What CMOs Need to Know About the End of Third-Party Cookies
After twenty-eight years of hard work—cooking up valuable data and delivering user-based insights into the hands of hungry marketers—third-party cookies are about to crumble.
But should this really be a surprise?
With the way technology has evolved, measurement, tracking, and data collection would inevitably change too. Coming into the 20th century, tech giants began using cookies to relentlessly track users and serve up ads while user privacy began to dissolve. Despite privacy laws, the fear of “cookie scraping” to collect private information, and relentless stories of data hacks in the news and media, consumers are tense. According to TechRepublic, 86% of consumers surveyed by KPGM see data privacy as a growing concern (2021). Needless to say, the “cookie monster” is inevitably doomed.
For marketers that rely on cookies to target the right audience, amplify customer experiences, and directly correlate impressions to campaigns and ad spend, what does the demise of the third-party cookie mean? What alternative solutions are available to elevate marketing’s effectiveness? Within this blog we put cookies into context:
- What Are Third-Party Cookies?
- The History of Third Party Cookies
- Consumer’s Growing Data Privacy Concerns
- A Phase-Out of Third-Party Cookies
- Alternative Options to Third-Party Cookies
- What’s Next: Embracing A No-Cookie Method to Marketing Measurement and Optimization
What Are Third-Party Cookies?
According to the FTC, “A cookie is information saved by your web browser. When you visit a website, the site may place a cookie on your web browser so it can recognize your device in the future.”
Third-party cookies are simply cookies from domains other than your own. They are used for a variety of reasons, from providing a more personalized online experience to tracking and targeting consumer behaviors on third-party sites. Third-party cookies are appealing because they give marketers the ability to track consumer activity across broader stretches of the internet, not just their own sites.
For example, if I am selling flower arrangements at flowers.com, I might drop cookies in the user’s browser registry telling me who that user is, their username, or places they’ve been using my domain–these would be first-party cookies. Third-party cookies are cookies that have been dropped onto my own website such as weddings.com to target potential clients.
The availability of consumer information through third-party cookies has been invaluable to marketers. Data analysis techniques like multi-touch attribution (MTA) heavily rely on the ability to link a consumer across multiple ad platforms.
The History of Third-Party Cookies
Now that you have an idea of what third-party cookies are, you’re probably wondering how they came to be. Quartz details that Lou Montulli invented the cookie in 1994. As an engineer at Netscape, he set out to solve the problem of anonymity–when a user comes into a site. How can that user be identified as the same person as they travel from page to page? This invention made it possible for users to keep their shopping cart as they navigate e-commerce sites. This small file traveled as the user moved and eventually evolved into tracking cross-websites–into third-party cookies–following millions of users.
Consumer’s Growing Data Privacy Concerns
It wasn’t until a few years later that the public became aware of cookies. The idea that connecting the dots, a deep knowledge of your likes, dislikes, and even private activities could be surfaced was seen as a threat. In a perfect world for advertisers, all cookies would be interoperable and transparent allowing every advertiser to know every time an individual was exposed to a message, and what they did about it. Of course, this perfect world for advertisers is a privacy nightmare for many consumers. Even in 2019, Forbes reported that “46% of customers [felt] they’[d] lost control over their own data” in a survey that was conducted by Salesforce. While some argue that better tracking allows for “more relevant ads” (and indeed, this is the positioning that Facebook and other huge networks use when asking for permission to track on iOS), perfect tracking of individuals as they go about their digital lives is a dystopian idea for many others.
A Phase-Out of Third-Party Cookies
Let’s face it, using third-party cookies is getting harder and harder. Stories of data breaches at large-scale companies like Yahoo and Facebook, along with general news-spurred anxiety about foreign data interference, have led to an increase in consumer concerns over data privacy. Legislative pushes like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) marked a worldwide shift towards increased data privacy regulations. The demand for online privacy often overrules desires for greater efficiency and personalization. Ultimately posing a difficult task for marketers seeking to balance these priorities.
Furthermore, in a bid for consumer trust, Google announced in 2020 that it would be phasing out third-party cookies on the Chrome browser. Consumers and marketing were largely supportive of this change, but some claimed that this was simply a move to bolster control over customer information. Regardless of the intent, Google’s decision dealt a significant blow to the availability of third-party cookies. Considering Chrome is the most commonly used browser in the world, with about 65% market share according to Match2One. With Chrome’s cookies set to crumble by 2023, more tech companies like Apple are joining the trend towards greater consumer privacy and data siloing.
This decline in consumer information availability has caused uncertainty among marketers. Hubspot revealed that 41% cite the inability to track relevant data as their biggest upcoming challenge and 44% predict a 5-25% increase in spending needed to achieve the desired ROIs. Coupled with other budgetary and data management problems, few marketers feel prepared for the post-cookie world.
