Hashed email, data clean rooms, and the future of advertising identity in pharma advertising

Technology innovation

Hashed email, data clean rooms, and the future of advertising identity in pharma advertising

By Anton Yazovskiy

Over the last couple of years, various groups have put forth standards to think about and measure identity. Among the most promising alternatives involve the use of hashed email addresses, such as Unified ID 2.0. Still, these solutions run into challenges as they scale and invite some of the same criticisms that killed off third-party cookies.

In today’s fast-changing world, identity needs to be considered holistically, with organizations adopting multiple forms of identity resolution and measurement, including the use of identity graphs and data clean rooms to stitch together a more complex picture of behavior while preserving individual privacy. This article will explore several emerging identity standards and what’s needed for the successful planning, activation, and measurement of advertising campaigns in the near future.

Email is ubiquitous – and vital to publishers in the post-cookie world

Anyone who has ever registered for a service or online subscription knows that email is the one consistent piece of information that sites require. Users often maintain the same email address for years or even decades, and they’re unique to individuals, making them a reliable identifier for publishers to offer 1:1 targeting and measurability without third-party cookies. Using cryptography to encode or hash email addresses, publishers and advertisers can securely exchange information about ad performance across channels. However, solutions that rely on hashed email face particular challenges that will limit their effectiveness over time.

First, not all online publishers are created equal. There are grades of quality that determine whether a user will offer up their email – and opt-in to that publisher’s data collection policy – or simply click away if they sense their data will be mishandled. To illustrate, a user may be willing to donate their email address in exchange for free access to an article from Rolling Stone or ESPN but not a meme linked on Facebook.

Second, email is becoming less and less reliable. As long emails have existed, users have shared their account login information with friends and family. Additionally, tech companies like Apple have introduced features like Hide My Email that create unique, random email addresses that cannot be easily identified to individuals. These features significantly lower the barrier to creating new accounts to avoid identity resolution and ad measurement.

For these reasons and more, most advertisers will need to adopt multiple forms of identity resolution and measurement in the post-cookie world. Many brands are already investing in technologies like customer data platforms and identity graphs to better collect and make sense of first-party data, and they’re looking for solutions that can integrate other sources of data to drive efficiencies and optimizations. For healthcare marketers, it’s imperative that any data used during this process is fully anonymized and remains HIPAA compliant, which is where data clean rooms come into play.

Data clean rooms – unifying first and third-party sources in a privacy-safe way

Even the most analytical digital marketers today are limited in their ability to understand ad performance among specific groups across channels with any degree of granularity. Put simply, identity resolution is hard. Doing it in a privacy-safe way is even harder.

To do so this way requires the use of a data clean room where organizations can safely aggregate anonymized data from different platforms or lines of business and combine it with ad data for analysis. For example, let’s say a pharma brand wants to understand the impact of a recent HCP campaign. Using a data clean room, the brand can use impression data and CRM data from Salesforce to see how sales and marketing channels work together to improve the total number of scripts written by HCPs. Alternatively, brands may wish to feed in opted-in, first-party data from patients, such as information shared via web and mobile applications, to analyze patterns for future planning.

Within a data clean room, analytics teams can see which campaigns are working and make more personalized experiences for patients and providers while preserving privacy. This type of analysis will become more and more necessary to drive the same kinds of efficiencies that marketers have previously come to expect with the use of third-party cookies.

The future of addressable advertising in pharma

The end of third-party cookies is not the end of addressable advertising for healthcare marketers. Consider that healthcare marketers can still plan and activate HCP and patient campaigns using first-party data, and publishers will be able to identify returning users with their first-party cookies. Additionally, important emerging channels like connected TV (CTV) do not rely on cookies at all.

Still, the deprecation of third-party cookies will drive significant changes to the broader media landscape. The number of walled gardens will only continue to increase, for example, and addressable inventory will likely consolidate around more reputable publishers who can charge higher audience-based CPMs.

Healthcare marketers will want to hedge against the impact of these changes by asking questions of their tech partners and publishers using first-party identifiers, such as:

  • Does the solution use HIPAA-compliant technologies to ensure patients’ health data remains anonymized?
  • How does the solution ensure that HCPs’ preferences are respected in the advertising value chain?
  • How many media owners and platforms have adopted the solution and to what degree of success?
  • What methods does the solution use to identify cookieless traffic? And will they scale with accuracy while delivering the required ROI?

Google may yet offer another extension to third-party cookies, but healthcare marketers shouldn’t count on it – or wait any longer to try new approaches. Adapting to the post-cookie environment will take testing and iteration to get right, likely using multiple forms of identity resolution and measurement. It’s important to start that process now and ask questions like these to find solutions that can scale in order to mitigate the inevitable impact of these changes.

Anton Yazovskiy, DeepIntent

Anton Yazovskiy is the chief technology officer of DeepIntent. He leads the healthcare marketing technology company’s global engineering team to design solutions that help advertisers positively influence patient health and business outcomes. Before DeepIntent, he held the position of director of engineering at Lineate.