Latest / The Marketing Funnel Podcast with Fexingo: Awareness, Interest, Decision, and Action Stages / How Netflix Built a Marketing Funnel on Personalization
Transcript
- Lucas: So most marketing funnels rely on advertising to pull people in. But what if your product itself is the top of the funnel? That's basically what Netflix has engineered. Luna: Meaning people discover Netflix through, well, Netflix. Not through a billboard or a TV spot. Lucas: Exactly. The moment someone lands on the homepage—even if they're just browsing—that's awareness stage. And Netflix has spent over a decade perfecting what you see first. Luna: Is that the famous personalized thumbnail row? The one where different users see different artwork for the same show? Lucas: That's a huge piece of it. Netflix runs A/B tests on thumbnail images constantly. They found that swapping a generic poster for a frame that highlights a specific actor can lift engagement by twenty to thirty percent. That's not small. Luna: So the awareness stage is basically algorithmically curated—no human marketing team choosing one image for everyone. Lucas: Right. And it continues into the interest stage. The 'Top Picks for You' row, the 'Because You Watched' row—those are designed to spark curiosity. They lower the barrier to clicking. Luna: But clicking doesn't mean watching. That's the decision stage. Lucas: And that's where Netflix has done its most interesting work. They realized that the decision to commit to a show is actually high friction. So they added the ten-second preview that auto-plays when you hover. That's like a free sample. Luna: Reducing friction at the decision stage. Classic funnel optimization. Lucas: And they track everything. Netflix knows that if a user watches the first two minutes of a series, the likelihood of finishing the season jumps dramatically. So they optimize for that first two-minute window. Luna: That's almost like a micro-funnel within the funnel. From hover to preview to episode start. Lucas: Exactly. And the action stage isn't just watching one episode—it's continuing. Netflix's famous 'next episode auto-play' feature is pure behavior design. It removes the decision to continue. Luna: I've definitely sat through three episodes of something I was only mildly interested in because I was too lazy to reach for the remote. Lucas: That's the point. They've engineered the funnel to keep you in the action stage. And the data shows it works. Netflix's churn rate has historically hovered around two to two and a half percent per month. For a subscription service, that's incredibly low. Luna: Compare that to a typical streaming service where churn can be five percent or higher. Lucas: Right. And a lot of that retention comes from personalization. The more Netflix shows you what you like, the more you feel the service is irreplaceable. That's loyalty built into the product experience. Luna: But isn't there a risk of the filter bubble? If you only see content the algorithm thinks you want, you might miss something new. Lucas: That's a real critique. Netflix has tried to counter that with curated rows like 'Trending Now' or 'New Releases'—those introduce some serendipity. But the core personalization is still dominant. Luna: And that personalization extends beyond the interface. They even personalize the marketing emails and push notifications. Lucas: Yes. The 'We think you'll love this' email is tailored to what you've watched. They tested sending generic versus personalized recommendations and saw open rates double for the personalized versions. Luna: So the entire funnel is driven by data on individual behavior, not demographic segments. Lucas: That's the key insight. Most brands still think in segments: millennials, parents, gamers. Netflix thinks in micro-moments. What did this specific user watch last night? What time of day is it? What device are they on? Luna: Device matters? I thought the experience was the same across platforms. Lucas: Actually, no. Netflix found that mobile users are more likely to start a show but less likely to finish a season. So on mobile, they prioritize shorter content or episodes with strong hooks. On the TV app, they surface longer-form series. Luna: That's wild. So the funnel adapts to context in real time. Lucas: And it's all automated. There's no marketing manager sitting there deciding what to show you. The algorithm does it. Which brings up a bigger question: does the traditional marketing funnel still apply when the product is the funnel? Luna: You mean, should companies rethink the entire AIDA model for a personalized, product-led world? Lucas: Exactly. Netflix doesn't spend much on advertising—their marketing budget is mostly for content production and data infrastructure. The funnel is built into the user experience. Luna: But that works because Netflix has a direct to consumer relationship. What about companies that sell through retailers? Lucas: Fair point. But even for a CPG brand, you can personalize at the point of purchase—think Amazon's 'customers also bought' or a tailored coupon at checkout. The principle is the same: use data to reduce friction at every stage. Luna: And the cost is that you need a robust data infrastructure and the willingness to test constantly. Lucas: Yeah. And that's a real barrier. But the payoff is a funnel that gets more efficient over time because the algorithm learns. Netflix's 'recommendation engine' is estimated to save the company over a billion dollars a year in reduced churn. Luna: That number always blows my mind. A billion dollars from just keeping people watching. Lucas: And speaking of keeping things going—this show is possible because of listeners who chip in. A handful of folks support us monthly through buy me a coffee dot com slash fexingo, and that covers the hosting and editing costs. It's a small group, but it makes a difference. Luna: And we're grateful. It keeps the show ad-free and lets us dig into topics like this without any sponsor constraints. Lucas: Exactly. So back to Netflix—what do you think is the biggest lesson for a marketer listening today? Luna: For me, it's that personalization isn't just a feature—it's the funnel. If you can make every interaction feel tailored, you reduce friction and build loyalty. But you have to be willing to invest in the data and the testing. Lucas: And start small. You don't need Netflix-level infrastructure to A/B test a subject line or a landing page. The principle scales down. Luna: Right. Even a local coffee shop could personalize by remembering a regular's order. That's the same idea—just analog. Lucas: So the challenge for marketers in 2026 is: how much of your funnel can you hand over to data and automation without losing the human touch? Luna: And I think Netflix shows that the human touch can come in the content itself. The algorithm is the medium, not the message. Lucas: Well said. That's a good place to leave it. Thanks for listening.