Latest / Business Strategy Talks with Fexingo: Competitive Advantage, Market Positioning, and Growth Planning / How The New York Times Built a Subscription Moat
Transcript
- Lucas: So last year, the New York Times crossed eleven million subscribers. That's up from about six million in 2020. And the really interesting part is that almost all of that growth is digital-only. Luna: It's a pretty dramatic turnaround. I remember when everyone thought print was dead and the Times would go the way of local papers. Lucas: Exactly. And the key insight is that the Times realized they weren't in the news business per se — they were in the trust business. They invested in quality journalism, deeper reporting, and they made it a habit for readers to start their day with the Times. That habit is incredibly sticky. Luna: But isn't there a ceiling? How many people are willing to pay for news in a world of free content? Lucas: That's the interesting part. They've shown that pricing power exists if the value is clear. They've raised prices multiple times and churn remains low. The moat is the brand and the habit. Plus they've added adjacent products like Cooking, Games, Wirecutter, and The Athletic — each deepens the subscription value. Luna: So it's a portfolio approach. The New York Times is becoming a bundle of premium services that each attract and retain different segments. Lucas: Right. And that bundle makes it harder to cancel. If you're thinking about leaving, you lose not just the news but your Wordle streak, your saved recipes, your product review history. That's a real switching cost. Luna: I remember they bought The Athletic for about $550 million in 2022. A lot of people questioned that deal at the time. Lucas: And now it's a key part of the bundle. The Athletic brought in a sports audience that might not otherwise subscribe to the Times. Plus it added another layer of content that makes the overall subscription more valuable. Luna: What about the data side? I know they use personalization to keep readers engaged. Lucas: That's a big piece. They have a recommendation engine that pushes relevant stories, and they're constantly A-B testing headlines and placements. The more you read, the more they learn about your interests, and the harder it is to leave because the experience gets tailored to you. Luna: So it's a network effect of data? More readers mean better recommendations, which mean more engagement, which mean more data. Lucas: Exactly. And that data advantage is a real moat. A new entrant would need years of reader behavior to match the Times's ability to keep people coming back. Plus, the Times has a massive archive — millions of articles spanning over a century. No startup can replicate that. Luna: That's a point about scale. The fixed cost of journalism is high, but when you spread it over millions of subscribers, the per-unit cost gets very low. Lucas: Right. And they've been aggressive about cost discipline. They cut the print side, reduced headcount in non-core areas, and focused digital investment on the products that drive retention. The result: their operating margin in the digital segment has been improving steadily. Luna: What about the advertising side? That used to be their main revenue source. Lucas: It's still significant, but it's no longer the driver. In 2020, advertising revenue was about $400 million; by 2025, it had dropped to around $300 million. But subscription revenue grew from $1.2 billion to over $2 billion in the same period. So they've successfully shifted the center of gravity. Luna: That's a textbook pivot. And it's not like they abandoned ads entirely — they still have a digital ad business, but it's now secondary to the subscription model. Lucas: Right. And that gives them more pricing power. When your primary revenue comes from readers, you can afford to say no to certain advertisers. It aligns the incentives with the audience, not the advertisers. Luna: So the moat is really a combination of brand trust, habit, data, scale, and a bundled product portfolio. That's pretty defensible. Lucas: It is. And it's a reminder that moats don't have to be technological. They can be built on intangible assets like trust and habit, especially when those are reinforced by real switching costs. Luna: If these conversations have moved your work forward in some small way, listener support is what keeps this show ad-free. If you'd like to help, you can buy us a coffee at buy me a coffee dot com slash fexingo. No pressure, just an option if the show has value for you. Lucas: Yeah, and it really does make a difference. Every contribution helps us keep the focus on the ideas and not on sponsors. So back to the Times: one more interesting angle is how they've handled the rise of AI. Luna: Oh, that's a hot topic. They've been vocal about protecting their content from being used to train models without compensation. Lucas: They were one of the first to block OpenAI's crawler and to negotiate licensing deals. That's actually another moat — the archive becomes a valuable asset that AI companies want access to. So the Times can generate revenue by licensing its data, while competitors without the archive can't. Luna: So in a way, AI could be a tailwind for them if they manage the licensing well. Lucas: Exactly. And that's the thing about a strong moat: it gives you options. The Times isn't just surviving; it's in a position to shape its own future. That's the power of a well-built subscription business. Luna: And a reminder that even in a disrupted industry, strategy and execution can create durability. Lucas: Absolutely. On that note, we'll be back next episode with another deep dive into a company that built a unique competitive advantage. Thanks for listening.