AdExplainer

“Measurement” and “currency” are often conflated in TV land, but they’re not the same. They have different standards and use cases – and these contrasts matter as the industry looks for a better way to transact TV ads.

Virginia is for lovers – and privacy lawyers. Although California has attracted most of the attention as the first US state to pass and enact comprehensive data privacy legislation, other states, including Virginia, have been swiftly following suit with regulations of their own.

Although there are important nuances between the different laws, businesses that have been working toward compliance with the California Consumer Privacy Act and California Privacy Rights Act are in a good position for complying with other state privacy statutes. But the CPRA has several unique provisions that make it a beast all its own.

For more than a decade, the ad tech industry has tried to replace the term “fingerprinting” with euphemisms, like probabilistic modeling. But too bad for ad tech, because the term stuck.

Lots of people are talking about addressable TV. “Data-driven linear,” though? Not so much. But despite the fact that data-driven linear (DDL) doesn’t get as much attention as its somewhat sexier addressable cousin, it’s becoming an increasingly popular choice for linear advertisers attempting to make more informed media buys.

Some business practices on the internet may not be against the law, but they undermine or manipulate consumer choice. Legal advocates have coined a new name for this practice: dark patterns. And dark patterns are next up on the enforcement docket both for the Federal Trade Commission and state-level data privacy laws.

The European Parliament adopted the Digital Services Act (DSA) and the Digital Markets Act (DMA) in July. Although they were passed as one legislative package, they function as two distinct laws. But there is one common thread: Holding Big Tech providers more accountable for what happens on their platforms.

Rather than looking at one particular data signal, attention metrics include a variety of data points, which are fed into a machine-learning model to predict the likelihood that a given media environment and ad creative will draw attention from a hypothetical audience member.

Contextual targeting laid the foundations of TV advertising – particularly by ensuring that ads were stitched into content marketers considered “brand safe.” With the advent of CTV, buyers put context on the back-burner in favor of more granular, first-party audience targeting. Now, the pendulum is swinging back again. Why? Two words: signal loss.

Over the past two years, data clean rooms have exploded onto the programmatic advertising scene, and they’re already at the center of some of the most exciting new partnerships and growth opportunities. But despite their rapid adoption, the definition of what a data clean room is – and all of the related nuance – is not well understood.