IAB Europe Updates Advice on Ad Targeting Without Third-Party Cookies

February 17, 2021Alerts

IAB Europe has updated its Guide to Post Third-Party Cookie Era. The guide provides a detailed overview of the various targeting techniques used today and some options and consideration going forward.

Key Takeaways

The Issue

  • A 2019 Google study showed that publisher ad revenue decreases by 52% when third-party cookies are not present in ad inventory.
  • In an ecosystem without third-party cookies, proprietary platforms may be able to offer targeting based on a substantial amount of directly-identifiable, first-party data. However, in return for accessing the wealth of data, proprietary platforms may impose restrictions in control and transparency to buyers.
  • Estimates show that 70% of buyers rely on third-party cookies in 2020, therefore not only will advertisers be unable to segment users, but campaigns won't be able to run due to a reduction in data from the buy-side.
  • Without the choice of an open internet, consumers will have to increasingly pay to consume premium content or access it within proprietary platforms.
  • Rather than trying to replicate or find a “work around” for third-party cookies, it's critical for advertisers and publishers to gain maximum value from first-party data derived from direct to consumer touch points, as well as to diversify their activity beyond the proprietary platform.

Starting to Adapt

  • While the depletion of cookies is the latest significant change in the industry, ad verification and measurement can certainly adapt to a cookie-depleted world and has already started to.
  • Ad verification: Most ad verification does not need to rely on cookies to detect fraud, deliver brand safety or measure viewability. Verification solutions will therefore be able to continue as before.
  • Measurement: The following can be used going forward:
    • Partnerships can be formed with publishers, networks and measurement companies to match passive exposure and respondent data
    • Specific media consumption questions can still be used to model probability of exposure where passive exposure tracking is not possible
    • Controlled exposure (online or in-person) lab approaches
    • Advanced analytics
    • Experimental designs such as A/B split market testing
    • Working with publishers that can identify the exposure of their users on their platforms, and deliver surveys within their live environments for single site analysis
    • Custom approaches can be developed with purpose-built passive exposure tracking panels.

Alternative Approaches to the Use of Third-Party Cookies 

Identity-Based Solutions

  • CRM data and email
  • Data clean rooms: Safe spaces where insights gleaned from platforms such as Facebook and Google are commingled with first-party data from marketers, for measurement, attribution and targeting. Data clean rooms can operate independently from Facebook and Google. Some onboarding providers offer them as an extension of their offering, and can be used to run statistical modelling on first-party data alone and/or statistical modelling on enriched first-party data (first-party data + ID provider third-party graph).
  • First party telco operator data: These profiles are created on a per-publisher basis and are not a uniform ID. Leveraging telco-verified audience data allows advertisers to reach real audiences in real time and at scale using verified data, which has been collected and consented to at first party data owner level.
  • Shared ID solutions/consortium:  A shared ID combines user identity from across multiple websites to allow publishers to transact on one shared ID (per user).

Use of Other Advertising Data to Make Targeting Decisions

Contextual Intelligence

  • Contextual targeting is not analyzing previous browsing behavior or historical content favorability. This means it does not rely on cookies to effectively match content to people in a current mindset. Instead it is focused on a deeper understanding of the context of the page.
  • In the most basic form this can be done by seeking keywords on a page to classify that particular page. More advanced approaches can analyze and assess the relationship between the words on the page to deliver a deeper contextualization relevant for advertisers.
  • Another way of describing this approach is “mindset marketing,” a consumer-centric strategy in which advertisers design campaigns to match the mindset of the customers viewing them, based on the placement and content around each ad.
  • However, for contextual engagement to be most effective, marketers require cross-publisher identifiers to measure what happens after the exposure and to properly attribute credit to those publishers.

Odia Kagan is a partner in the firm's Privacy & Data Security Practice and Chair of the GDPR Compliance & International Privacy Practice. For questions about this alert or assistance with AdTech-related issues, contact Odia at [email protected] or 215.444.7313.