Third-party cookies were the main mechanism for identifying individuals across different websites for the purpose of showing them personalized ads, running frequency capping, measuring the performance of campaigns, and performing attribution.
But as we all know, third-party cookies are not very privacy-friendly and are being shut off, one web browser at a time.
Apple&#;s Safari and Mozilla&#;s Firefox already blocked third-party cookies by default and Google Chrome will be shutting off support for them in .
So how can advertisers still run personalized ads, measurement, and attribution without third-party cookies while still ensuring a certain level of user privacy protection?
Various solutions to this problem have emerged, with data clean rooms being one of the main ones.
In this blog post, we explain what data clean rooms are, how they work, the pros and cons of them, and why some brands are building their own.
Watch the video interview below with Gowthaman Ragothaman, CEO at Aqilliz, a data clean room provider.
Link to EZONG
What Is a Data Clean Room?
A data clean room is a piece of software that allows brands and advertisers to run targeted advertising campaigns, apply frequency capping, measure and report on the performance of campaigns, and run attribution &#; all in a privacy-friendly way. They can achieve this by uploading their first-party data and comparing it to the aggregate data in the data clean room, which has also been added by other companies.
Unlike other types of data partnerships whereby companies directly exchange user-level data, such as cookie IDs, device IDs, and IDs created from hashed addresses, data clean rooms match the first-party data provided by brands and advertisers together but prevent any user-level data from being accessed outside of the data clean room. All of the first-party and user-level data stays within the data clean room and isn&#;t shared with anyone else.
How Does a Data Clean Room Work?
The first step involves companies adding their first-party data to the data clean room. In the next step, various security and privacy-protection measures are applied to the data, such as pseudonymization, restricted access, differential privacy and noise injection. The third phase involves placing the data into cohorts.
The data can then be activated &#; i.e. used for various advertising and marketing processes such as targeting, measurement, and audience analysis.
Advertisers and publishers can analyze reports provided by the data clean room to improve the campaigns they are currently running or will run in the future.
To understand how data clean rooms work, think of a metal box traveling along a one-way conveyor belt. Using this analogy, here&#;s how the process works:
Advertisers put a package of their first-party data on the belt. The package can contain user-level data as well as transactional and historical data. On the other side of the belt, another advertiser or publisher places their package of first-party data on the belt.
The belt takes packages to the metal box, which is the data clean room. In that box, the data from the two parties is matched and cleaned &#; i.e. audiences are matched and privacy techniques such as encryption, hashing, pseudonymization, restricting access, and noise injection are applied.
From there, you can show ads to members of your target audience and receive reports, which you can then analyze and utilize for other advertising-related activities.
Because privacy is the key focus of a data clean room, you&#;ll receive reports based on aggregated data. So you&#;ll know how many people clicked on one of your ads, but you won&#;t know anything about them, e.g. you won&#;t receive user-level data such as IDs.
Our AdTech development teams can work with you to design, build, and maintain a custom-built data clean room for any programmatic advertising channel.
Learn moreThe Main Use Cases Of a Data Clean Room
The various privacy changes in web browsers and mobile apps, as well as new privacy laws, are creating a better world for consumers and Internet users, but are making it harder to run digital advertising activities that companies have relied on in the past. Data clean rooms offer a good balance between protecting user privacy and allowing companies to reach their target audience, measure the performance of their campaigns, and attribute impressions and clicks to conversions.
A data clean room can also allow companies to establish co-marketing partnerships by identifying the customers they share with each other and create more detailed user profiles by analyzing the anonymized reports.
The Pros, Cons And Risks Of Using a Data Clean Room
As with every piece of technology, data clean rooms have both positive and negative sides.
The pros of using a data clean room:
The cons of using data clean room:
The risks of using a data clean room:
Despite the cons and risks of using data clean rooms, they offer a very promising solution to the current challenges facing the programmatic advertising industry, i.e. running advertising processes, such as ad targeting and measurement, in a privacy-friendly way.
Watch the video interview below with Juan Baron, Director Business Development & Strategy (media & adv) at Decentriq, a data clean room provider.
What&#;s The Difference Between a CDP And a Data Clean Room?
Both advertisers and publishers collect valuable first-party data from different sources. To help them collect and manage this data, they can use a custom data platform (CDP). A data clean room extends the capabilities of a CDP and takes data management to the next level.
But what are the main differences between a CDP and a data clean room?
What Are the Privacy Alternatives to Data Clean Rooms?
The availability of third-party cookies has been on the decline for a few years now and when Google Chrome, the world&#;s most popular web browser, announced that it would be shutting off support for third-party cookies, various alternatives, such as data clean rooms, started to appear.
