Understanding Implications of the Cookieless Future

/ Thoughtspace - Advanced Measurement, Strategy, Targeting

Google’s announcement that Chrome will no longer support cookies as of 2023 has many digital marketers concerned about their cookieless future. Marketers that have historically relied on cookies to reach their target audiences and measure success will be greatly affected by this change and many are actively working on the next steps to avoid campaign performance declines. The actions taken by marketers in this pre-cookieless environment will help to shape and define the future of targeted advertising and performance metrics. 

“Businesses and advertising professionals will need to better understand how customers make decisions, what actions are valuable for businesses and bring that all together when showing success.” – Maggie Gotszling

Why are cookies important and how do they work?

Cookies are a backend line of code on a website that helps advertisers track a user’s behavior across the internet and includes 3rd party tracking pixels from platforms such as Facebook. The tracking of these activities makes it possible for advertisers to effectively deliver ads to their target audiences and directly measure and attribute conversions. With the deprecation of cookies, that tracking will no longer be viable, effectively blinding some targeting and measurement capabilities on which many marketers currently rely.  

What does it mean for campaign targeting strategies?

The major impact will be on retargeting third-party cookie-based audiences. It is recommended that advertisers begin shifting overreliance on this tactic and begin testing alternative targeting options to fill the gaps. Gathering first and second-party data (which is owned by publishers) will be central to an effective digital market strategy in a post-cookie environment. Additionally, the use of contextual targeting does not rely on cookies and provides brands with a strong opportunity to be able to generate increased brand awareness when done strategically. As an additional benefit, the cost of contextual advertising tends to be substantially lower than addressable impressions as data is not layered on, though costs are impacted by whether the tactic is targeted through a whitelist or contracted with a private marketplace deal.

Definitions and tips for collecting zero, first, and second party data

Zero party data: Coined by Forrester, Zero-Party data is collected when “a customer intentionally and proactively shares with a brand. It can include preference center data, purchase intentions, personal context, and how the individual wants the brand to recognize [them].” 

How to collect Zero Party Data:

  • Surveys
  • Polls

Tip: Don’t ask for too much too often and create poll fatigue on the consumer.

First party data: Observed behaviors of users who interact with your company. 

How to collect first party data: 

Form submissions or other forms of contact sharing on

  • Mobile apps 
  • Websites 
  • Social media 
  • SMS 
  • Email
  • Customer service platforms
  • Point of purchase

Second party data: Second Party Data is First Party Data collected by one company that they privately share with another company. For instance, when a publisher allows another company to use their CRM data to reach a target audience that overlaps with their own. An example of this would be if a brand were to work with Drizly, an online alcohol retailer, to reach their target audience of active digital alcohol shoppers. 

“Brands need to reestablish expectations for programmatic and be open to experiment with alternative targeting and measurement solutions. Ideally, this will happen in 2022 while we still have access to data that is likely to be lost.” – Savannah Westbrock

What impacts will we see on measurement?

Cookies have been the underpinning for most digital marketing performance measurements for over twenty years, including post-click and post-view conversions and attribution for sales impact. For example, the Facebook ecosystem will be heavily disrupted in attribution of conversion-based events, largely due to their reliance on mobile ad IDs for measurement. Historically, marketers have leaned heavily into Facebook and other walled garden environments due to their ability to evaluate strength ROI based on the multiple touchpoints that go into a final purchase, facilitated by the placement of a tracking pixel on the brand’s website. 

However, these walled garden pixels are defined as a third party cookie and will be limited in their ability to pass back data once the elimination of the cookie is mobilized. As a whole, we can expect  campaign performance on the front end to decline as compared to previous years, even if the backend business performance remains the same. Brands and teams should start to plan for shifts in attribution and performance as we get closer to the 2023 depreciation.

