• This article is part of our Future of Addressability series. Contributors are industry leaders invited to share their perspectives on  how marketers can  successfully navigate changes brought on by the deprecation of third-party cookies.


    Earlier this year, Google announced that they would be phasing out support for third-party cookies within two years. Google wasn’t the first to implement sweeping measures to restrict interaction with user data. Apple and Mozilla both updated their browsers in 2019, although their combined global market share amounts to less than one-third of Chrome’s. 

    We sat down with Jon Taylor, Essence’s EVP of Global Data Strategy, to understand how his agency is approaching the end of cookies and advising the brands they represent. 

    1. How are cookies currently being used by media agencies, from planning to measurement?

    Many of the tools and tactics employed by media agencies over the last decade have relied on third-party cookies, spawning categories and subcategories of solutions to problems with ad spend deployment and optimization. An advertiser might target audience segments provided by their data management platform (DMP) or third-party data provider who use cookies to track site visits or browsing behavior. 

    Once media is in flight, cookies are used to manage frequency and avoid over-exposure across platforms. Finally, that advertiser will need to measure the effectiveness of that campaign and may use view-through conversion tracking or multi-touch attribution models which both rely on cookies for the ability to track sales across platforms. 

    2. How are agencies, and by extension the brands they serve, preparing for a cookieless future?

    Hopefully, most agencies and brands read the writing on the wall as far back as 2018 and have been innovating solutions with a more privacy-first mindset. There are more representative, aggregated data sets which can be applied alongside granular first-party data to produce wide-ranging answers for brands seeking growth and audience insights. In addition to building new data sets, we’ve been working with clients to adapt new tools and methods, making them available not just to statisticians, but across marketing and media teams. 

    I expect low-code and no-code alternatives to subject matter expert (SME)-level solutions will only increase, making the ability to “ask the right question” one of the most critical skills for anyone on the team. 

    3. Would you be able to hazard a guess as to whether or not most companies are adapting quickly enough to the deprecation of cookies and frankly, much of the way the Mar Tech ecosystem uses them?

    In general, you’d have to assume the market is underprepared at this point. Marketing technology flourished using the cookie as its primary currency for over a decade and you can’t expect the industry to pivot out of that in a few months.

    That being said, brands need to accelerate and prioritize their identity strategy and start to gain clarity from their partners about how they intend to approach an absence of cookies. Any misalignment could have major consequences for the interoperability of marketers’ tech stack components.

    Moreover, an open and commercial web faces headwinds if the stakeholders in it, such as industry bodies and the various ID consortia, can’t align on a widespread solution. 

    4. How has Essence prepared for this new reality?

    We’ve spent years using and experimenting with tools like Google’s Ads Data Hub, Big Query, and other machine learning and clean room offerings. We had been using the wealth of data available in data transfer (DT) logs to inform planning and optimization, but we have embraced the ability to run comparable analyses in aggregated and anonymized ways that meet the expectations not only of regulations like GDPR, but also the expectations of consumersmany of whom are increasingly aware of what data is available and how it’s being used. 

    As an agency, we’ve always prioritized transparency and curiosity, which makes our practitioners uniquely well-suited to the new world of cookieless media. 

    5. What advice do you have for companies that haven’t yet prepared?

    I think there are five things every marketing team should be doing over the near to mid-term.

    1. Think big(ger) data models—explore more representative, aggregated, and slower-moving types of data to complement granular, programmable data.
    2. Revamp (and radicalize) research—set objectives for what you are trying to learn from your data and ensure it’s compiled in machine learning-friendly formats.
    3. The power of partnerships—make data a part of broader conversations with your media partners, not just in terms of audience targeting, but also research and insights.
    4. Augment the tech stack—ensure you have a clear (diagrammatic!) view of your current marketing and tech stack and how they share data. Identify where cookies are used and quickly test and implement addressable solutions that will continue to enable targeting, measurement, personalization, etc.
    5. Analytics everywhere—review low-code AI/machine-learning tools and services and look for opportunities to pilot, experiment, and test with your team to understand which can be used by nonanalytic practitioners and which require SMEs.

    Much of the innovation in ad tech and marketing measurement will be seen as a reaction to outside forces like privacy regulation, but creating a more transparent and sustainable model for the commercial web is also the right thing to do regardless. The expectation of today’s consumer is that their personalized marketing experiences are considerate, additive, and provided with their permission.

    Therefore, advertisers and agencies alike should welcome and lean into new legislation like CCPA, accelerate and prioritize their identity strategy, and embrace the challenge of a diminishing degree of user-level data. We need to find the courage to focus our analytic abilities on a bigger target that encompasses a broader and more varied dataset. And while doing so, we need to align on new codes of ethics for data, for our teams and our partners, to move beyond the notion of compliance and towards doing the right thing for consumers. As we develop these new models, we need to place an emphasis on explainability, not only for regulators, but for our wider organizations, to empower and inspire them with new knowledge and possibilities.

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