Marketing industries are facing more regulation than ever – especially when it comes to how data can be used and processed. Along with privacy updates from the likes of Apple, it’s a challenging landscape for marketers.
‘Data clean rooms’, however, offer a highly secure environment for multiple companies, or divisions of a single company, to collaborate across data sets. They give businesses a protected space to store personally identifiable information (PII), where data is anonymised and processed to be made available for the purpose of identity, analysis, targeting or media measurement. All in a privacy-safe, compliant way.
As data clean rooms evolve, more advertisers are expected to tap into these environments to bolster their business and better serve customers. In fact, Gartner predicts that organisations that share data externally generate three times more measurable economic benefit than those that do not. Therefore, we are seeing huge growth in adoption across the marketing and advertising landscape, and that isn’t about to slow down.
Making data clean rooms work for you
The first step when using data clean rooms is to distinguish between traditional and distributed, and determine which one is most suitable for a business’s needs, as both offer different levels of functionality.
With a traditional data clean room, all data is stored in a single physical location, which creates limitations on how data can be shared. However, with a distributed clean room, cloud technology means that the need to move data from one location to another is eliminated, since the data can live in the cloud. Data management is, therefore, more agile, as each partner can control its own data while also enabling governed analytics with other partners simultaneously.
Distributed data clean rooms have the potential to provide markets with many key benefits. For example, the ability to conduct in-depth analysis on combined data sets to gain insights into customer behaviour, segmentation and customer lifetime value. With these insights, marketers can create a more complete picture of their customers and then use this to build custom audiences that can be used on advertising platforms for the likes of social media, allowing for more accurate ad targeting.
Deeper analysis is also possible through a distributed data clean room as marketers can configure a ‘private data exchange’. This is where participants can privately ‘list’ the data that would be useful for analysis in a secure place where only selected parties can view it. The data also doesn’t have to be moved out of its database account.
This has significant security benefits, as each participant can configure access controls and use secure functions to properly protect the data – without impacting the performance of joint data analysis. An advertiser could therefore use these secure functions to allow the analysis of carousel adverts by geographic location, while removing results from irrelevant areas or sample sizes that aren’t large enough. Secure functions can also highlight and remove any data that may violate privacy principles, strengthening the accuracy of the data that is being analysed and producing better and more usable data.
Putting distributed data clean rooms into practice
In an industry-leading example, in 2021, Snowflake customer NBCUniversal launched the NBCU Audience Insights Hub, built on a cross-cloud data clean room environment powered by Snowflake. The solution enables NBCUniversal to feed its first-party audience data, which advertising partners will then be able to safely and securely join with their own respective data sets, without moving, copying, or exposing any underlying PII.
Snowflake’s framework will let NBCUniversal and its partners govern what data is housed in the clean room, how data can be joined, what types of analyses each party can perform on the data, and what data, if any, can leave the clean room. The approach is distinct from other privacy sandboxes in that it lets the participants design the level of protection and transparency that is appropriate for building audiences, activating campaigns, or measurement. This creates a better experience for the consumer, as the ads they are receiving are more personalised because both the advertiser – in this case, NBC Universal – and the ad partner have a clearer picture of who they are targeting. This is because they can aggregate insights without any sensitive data being exposed.
In this example, the hub also includes certified reach measurement models that enable partners to use ad exposure data to conduct their own analyses. This gives the opportunity to establish one clear set of metrics when it comes to reach and frequency, ensuring better measurement. These metrics can then be used to better plan media marketing campaigns based on accurate audience insight and data that wouldn’t be available if it wasn’t for data clean rooms.
A new age of attribution
Attribution has been an age-old dilemma for the marketing industry. But, due to anonymised data that can be pulled from a range of sources and parties, data clean rooms can help to better attribute customer sales. For example, native audience insight platforms can share basic consumer demographics for analysis, but by adding sociographic and behavioural data, provided by other departments or external organisations, it becomes possible to present a more robust picture of the customer journey.
Furthermore, because of the way data clean rooms are created, they don’t allow data points that could be tied back to a specific user to leave the environment. This gives organisations the ability to adhere to privacy laws, which also achieve better attribution.
The data vs customer experience paradox
For many years now, marketers have faced a huge challenge. Data is essential in giving customers the best experience; the more you have of it, the more you can offer. But consumers are increasingly becoming more aware of how their data is being used. The introduction of regulations such as GDPR, and increasing pressure from customers to understand what data is being collected and processed, is making it increasingly difficult to give customers the experiences they expect.
By offering the ability to mine, analyse and share data in a data clean room, businesses aren’t just protecting themselves from being at the heart of the next headline data breach, they are also ensuring that they are reaching audiences in the most effective way possible. Those who aren’t already investing in this space risk leaving themselves open to reputational damage and below-par data – two things that can be detrimental in today’s world. The answer, therefore, is in data clean rooms.
Julien Alteirac is regional vice-president, UK and Ireland at Snowflake.