Fortunately, there are potential workarounds. For example, brands can overlay their conversion-based data found on Google analytics to match up on site conversion with Facebook mobile IDs after the fact. This helps level media metrics back up to business goals, but requires more analysis and less “real-time” results. Tests and conversations in 2021 can prepare in advance for performance declines and reduce a sense of panic. 

Post-cookie ID-based solutions for targeting and measurement

There are also multiple cookie alternatives in development that promise to bridge the addressability gap that will be created when cookies are deprecated. Here are a few of the options currently out there or in development.

Google’s Topics:

Google is developing a solution for targeting called Topics. Similar but slightly different than its predecessor FLoCs, Topics uses an individual’s browsing activity to tag them with broad interest categories, or topics, that can be used to target ads to that individual in the future. For instance, if a user visits Nike’s website, they may be tagged with an interest in fitness.  When ads are served to this user, their browser will choose, at random, three of that user’s top five topics based on the previous three weeks’ browsing history. Those three topics are then shared with the advertiser as a tool to serve relevant ads to the user during their visit. This method allows the advertiser to target based on interest without using identifiers or other potentially invasive data points.

Standard Universal IDs: 

Originally used as a way to combat mismatched data when syncing cookie data across domains, companies like The Trade Desk, LiveRamp, and IAB have developed what are known as Universal IDs. This standardized identifier allows advertisers to buy into a community of shared data to track audience activity across the internet. The primary concern with Universal IDs, however, is that they still currently rely on third-party cookies, without which they are unable to set or recognize identifiers across domains. 

Encrypted Universal IDs:

Understanding the original design of Universal IDs would no longer be effective once cookies were depreciated, companies like LiveIntent (nonID) and The Trade Desk (Unified ID 2.0) started developing encrypted identifiers using email addresses instead of cookies to track user activity. The primary hurdle with email-based IDs is that they require users to provide and consistently use the same email across websites in order to build an accurate profile. If the user is unwilling to provide that data, or different emails are used for different sites, advertisers will be blind to their activity and be unable to target them accurately.

While all of these solutions have their pros and cons, they are all worth monitoring as they continue to develop as they will be key in building targeting and measurement strategies in 2023 and beyond. 

Recommendations to prepare for the cookieless future

  • Plan early & anticipate impacts to your measurement/attribution system. We encourage everyone to have conversations with their clients and agencies to set expectations ahead of time. We’ve outlined a quarterly look at the impact across audiences, e-comm/attribution as well as media mix & creative. 
  • Benchmark your current performance: You can start modeling the impact of third-party cookie blocking by recording your current analytic metrics and monitoring them as the update takes effect. Establishing benchmarks by operating system and browser will enable you to calculate most accurately the potential impact.
  • Apply business intelligence models to your analytics: Predictive analytics can be used along with your data to provide deeper insights for the best performing marketing tactics and identify macro and micro trends that influence your business outcomes.
  • Consolidate media activation to as few platforms as possible: Platforms are developing their own internal frameworks to accurately track and measure marketing performance outside of third-party trackers. The more platforms you execute your media through the more disparate measurement systems you have to take into consideration. There is also the likelihood that you will have duplication across platforms and consolidation will reduce that occurrence. 
  • Expand implementation timelines: Relying on first party data more and needing to run that first party data through an identity solution and then back into a web environment will add time to campaign and ad ops setups. While match rates should improve, campaigns will be moderately more cumbersome to set up, especially as we get used to these new flows. Teams and clients should build in extra cushion.
  • Create new relationships with third-party, cookieless data providers: This is not a new risk in the ad operations system, but an ever present risk that doesn’t go away under a new system. Fortunately, these companies benefit from interoperability and scale. The most important thing brands can do to reduce dependencies is to understand how your audiences and targets are built in each platform and know what’s different depending on the partner. Always ask what’s inside the box or model.

“Brands who have been targeting super-niche audiences will have to reestablish expectations for programmatic and be open to experiment with alternative targeting and measurement solutions. Ideally, this will happen in 2022 while we still have access to data that is likely to be lost.” – Colin Duft

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