory reasons. For example, in the same Roku example cited by AdExchanger, the kind of data matching and ad tracking Roku can enable through its DSP based on multiple first-party datasets would already be illegal in Europe under the GDPR if it didn’t have privacy compliance measures in place. (The only way to use Google ad server data in the EU is through Ads Data Hub). There now lies a potential way to create a strategy and apply that to more places across the globe. Scaling this approach, driven by Data Clean Rooms, may provide an approach and provide efficiencies that CMOs don’t have today.
Now as a CMO endeavors to find Clean Room(s) across Publishers, Media Owners and Ad Tech platforms, they should know that they aren’t all created equal. For example, you’d want to err on the side of establishing a Decentralized Clean Room over a Single Party Clean Room (e.g. a CDP often can be classified under Single Party) - the main distinction of which is that a Decentralized Clean Room offers data computation solutions that ‘do not’ require processing to take place in a centralized location, therefore requiring data to move or be shared across multiple systems increasing the risk of exposure leakage, and misuse.
And it’s a strategic initiative to establish the best set of Clean Room(s) to address its desired consumer.
Here are 5 Ways to Strategically Choose a Data Clean Room Partner
- Adoption - we’re in the low/no code revolution. Leaning into tools that almost anyone can use, autonomously, is key to adoption and maximizing usage.
- Control - your data should stay where it is. So should your partners. If it traverses, it’s not secure.
- Security - Have your IT teams stress test security, to ensure compliance in all its forms. No evidence or leakage or potential cases of misuse should be tolerated.
- Scale - Pick partners that encourage ways for you to scale. It should scale beyond a few partners, which is what a CDP can traditionally do. It shouldn’t be limited.
- Speed - deploying data and activating should be done in seconds, not days or weeks.
When CMOs strategically embrace Data Clean Rooms, and these best practices, they will be more impervious to an ever encroaching ‘Cookie-Present’ state of things, and be able to meet their talent pools maturity or learning curve to get the most out of the investment so that their marketing objectives may be met, and thrive. A fast follow up would be to take the next steps, or asynchronously, meet with Media Owners, Publishers and Ad Tech partners that enable activations, to validate that your stack will integrate well and create the best inventory and addressable audience mix to future proof your marketing programs.