As GDPR enforcement becomes a reality not only in Europe but also here in the US, advertisers are struggling to find a way to scale the walled gardens and optimize their data assets.
As of May 25, 2018, Google announced that DCM users will be unable to use cookies or mobile device IDs to connect impressions, clicks and site activities from the DCM logs, users will be limited to Google’s own Ads Data Hub for those metrics. For some, this means that they are satisfied to stay within the Google stack but not every brand’s solution will be and should be limited to Google. But if media buyers want to analyze their spend outside of Google’s platform and offer up any attribution, then just using Google won’t work.
“Some marketers who spend 75 percent or more of their budgets on Google will be fine just letting Google do the analytics,” says Alice Sylvester of Sequent Partners.
Google wasn’t the only one to lock down their platform. In response to the combined pressure of GDPR and the Cambridge Analytica scandals over its handling of personal information, Facebook decided that it would shut down ad tools called “Partner Categories” powered by outside data brokers. Those tools let Facebook advertisers target ads at people based on third-party data such as their offline purchasing history. This means advertisers will have access only to their own data and data Facebook collects itself. If an advertiser wants to pull campaign-level insights to inform future campaigns or use the data for the basis of an attribution model then they are out of luck.
Introduction of Data Clean Rooms
Data clean rooms allow large inventory partners like Facebook and Google to share customer information with brands, while still maintaining strict controls in place. Data clean rooms were named for the completely airtight rooms where microchips and other sensitive materials get made. In this case, the rooms enable a shared environment between two or more companies that is completely secure from external access (no wifi) where each company decides the level of visibility to their data. This eliminates the possibility of data leakage for companies like Facebook which caused the Cambridge Analytica mentioned earlier.
“We and a partner combine a data set with very specific rules and controls around how each party can operate within the shared environment,” said Scott Shapiro, a product marketing director for measurement at Facebook, who noted that Facebook didn’t invent the clean-room concept.
The concept is to create a safe space where data can be share and manipulated without leaving the inventory partner’s environment. Specifically for Facebook, a brand can create an audience based on first-party data, like a list of email addresses and then push that list into Facebook, match it, and grab a copy which they can later combine with their data as the basis for attribution, measurement and modeling.
How it happens in reality is that an advertiser will lead a clean or wiped laptop or device that has never been connected to the Internet with that advertiser’s first party data, which in most cases is an email list. A second clean computer is loaded by Facebook or Google with impression-level and non-PII campaign data.
Maybe, The Answer to Scaling The Walled Gardens?
For advertisers with a lot of data and substantial programmatic advertising budgets this is a great opportunity to scale the otherwise elusive walled gardens. The data clean rooms create a safe environment for data providers to share the marketing data that brands need and crave to model future media buys and advertising strategies. If managed in the right way, with the right methods and standards, this would be the tool for brands to really understand their walled-garden ad spends within the larger marketing ecosystem. For advertisers and publishers there is a lot at stake in the post GDPR world of data governance. There is no room for unintended data sharing because the consequences are too great.
Marketers have been eager to get more insights out of Facebook and other walled gardens but it’s unclear how many brands or agencies will take advantage of this opportunity to get more out of their spend with the largest inventory providers. From Facebook’s perspective they are not advertising the data clean room solution because if they gave advertisers too much access to data buyers might eventually become less reliant on their platform for scale and identity data. But Facebook and Google also don’t want to piss off their advertisers because they are demanding more data so this is the solution that they can offer for brands that pressure them to giving them more insights. There is still the issue of the manpower involved and the fact that the data is limited to a snapshot in time but advertisers who buy into this solution are fully aware of what they are getting and have to decide if the value is worth the effort.
The world of digital advertising and programmatic advertising has developed its own language in the last couple of years, full of terms that are commonly heard and used everywhere but mean something very specific when attached to the word advertising. Most recently it’s almost impossible to read an article or even talk about media buying without bringing up the terms Artificial Intelligence (AI) or Machine Learning. The terms AI and machine learning are often used interchangeably but they are different. What is the difference between the two and what should they mean to us or me as a marketer or CMO?
Artificial intelligence is the concept of reproducing human intelligence in machines so they can execute on activities that normally would require a human brain to be involved in, such as making data-based decisions. By using AI-powered systems brands and advertisers case save money and time by completing tasks faster than us mere humans and make less mistakes. When you apply this to the programmatic media buying industry, you bring efficiency to the media buying process, freeing people who’s job it is buy media from the more tedious and allowing them to focus on the strategic and creative elements of their jobs.