Latest / Business Strategy Talks with Fexingo: Competitive Advantage, Market Positioning, and Growth Planning / How Netflix Built a Moat in Original Content
Transcript
- Lucas: So Netflix spends seventeen billion dollars on content this year. That's more than the GDP of about thirty-five countries. And almost all of it goes into originals now — seven hundred plus series and films per year, their own stuff. Luna: Seventeen billion — that number keeps growing. But is the spending itself the moat, or is it something else? Lucas: Good question. The spending gets the headlines, but the moat is really in how they decide what to spend on. Netflix doesn't greenlight projects the way Hollywood does — gut feeling, track record of the director, a hot script. They greenlight based on data from their own platform. Luna: Right, the algorithm knows what you watched, what you paused, what you rewatched. That feeds into what they produce. Lucas: Exactly. When they decided to greenlight 'House of Cards' back in 2013, they knew that subscribers who liked the original British version also watched movies directed by David Fincher and starring Kevin Spacey. The intersection of those three data points was large enough to justify the investment. That was the first big proof point. Luna: And that approach scales. 'Stranger Things', 'The Crown', 'Squid Game' — all hits that came from data insights, not just creative hunches. Lucas: Let's talk about 'Squid Game' specifically. That show was a Korean-language survival drama with no big stars internationally. A traditional studio would have passed or given it a tiny budget. Netflix looked at their global data and saw that Korean content had a passionate, growing audience outside Korea. They bet forty million dollars on it — and it became their biggest series launch ever, generating nearly nine hundred million dollars in impact value. Luna: So the data gives them confidence to take risks that others can't. That's the moat — the feedback loop between what audiences actually watch and what gets made. Lucas: That's the engine. And it's reinforced by another layer: the recommendation algorithm itself. Netflix's homepage is personalized for each subscriber. If you like thrillers, you see thriller originals. That drives discovery and engagement. The more you watch, the better the algorithm gets, the more you stick around. It's a flywheel. Luna: It also explains why they spend so much on originals. If they license content from Disney or NBC, they can't control the algorithm around it — and they can lose it when the license expires. Lucas: That's the second piece. Licensing is renting. Originals are owning. When Netflix started, they licensed everything. But as studios launched their own streaming services — Disney+, HBO Max, Peacock — they pulled their content. Netflix saw that coming. They started Originals in 2013, and by 2019, they were spending fifteen billion a year. By 2026, it's seventeen billion. They own the IP, so the content stays. Luna: And that IP becomes part of the brand. You don't subscribe to Netflix for 'Friends' reruns anymore. You subscribe for the next 'Stranger Things' season. Lucas: Precisely. A 2025 survey from Deloitte found that sixty-two percent of U.S. streaming subscribers said original content was the primary reason they kept a service. Netflix has the deepest bench of any platform. They release new originals every week — it's relentless. Luna: But can Disney+ or Apple TV+ catch up? They're spending too — Disney's content budget is around thirty billion annually, but a lot of that is sports and theatrical. Lucas: Disney has strong IP — Marvel, Star Wars, Pixar. But those are big, expensive bets, and they don't have the data engine Netflix has. Disney+ just started using personalized recommendations recently. Netflix has been refining theirs for over a decade. Also, Disney's content is more narrow — family-friendly, franchise-driven. Netflix covers every genre, every country. Luna: That global reach is another moat. Netflix produces in over fifty countries. They have local originals that appeal to local audiences and sometimes cross over globally — like 'Squid Game', 'Lupin', 'Money Heist'. Lucas: It's a distribution advantage. They have two hundred sixty million subscribers in over one hundred ninety countries. If they make a show in India, it gets seen globally. That scale means they can amortize the cost of a local show across a global base. Local broadcasters can't do that. Luna: So the moat is three things: data-driven greenlighting, owned IP, and global distribution scale. But what about the debt? Netflix has taken on a lot of debt to fund this content. Lucas: They did. At its peak in 2020, Netflix had about fifteen billion dollars in long-term debt. But they've been generating positive free cash flow since 2021. In 2025, they generated over six billion in free cash flow. They're now funding content from operations, not borrowing. That's a big shift. Luna: Still, the content spend is huge. If subscriber growth slows further, can they sustain it? They added about eight million subscribers in 2025, down from peaks. Lucas: That's the risk. But they have pricing power. They've raised prices multiple times, and churn remains low — around two to three percent per month in mature markets. The content keeps people hooked. Also, they have the ad-supported tier now, which is growing. That opens a new revenue stream without raising subscription prices for everyone. Luna: Good point. The ad tier launched in late 2022, and by 2025 it had forty million subscribers. That's incremental revenue, around five to six dollars per user per month from ads. Lucas: So the moat is not just about content — it's about the whole system: data, IP, global distribution, and now multiple revenue models. Competitors can copy one piece, but copying the whole machine is incredibly hard. Luna: If these conversations have moved your work forward in some small way, there's a simple way to support the show. We deliberately don't run ads on these — that's a choice we've made from the start. Lucas: Yeah, and that choice depends on listeners who appreciate it. If you want to keep this ad-free, the link is buy me a coffee dot com slash fexingo. No pressure, no perks — just a way to say the content matters. Luna: Agreed. Now, back to the moat — one thing I find fascinating is how Netflix uses data not just to greenlight shows, but to optimize the artwork. Lucas: Oh, the A/B testing on artwork is legendary. For a single show, they might test dozens of thumbnail images. If you like romantic comedies, you see a couple embracing. If you like action, you see an explosion. The same show, different artwork, different click-through rates. Luna: That's micro-optimization, but it adds up. Higher click-through means more viewing, which feeds the algorithm, which improves retention. It's a compounding effect. Lucas: Exactly. And it's something competitors overlook because it's not flashy. Disney+ still uses the same poster art for everyone. That's a subtle advantage that over millions of subscribers drives real engagement differences. Luna: Let's talk about the risk of over-reliance on data. Could it lead to formulaic content? Some critics say Netflix originals can feel algorithmic — safe, predictable. Lucas: It's a valid critique. Data can tell you what has worked, but not what will work that's truly new. That's why Netflix also gives creative freedom to top talent. They let Shonda Rhimes and the Coen brothers make what they want. The data helps reduce risk on the majority of projects, but they still swing for the fences on prestige projects. Luna: So the moat is a balance. Use data to minimize misses, but retain the ability to take creative risks. That hybrid model is hard to replicate. Lucas: And it's protected by another factor: time. Netflix has been doing this for thirteen years. The data set they have — trillions of viewing hours across two hundred sixty million users — no one else has that. Not Disney, not Amazon, not Apple. That data advantage compounds. Luna: So what's the one takeaway for someone building a moat in their own business? Lucas: Find a feedback loop that gets better the more you use it. For Netflix, it's the data to content to engagement loop. For your business, it could be customer usage data improving your product, which drives more usage. That's a moat that gets stronger over time, not weaker. Luna: And own your core asset. For Netflix, it's the IP. For others, it might be proprietary data, a unique process, or a community. If you rent it, you're vulnerable. Lucas: Good summary. Next episode, we'll look at a company that tried to copy Netflix's model and why it didn't work. Until then.