A look at Digiday’s most popular WTF explainers in 2022

Digiday sets out to explain complex and difficult-to-understand topics in our ongoing explainer series, called WTF.

Taking the opportunity to see what topics readers wanted most explained, here’s a look at some of Digiday Media’s most popular articles from our WTF series:

WTF is a decentralized autonomous organization (DAO)

Decentralized autonomous organizations (DAOs) were described by Media Editor Kayleigh Barber as “kind of like clubs for crypto enthusiasts.” Here’s a look at the history of how DAOs — pronounced “dows” — were created and what they mean for the marketing and media industries. Read WTF is a DAO here.

WTF is Web3?

Digital worlds and their communities and currencies were of keen interest to readers all year. In this explainer, Barber broke down what Web3 means, how to access it and how it’s different from Web 1.0 or Web 2.0. Read WTF is Web3 here.

WTF is Google’s Topics?

In this explainer, Senior Reporter, Advertising Technology Ronan Shields explained how Google’s alternative to third-party cookies actually works — and how it differs from Google’s prior attempts at replacing cookies (looking at you, FLoC). Senior Media Editor Tim Peterson also offers a handy breakdown over video. Read (and watch) this WTF explainer here.

WTF is marketing mix modeling?

Speaking of data, as CMOs navigate these inconsistently measured times, they’re turning to marketing mix modeling to prove their worth to leadership. Hear from Senior Marketing Editor Kristina Monllos on what that looks like and watch Peterson break marketing mix modeling down over video. Read (and watch) WTF is marketing mix modeling here.

WTF is automatic content recognition?

As Peterson lays out in this explainer and accompanying video: “Your TV is listening. And watching.” In this WTF article, he breaks down what that means for the TV viewership data that is accumulated by listening and what companies like LG, Roku, Samsung and Vizio are doing with it. Read (and watch) WTF is automatic content recognition here.


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