Episode 69 How Oatly used the messenger effect to become the world's most successful milk alternative
In this episode, we explore how Oatly became a billion-dollar brand by using behavioral science in clever, unexpected ways. We unpack how the launch of their Barista Edition—crafted specifically for coffee shops—tapped into the Messenger Effect, where who delivers a message matters as much as what is said. Along the way, we break down what makes a messenger truly persuasive—and how your brand can apply the same principles to win trust and grow.
Episode Highlights
Neutral messengers are often more persuasive than self-interested ones. A small shift—like a colleague delivering praise instead of the person themselves—can meaningfully boost credibility and conversion rates.
Levine's study shows how quickly identity framing can influence behavior. Man U fans were far more likely to help a jogger wearing their team's shirt—unless primed to see all football fans as part of their in-group.
Three key takeaways: The messenger matters as much as the message; credibility, relatability, neutrality, and status make for strong messengers; and never rely on self-reports—people often misread their own motivations.
Resources & Useful Links
See below for additional resources from this week's episode.
Keep Listening
Ep51 - Interview: Seth Stephens-Davidowitz, author of Everybody Lies, on how to uncover hidden consumer motivations
MichaelAaron and Richard sit down with economist and data scientist Seth Stephens-Davidowitz, who reveals why direct questions often don't reveal one's true motivations. They also unpack concepts like the illusion of effort, the curse of knowledge, and how to handle conflicting datasets effectively.
Ep50 - The replication crisis: How to avoid basing your marketing on bogus findings
This episode dives into a concept known as "replication crisis" in behavioral science. We explore how repeated attempts to replicate certain studies have yielded results that challenge or contradict the original findings, calling their validity into question. We highlight some well-known studies to be cautious of and share practical advice on how to ensure the findings you apply are reliable.
