Digital Marketers should focus on clean rooms strategy in 2022.

Digital marketers who aim to evolve their audience strategies must consider ways to employ clean rooms into their vendors' ecosystem.

Data clean rooms allow marketers to gain access to large amounts of valuable consumer data in order to optimize their targeting efforts — in a standardized and secure manner that addresses growing privacy concerns. But, as Katherine Strieder, global chief product officer at programmatic marketing firm MiQ, writes, marketers have many different types of data clean rooms to choose from, and the best fit will vary depending on a variety of factors. Currently, the digital ecosystem is undergoing a huge expansion in terms of consumer experience as well as the swift evolution of privacy and regulatory compliance. It is surprising how data clean rooms have reached this far as one used to activate audiences by uploading lists of content categories into platforms serving display banners long before privacy and data-sharing laws.

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Today, the vast swaths of customer data, content, including the core technology that drives the industry are controlled by the walled gardens of Facebook, Apple, and Amazon. As audience data is used in new and innovative ways, smart businesses are realizing the value of their own data, and technology vendors are also further evolving. Meanwhile, to reflect those sectors such as healthcare, traditional television, and so on that have been governed for long, the industry is intending to evolve its business and ethical standards. Further, for a variety of reasons, these structures were not initially incorporated into the digital ecosystem.

Some declared that publishers and brands did not implement adequate governance with their tech stacks, while others argue that the leaders who built today's walled gardens were opportunistic in their approach, but failed to consider the conflicts of interest associated with powering tech, content, and consumer data. Moreover, space evolved much faster than what regulators were accustomed to initially. Today the most effective way for businesses to reach the consumer is through their data as they primarily live in the digital universe. Methods for doing so have grown in number as mediums of engagement have multiplied and privacy practices in various markets and verticals have diversified. Marketers must then decide which data and methods to employ.

One such method which provides a unique opportunity for marketers to connect different data sets, graphs, panels, and experimental data science to build insights about consumers on a global scale — in privacy-first, secure environments — by leveraging nascent technologies is the data clean room. However, there are numerous types of clean rooms, and it is essential to understand the difference between them. Walled gardens are interested in retaining control over technology, content, and data. However, they are also interested in collaborating with other businesses to reach out to consumers. Companies, on the other hand, require access to consumer data made available through these walled gardens. As a result, tech companies have made forays into data clean rooms, which allow marketers to compare their own first-party data to walled garden data without either side actually handing over the data. When collaborating with these vendors, marketers must be very clear about how they will protect their data and insights. They must also understand that the primary goal of these clean rooms is to increase the number of purchases made on their platforms.

Google's Ads Data Hub (ADH) is an excellent example of such a clean room. A clothing brand could port its own purchase data into Google ADH and match it with Google campaign data to find patterns between the time of purchase and creativity served in this space. Contrary to its initial assumption, the brand may discover that a jeans and t-shirt creative combo converts just as well on weekdays as it does on weekends, which can then be modified as per the campaign requirements. Recently even Amazon has released its own version. Furthermore,  in the coming months, one can likely see companies that lack tech dominance but those that have a vital mass of users and content particularly the ones with valuable streaming content, such as Disney, Spotify, and TikTok, will begin to build their own clean rooms.

Neutral data clean rooms have also made an appearance in the sector. They work in a variety of markets, verticals, and mediums and enable virtual data collaboration through the use of multi-party encryption technology and data science. Nth Party, Kochava, Infosum, and Snowflake are examples of neutral data clean rooms. These platforms operate in a very different way than the clean rooms run by major tech companies, and they utilize their own distinct business models. All of these clean rooms are experimenting with big data in order to uncover innovative data insights. Without exposing or moving the underlying data, businesses can securely and privately connect, analyze, and enrich their data with datasets, graphs, and integrations from other sources. This adaptability allows for a wide range of applications for marketers to examine consumers in the digital universe.