There are essentially three main alternatives to a data clean room:
There are also many other alternatives that could be explored in the future, such as cryptoidentities, which aim to represent people via avatars. The technology enables matching, acquiring, and testing data without sharing personally identifiable information (PII).
Which Companies Offer Data Clean Rooms?
There are three kinds of data clean rooms. The first kind is provided by the walled gardens of AdTech, the second kind is provided by independent companies, and the third is owned by companies with huge amounts of users and content.
What&#;s the difference between them?
With the first kind, Google, Amazon, and Facebook run media clean rooms where each company delivers hashed and aggregated data to companies that use their advertising platforms.
In the second case, two data owners, e.g. a publisher and an advertiser, put their data into one neutral room and share it safely between one another.
And in the third case, companies that have massive amounts of user data and content, such as Disney, Spotify, and TikTok, build their own data clean rooms.
Let&#;s now look at some examples of companies that offer data clean rooms.
Known as the &#;Switzerland of Data&#;, Decentriq is a data clean room and data collaboration platform. Decentriq&#;s technology is built using the latest advancements in encryption and Privacy Enhancing Technologies such as synthetic data, differential privacy, and Confidential Computing. The Decentriq platform is used by companies from various industries, including media and advertising, healthcare, and banks.
Google Ads Data Hub is a privacy-safe data warehousing solution built on Google Cloud. It provides the tools to create custom reports that don&#;t contain personally identifiable information (PII). The sources of data come from Google Campaign Manager, Display & Video 360 (DV360), Google Ads, and YouTube.
Amazon Marketing Cloud (AMC) is a holistic data clean room solution built on Amazon Web Services. It helps companies discover the true impact of cross-media investments by matching and analyzing two sources of data: advertiser&#;s data sets and data sets delivered by Amazon Advertising events.
Contact us to discuss your requirements of clean room specifications. Our experienced sales team can help you identify the options that best suit your needs.
InfoSum created a privacy-enhancing environment with the utmost respect for the safety of data. The mechanisms behind InfoSum&#;s data clean room process the data in a fully decentralized and cloud-agnostic room which eliminates all the data-leakage risks related to centralized data lakes or warehouses.
With Snowflake, advertising companies can build an environment capable of processing shared data sets. Snowflake&#;s clean rooms provide real-time information and hide customers&#; personal information at the same time.
Aqilliz offers a new-age middleware technology for the currently disjointed digital marketing ecosystem. Rooted in the pillars of differential privacy and federated learning on a distributed ledger, Aqilliz benefits brands, platforms, and consumers alike by delivering collaboration solutions that ensure a privacy-compliant approach to insights, activation, and measurement, leading to better productivity.
Disney Advertising Sales introduced its clean room in . The cloud-agnostic solution is powered by Disney Select data and Disney Advertising&#;s Audience Graph. The key strategic cloud collaborators are Habu, InfoSum and Snowflake.
Why Are Brands Using (and Building) Data Clean Rooms?
We&#;ve observed three different trends around building data clean rooms, with the retail sales sector being one of the most adaptive.
Hershey&#;s is an example of a company that seeks to evolve its advertising strategy and gather new insights about the performance of its ad campaigns. The candy maker sells its products throughout a network of retailers but lacks insights into certain key areas of its business, e.g. the effectiveness of its loyalty programs.
By building their own data clean room, Hershey&#;s can convince retailers to share their first-party data with the producer, check the volume of repeated ads, analyze loyalty programs, and choose the right direction for their advertising activities. The retailers store loyalty-card data alongside Hershey&#;s ad data and share data sets in Hershey&#;s data clean room.
Unilever is using a data clean room to identify the platforms where ad content was shown to the same user and didn&#;t result in a positive retail effect. The company does this by sending its ad-related records and data sets to measurement companies Nielsen and Kantar and then analyzing the results across platforms like Google, Facebook and Twitter.
Disney introduced its data clean room solution as a way to provide custom and future-forward solutions to marketers. By partnering with data clean vendors Habu, InfoSum, and Snowflake, Disney is able to offer their advertising clients a privacy-friendly way to reach Disney&#;s audience and obtain valuable consumer insights.
Conclusion
Due to the upcoming end of third-party cookies in Google Chrome, businesses are looking for ways to continue their advertising processes, such as ad targeting and measurement, while respecting users&#; privacy at the same time.
Data clean rooms are one of the solutions to tackle the problem. To use a data clean room, two entities (e.g. an advertiser and a publisher) prepare packages of data and upload them to the data clean room. Then, the data is encrypted and anonymized. Both parties get information in the form of cohorts and aggregated reports.
Data clean rooms are mostly used for ad targeting and personalization, frequency capping, measurement, and attribution purposes.
Of course, there are also other alternatives, such as universal user IDs, Google Privacy Sandbox, and contextual targeting.
