THE WALT DISNEY COMPANY
REGARDLESS OF THE inner turmoil that resulted in November’s news that longtime CEO Bob Iger was returning to unseat his handpicked successor, Disney has managed to do right by Mickey, Iron Man, Luke Skywalker, and all their friends. The company kept its Marvel content fresh during year 15 of its unparalleled run, thanks to stylish campaigns for Thor: Love and Thunder, Doctor Strange in the Multiverse of Madness, and Wakanda Forever, anchored by Angela Basset in a superhero role with remarkable gravitas. Then there was the metamarketing gambit that inserted Marvel Studios’ creative process into Shehulk’s story line. Disney was 2022’s top-grossing film studio for the seventh straight year, drawing in $4.9 billion globally. Disney+, Hulu, and ESPN+ have grown by 57 million subscribers to hit more than 235 million, making the bundle a neck-andneck rival with Netflix.
Along the way, just like Tony Stark, Disney has been tinkering with something extremely powerful behind the scenes. It has developed proprietary audienceand data-targeting capabilities that are lightyears ahead of competitors’, dividing its audience into more than 2,000 active segments (age, income, interests, etc.) and connecting advertisers to its content across streaming, mobile, digital, and connected TV.
Last year, Disney delivered its audience data to a so-called data clean room: cloud-based software that allows advertisers and agencies to bring their own data to match with Disney’s in a way that complies with privacy regulations.
The goal, according to Dana Mcgraw, senior vice president of audience modeling and data science at Disney Advertising, is to place the most relevant advertising on each platform (e.g., an ad that someone sees while watching Willow on Disney+ should not only be different from an ad someone sees on the ESPN app, but different from what a different viewer sees while watching Willow). So far, this tech has enabled Disney to triple and sometimes quadruple the match rates of relevant ads to audience, without compromising data privacy.
“In the clean room environment, data does not exchange hands,” says Mcgraw, explaining that parties can
“see it and understand it without moving it.” Welcome to the real Magic Kingdom.
E.L.F. (WHICH STANDS for “eyes, lips, face”) may sit beside L’oréal and Revlon on shelves at Walgreens, Ulta, and Target, but its leaders also view it as an entertainment company, servicing a huge audience of followers across its social platforms. “When you have 14 million people showing up on your doorstep every day,” says CMO Kory Marchisotto, “you can’t just sell them a product, you have to entertain them.”
Known for its affordable, fair-trade products and beloved “dupes” of high-end items, E.l.f. began partnering three years ago with marketer Movers+shakers on inventive digital work that went viral. Its 2019 #eyeslipsface campaign, with original music by producer
Ill Wayno, garnered 7 billion views. Today, E.l.f. is supercharging that strategy via usergenerated content. It debuted a short film last winter made of user videos, drawing more than 400 million impressions, and used a Tiktok talent search to help Simon Fuller select makeup artists for his pop group the Future X. E.l.f. also taps a range of influencers: In December, Meghan Trainor filmed a “radiance report” with the Weather Channel to promote E.l.f.’s restocking of its breakout 2022 product, the $14 Halo Glow Liquid Filter.
E.l.f. is experimenting with other platforms: A 2020 relationship with gamer Loserfruit led E.l.f. to launch the beauty industry’s first Twitch channel.
The company followed up with a gamerfocused product line last year. E.l.f. also became the first beauty brand on Bereal.
All of this helped E.l.f. grow sales in the fiscal third quarter of 2022 by 49% to $146.5 million, its 16th consecutive quarter of net sales growth. And in February, the company debuted a cheeky Super Bowl ad, starring Jennifer Coolidge.
DEEPMIND FOR PUTTING DRUG DISCOVERY ON WARP SPEED
LONDON-BASED ARTIFICIAL intelligence research lab Deepmind—founded in 2010 and acquired by Alphabet in 2014— built its reputation by developing AI that can beat humans across a range of difficult games, including chess, poker, and strategy game Go. Although these accomplishments display AI’S cognitive and reasoning capabilities, providing useful benchmarks, Deepmind founder Demis Hassabis says the goal has always been “to develop general purpose algorithms using games as a convenient test platform, and apply them to real-world problems.”
In July, Deepmind proved it’s no longer just playing games, rolling out 200 million entries to Alphafold, its open-access database of 3D protein structures, dwarfing the 350,000 that it launched with in summer 2021. The additional structures—basically, the entire protein universe—are a massive gift to scientists working in drug discovery, synthetic biology, and nanomaterials. Rather than undertaking the difficult and costly process of determining protein structures via crystallography and electron microscopy, Alphafold uses machine learning to predict 3D protein shapes based on their one-dimensional amino acid sequence, cutting the time for determining protein structure from years or months to hours, minutes, or even seconds—a prospect that has fueled adoption among pharma companies and researchers. Hassabis also heads Isomorphic Labs, Deepmind’s drug R&D spinout, where, he says, Alphafold will help researchers study dynamic protein interactions to see “if you have the structure of a protein, can you now find a molecule that will bind to the right part of it?”