Alternative Options to Third-Party Cookies
Google has opened doors to other options, however. Google’s Privacy Sandbox initiative previously included its Federal Learning of Cohorts (FLoC). FLoC would allow companies to continue tracking online behaviors with differential privacy, looking on the cohort level but not the individual level. Users’ online behavior via browser history would have been stored within a group of similar online users, a “cohort,” for analytical use. This solution, further explained in “What Is Google’s FLoC, and How Will it Track You Online?” by John Bogna, claimed to balance users’ demand for privacy with companies’ desires for targeted marketing analysis.
In January 2022, after FLoC trials and feedback, Google announced ‘Topics’ would replace the FLoC proposal. Topics API is interest-based advertising, where your top interests are determined from a week’s worth of browser history. With three weeks of backlog, any provider that participates will only receive three topics—one from each week to share. There is also a plan to allow users to remove topics or disable them completely in Chrome.
In addition, users can consider moving cookies in-house. We learned from “It’s not just cookies: Rebuild marketing and privacy for a new playing field” by Jay Cline and Andrea Fishman, another approach is to bring cookies in-house. By shifting to a syndicated or partially-owned cloud system to track first-party data and develop consumer identity graphs, companies can track customers in more private ways. Data clean rooms—in which customer data are either physically or virtually locked and accessible only by encrypted IDs—are also increasingly attractive, particularly for industries with particularly sensitive data, such as financial services and health care. Solutions like these can be developed with a knowledgeable internal team, or through partnerships with tech experts. IAB Tech Lab or Partnership for Responsible Addressable Media also known as PRAM are two examples.
What’s Next: Embracing A No-Cookie Method to Marketing Measurement & Optimization
The fact is, tracking users on an individual basis is sunsetting. A more sophisticated marketing measurement and attribution approach can help enterprises effectively evaluate and optimize upper and mid-funnel investments. Moving beyond cookies to understand buyers from an ethnographic level will aid a deeper understanding of channel performance. (By ethnographic level we mean researchers observe and/or interact with a study’s participants in their real-life, non-cookie environment.) To develop the right model we suggest addressing these questions in your modeling both upfront and in review to ensure sound and actionable results.
Which channels are driving which results? Goal: Accurately apportion value derived from channel stimulus to different response channels.
- Response Curves
How does marketing effectiveness change with increasing spending? Goal: Estimate how channels lose marginal effectiveness as spending increases.
- Lag Effects
How long does it take for results to show up? Goal: Estimate how long it takes for marketing’s impact to manifest, and how long it lasts post-stimulus.
- Market Context
How do competitive efforts impact return? Goal: Control for the broader market dynamics.
Aggregated Multi-touch Attribution Modeling
Adopting an aggregated multi-touch attribution model that looks at the effect of multiple marketing investments on last-touch channels over a period of time best answers the questions above. Aggregate multi-touch attribution is similar to media mix modeling but measures the impacts on siloed, coded response measures. This additionally allows for a full understanding of your marketing halo and how each channel drives attribution to other channels.
How MarketBridge Builds Aggregated Multi-touch Attribution Models for Our Clients
- Data Aggregation
Extract and transform historical marketing stimulus, response, and market control data into panel time series data sets using reproducible methods (e.g., Python stored in version control software, like Git).
- Build Initial Models
Beginning with significant executive, marketer, and data scientist interviews, iterate and finalize models to estimate cost per acquisition, contribution, diminishing returns (elasticity), and ROI by channel/objective.
- Embed Models into Monthly Processes and Reporting
Continuously identify new areas of improvement, account for new market and marketing dynamics, and adjust model parameters (and potential overall structure.)
- Strategic Decision Making and Optimal ROI
Optimize marketing over the short- and long-run to maximize efficiency and drive growth.
We believe marketing analytics is becoming more transparent and reproducible. In other words, more code-based and less cookie-based. By integrating best practices in direct response measurement with econometric modeling, marketers can understand how channels drive demand between them and optimize their mix.
Analysts with Gartner and McKinsey Propose 4 Strategies to Prepare for the Post-Cookie World:
- Start the Shift from third-party cookies early
Just because third-party cookies are becoming obsolete doesn’t mean that the benefit of other direct consumer measurements will be. Advertisers and publishers with vast pools of first-party data and demand-side platforms that have their own consumer IDs will be in an advantageous position in the post-cookie world.
- Adapt to a walled garden world
Just as companies should look inward to develop their data collection structures, they should also become comfortable relying on direct media buys for data from “walled gardens” (powerhouses like Google, Facebook, and Amazon).
- Rethink data collection and measurement practices
Work from the already known information about the customer to improve the consumer experience and gain the consumer’s trust. This may be easier for companies with stronger consumer engagement like retail and finance. Although, this will be essential for other industries. In addition, overhaul current strategies to prepare for an “era of advertising experimentation”. Companies should invest in market research, reassess measurement baselines, and establish resource connections whether that be software or corporate partnerships.
- Prepare for sustained disruption
Prepare for the coming effects of privacy and identity changes. You can do this by re-evaluating the media mix and budget allocations to cookie-related media.