The data clean room market is rapidly growing and accelerating as the end of third-party cookies gets closer. There are three types of data clean rooms; ones offered by the walled gardens (Google, Meta and Amazon), ones from independent vendors, and custom-made ones built by brands and content owners.
Our AdTech development teams can work with you to design, build, and maintain a custom-built data clean room for any programmatic advertising channel.
Learn moreMarketers know that in the constantly changing world of the consumer, having the right tech stack is key. As first-party data becomes synonymous with marketing success, many are turning to tech designed to capture, organize, understand and activate customer insights to enable audience targeting, customized experiences and better performance.
You might&#;ve heard of (or might even currently use) a data clean room or customer data platform (CDP) solution already. Both are integral tools when executing your first-party data strategy, but understanding which tool to use comes down to understanding their main functions. Do you know the differences between them? And more importantly, do you know why you might want both?
While clean room and CDP are often coupled together as similar products, there are some significant differences between them. CDPs and clean rooms can be great tools for brands to understand their customers, fill in information gaps, understand customer journeys, as well as prospect customers who are in-market for a brand&#;s products and services. At their most basic, both tools take data and organize it for brands to use. Epsilon's Customer, a CDP solution, can activate data to find the right people at the right time, and continually use that data to learn and measure strategies to strengthen over time. Something that no other CDP does.
Fundamentally, though, the two perform two different jobs. Before we dive into the similarities, let&#;s first understand them as separate solutions.
Customer data platform Clean roomCDPs are used for known customer data collection and analysis. Brands that have first-party data might not have a complete (or accurate) view of their existing customers, which limits their ability to reach them online and offline. When brands use CDPs fueled with a strong identity solution, like Epsilon's, they can start filling in those gaps, which gives the brand valuable and predictive signals. This in turn builds more relevant, personalized customer campaigns.
On the other hand, clean rooms create a safe, pseudonymized space to look for known and prospective customers. They are privacy-safe environments that use anonymized data to facilitate data sharing amongst multiple parties. This allows brands to drive prospect engagement based on consumer behaviors in the wild and use first-party and third-party data to build better unique audiences.
&#;CDPs are rooted in PII-based data, designed to improve marketing outcomes for known customers; whereas clean rooms are ID-based data that provide additional privacy for consumers and expand how brands can work with the data,&#; said Tyler McDaniel, Vice President of Product Management and Identity Solutions at Epsilon. &#;Additionally, brands that don&#;t have a rich first-party data foundation could use a clean room to their advantage for digital marketing or data sharing with partners.&#;
Ultimately, both are trying to solve for the same thing: To create seamless customer experiences rooted in first-party data. CDPs do this for customers with name-based recognition and clean rooms do it in an ID-based environment. That allows for more exploration in the wild if a brand wants to do so.
Both support secure data collection. Both also allow for deeper insights on consumer behavior as it relates to a brand&#;s marketing strategy. But where these two really shine is when they&#;re used together.
Kelley Maves, Senior Vice President of Product and Data at Epsilon said the synergies between a clean room and a CDP boil down to three things:
Some specific use cases might include:
Maves said the decision to use a clean room over a CDP, or vice versa, comes down to data. While he says both products maximize the use cases a brand can bring to life, the question marketers need to ask themselves is, &#;How much data do I have?&#;
&#;If the brand has a broad amount of customer data that they've captured over the years as they build relationships with their customers, they may find the most value is with a CDP, so that they can maximize the usefulness of their first-party data assets,&#; he said. &#;In cases where the brand has a more limited set of customer data, a clean room that is enriched with additional prospecting IDs will likely be the most useful capability to bring immediate value to the brand through the use of licensed consumer attributes.&#;
Based on the scope of data a brand is working with, their use cases might change. Marketers need to understand their unique challenges and their desired outcomes, especially if they have a limited budget.
Epsilon&#;s Digital CDP and clean room solutions are built using Epsilon PeopleCloud, meaning they seamlessly work together to drive bigger returns. With CORE ID at the center, we use identity resolution with unique IDs and proprietary attributes across our database of 250 million+ real people&#;all in a privacy-safe environment.
&#;Undoubtedly, CORE ID at the center of both solutions makes our offerings unique in the marketplace, giving marketers a unified view of an individual and enriching the marketers understand of individuals through Epsilon&#;s data,&#; McDaniel said. &#;Because we&#;ve designed these solutions to be fueled by first-party data, marketers will get the best activation performance and reduce media waste.&#;
With Epsilon, you&#;ll be able to build, enrich and extend your first-party data through our CDP solution, and target custom audiences with other first-party and third-party data insights using clean room.
Learn more about our Digital CDP and clean room solutions.
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