Clean Rooms Explained: How Marketers Can Prepare For Cookieless World

The advertising industry is undergoing a paradigm shift and their favorite buzzword is a clean room. Ad agencies, publishers, and technology providers have long relied on “centralized identification.” They know how to discover, reach, engage, and measure individuals by way of cookies, mobile IDs, and set-top field IDs.

With Google’s decision to end third-party cookie support in Chrome, the data will be lost on which brands once relied upon to gauge advertising returns. Consequently, in a world where user privacy regulations are being strengthened, marketers are heading into a brand new area of marketing analytics where connectivity and addressability are becoming more and more fragmented. Hence, it comes with no surprise that clean room is a hot topic for advertisers.

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What Does A Clean Room Do?

Data clean rooms are software programs that enable advertisers and brands to match user-level data without sharing any personally identifiable information(PII) or raw data. It was originally arranged by walled gardens such as Google, Facebook, and Amazon to provide advertisers with matched data about how their ads were performing on their platforms.

How Can Advertisers Use The Clean Room?

There are currently two types of clean room: walled gardens, like Google and Amazon, which let brands see inside their own ecosystems. Second, software companies and data managers like Habu or InfoSum act as conduits between parties that wish to share data.

For example, brand partners with a publisher (Google, Amazon, or retailer with a media network). A clean room provides a closer look at campaign performance data like reach, shopper conduct, and engagement for logged-in or registered prospects to both parties. Further, they will relay their first-party data into the clean room and compare it to platform data to enable activation and measurement without revealing user-level details. 

Marketers are partnering with expertise suppliers to create their own authentic and privacy-safe clean rooms. The digital sphere is becoming more and more like a federation of private rooms, each with its own distinctive capabilities and information. Also, “Id” is turning more decentralized than before. 

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How Should Advertisers Address This?

First, they need to determine which clean room to take advantage of based on their advertising stack and media allocation. Let us understand with an example of Google Ads Data Hub.

Entrepreneurs utilizing Google’s tech stack ought to prioritize Adverts Knowledge Hub for attaining/frequency measurement, marketing campaign supervisor attribution, and DV360 for mapping first-party information. Furthermore, YouTube information is extra efficient when used with the rest of Google’s information, enabling cross-device publicity evaluation.

The next step for advertisers after making the choice is to develop their clean room techniques as follows:

a. Build an audience:

Advertisers will require to build new paths in every clean room for locating and rising audience. They would start with mapping first-party information to every clean room to find present and prospective shoppers. Then analyze and enhance the conduct and efficiency throughout new audiences. This will provide stability as audiences from cookie-based monitoring falls as well as insight into prospects.

b. Brand Engagement

In the absence of cookies, advertisers must shift to a mobile-centric engagement model that allows them to reach shoppers within their in-app experiences and logged-in accounts. Recapturing the information will help device-based remarketing and enable cross-device insights.

c. Measurement and optimization

Deprecating cookies means losing a unified view of the effectiveness of your marketing campaigns throughout the buyer journey. As a result, they have to use cross-device data within every room to find new indicators. Responding to the challenges, advertisers need to provide a  framework for the clean room technique. 

Furthermore, advertisers would require clean-room measurements and optimization techniques to understand other cell indicators that affect their marketing campaign achievement, frequency goals, and attribution models. Each clean room has its own multi-touch attribution measurement. Afterward, advertisers will want to normalize the load by combining the results across all clean rooms.

Interesting Read: Impact of Delay in Deprecation Of Cookies By Google On Adtech 

What Does The Future Hold?

In the wake of third-party cookies being deprecated, marketers and publishers are racing to improve first-party data and the overall way they target,  measure, and optimize it. Tracking and reporting no longer function in the background and need explicit user consent. As marketers confront the challenges associated with measurement and optimization, there is a clear need to outline a clean room technique. It may be difficult and time-consuming work, but the rewards are enormous. Rather than relying heavily on small samples to infer buyer journeys, it may make more sense to establish, target, and measure audiences by using de-identified information about writers and platforms. Data clean rooms offer a valuable way to collaborate and analyze data in a privacy-compliant way to better understand how customers interact with the brand.