FIRST-PARTY DATA: NEW KEYS TO A NEW KINGDOM

There have been many chapters in this unfolding story: Europe’s GDPR introduced in 2016 and the California Protection Act introduced in 2018, key documentaries like “The Great Hack” in 2019 and “The Social Dilemma” in 2020. But nothing has made the data industry scramble and reorganize priorities like Google’s announcement in January 2020, that Google Chrome would be deprecating 3rd-party cookies within 24 months’ time.

In September 2020, as you might imagine, marketers and advertisers are still reconciling with this new reality, which I’ve been heard called “the cookie-pocalypse,” as it heralds the end of a digital advertising industry valued at about $565 billion dollars.

For those readers of mine who don’t work in digital advertising or marketing, “cookies” are pieces of code that are built that identify you when you’re on a website, and then follow you around as you leave the site and go to other places on the web. Cookies gather and store information about you as you go. Your browsing and purchasing patterns, your location, the news you watch and even your interactions with some quizzes and personality tests, are all fair game, as cookies gather and codify all of that behavior, to help categorize you into what are called “audiences.”

Harvard Professor Shoshana Zuboff, who coined the term “Surveillance Capitalism”

It’s essentially the same approach that TV, newspapers, and even billboard advertisers took in the days before the internet, when advertisers know the general income levels, family structure, ethnicity and education levels of a town. The basic idea is, Know your audience so that you can sell to them with a higher chance of them buying. In the world of digital advertising, these audiences are built off of what is known as third-party data in the advertising world, and, interestingly and compellingly, surveillance capitalism by the social psychology world.

In my seat, working in the world of data since the dawn of Web 2.0 in the mid-aughts, I’ve seen the analytics & data world swing from being enamored with first-party data, to being enamored with third-party data. This meant the rise of salespeople, media, smoke-and-mirrors language, and a focus on sales outcomes in data. Today, as we swing back to the world of first-party data, I expect to see the the focus shift back to the nitty-gritty. The new data “rock stars” will be the Data Strategy folk, the Engineers, the Quality Control folk, the Ops folk–in essence, those who really and truly sweat the details. All of these disciplines are becoming mission-critical as we see Personalization and Loyalty plays replace Audiences and Acquisition plays.

Visual Sciences Workstation, Circa 2006.

And that, my friends, is because first-party data takes a ton of loving upkeep and care to be done well. First-party data is data that is generated on a website/platform as users interact with it. (In my Data 101 class, I like to take my students on a “first party data party,” to show how it works.) Think, for example, of the data that Amazon has, or the New York Times, or Facebook–rich, deep datasets that allow for these companies to serve you content that is predicted to be what you’d like.

In the world of first-party data, a whole new set of characteristics take priority. Taxonomy (data-labeling), the nesting of metrics and dimensions, categorization of subject matter, identifying “journeys” you might take as you research and finally purchase that N-95 or that dustpan….all of that takes precedent over Audiences.

In the world of data right now, as the future of audiences and third-party data as we know it is dim, the rise of the first-party dataset has come once again. Here in the industry, I’m seeing an increased focus on my beloved discipline Tag Ops, which my colleague Zack and I built over several years at SSW. The increased focus on Quality Control and taxonomy will make the industry less amenable to salespeople who use smoke-and-mirrors language to sell audiences, and more amenable to thinkers who are very comfortable with levels of high specificity in data-labeling.

I’m here for it.

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