Explained: What is a data clean room?

We’ve definitely been in a situation where we are talking about something and suddenly find ads on all social platforms and browsers about exactly that. For example, We’re talking to our friend about buying a new vacuum cleaner. We go home and start browsing on social media. Out of nowhere, we are bombarded with a series of advertisements for vacuum cleaners. How does our phone know that we want one? Do walls have ears? Is the government spying on us? Is this proof that the Matrix is real? Well, let’s answer this.

All web browsers and big tech companies such as Google, Microsoft, Meta and Amazon share data obtained from customers with advertisers. These companies are constantly studying and trying to understand consumers’ habits and behaviours from their actions on their respective platforms. Be it shopping for a specific item, looking for an online course, planning your next holiday and much more. All of these actions are tracked and calculated predictions and information is sent to advertisers by these platforms to provide predictive prompts in the form of ads to users. However, not all data is shared with advertisers for safety purposes. How do these tech firms filter through data and ensure that advertisers are receiving only what they require and nothing more? This is done via data clean rooms.

What is a data clean room?

Data clean rooms are places where walled gardens like Google, Microsoft, Meta and Amazon share aggregated data rather than customer-level data with advertisers. This is done while exerting strict control. Data clean rooms provide for two-way data influx. Advertisers too pour in first-party data that they gather into this room to measure how different data sets match up, to understand if there are any inconsistencies between the two sets of data. This determines whether the advertisers are over-serving ads to the same set of audiences. None of this aggregated data leaves the data clean room.

Using data clean rooms means that advertisers don’t have to part with valuable targeting segments that can give one platform the upper hand over any other. Furthermore, these safe rooms also provide an opportunity for the platforms to eat into their rivals' shares.

Even though data clean rooms provide a safe space for data exchange, they aren’t widely adopted.

What are the downsides of a data clean room?

Data clean rooms aren’t cheap. While Google, Meta and others have offered alternatives for quite some time, political and logistical impediments put strains on all parties. Moreover, it is not favourable for walled gardens to submit too much data to advertisers, given the amount of value they’re able to derive from their own targeted data. A lot of times, advertisers too don’t want to share detailed transactional data due to privacy policies and risk assessments. This disrupts the data measurement within the rooms. Managing data clean rooms is a laborious task. People often end up emailing entire data sets or create shared folders. This results in risking private information and treads on borderline privacy breach.