Netflix vs Facebook: Who Has The Better Business Model?

A tale of two business models.

Both Facebook (Meta) and Netflix are leading Tech companies. Part of the illustrious FAANG.

However, Facebook’s ARPU (Average Revenue Per User) of $207 is higher than Netflix’s ARPU of $194 even though Facebook is free for users.

How can a social media platform beat out one of the biggest streaming services in the world in terms of revenue per user?

The answer is their different business models and monetization of new features.

Facebook collects data on its users’ behaviors, interests, and preferences, which allows advertisers to target their ads with unprecedented accuracy. This, in turn, leads to higher engagement rates and more revenue for Facebook.

Recently, Meta’s daily active users rose 4% to a better-than-expected 2.04B, and monthly active users were 2.99B, all thanks to Reels. Stories and other imrpoved product features.

On the other hand, Netflix relies primarily on its subscription model for revenue, which doesn’t allow for the same level of targeted advertising. While Netflix has experimented with advertising in the past, its primary focus remains on providing content to its subscribers.

Additionally, Facebook has other revenue streams such as Oculus, its virtual reality platform, and WhatsApp, its messaging app. These platforms also contribute to Facebook’s impressive ARPU.

What are your thoughts on these business model differences?

Related Posts

Escaping AI PoC Hell: Why AI Initiatives Stall—and How to Move Forward

Despite big budgets and big promises, most AI projects never move beyond the proof-of-concept stage. Discover why 97% of generative AI initiatives fail to show business value—and the 5 proven strategies successful leaders use to break free and scale AI impact.

AI and the New Breed of CIOs: Why IT Leadership Matters More Than Ever

As AI reshapes the business landscape, the CIO has emerged from the shadows to become a strategic leader. No longer just IT gatekeepers, today’s “AI CIOs” are driving transformation, leading responsible AI, and shaping enterprise innovation from the top.

From Queries to Autonomy: Mapping the Evolution of Agentic AI

Agentic AI is progressing from simple Q&A bots to autonomous systems that drive real business outcomes. This post breaks down the four levels—from Query Agents to fully Autonomous Agents—and offers leaders a roadmap to scale AI-driven decision-making, efficiency, and innovation.

OpenAI’s GPT-4o Image Generation: Redefining AI Creativity

OpenAI’s GPT-4o Image Generation redefines AI creativity with improved precision, text rendering, and contextual understanding. It eliminates common issues like distorted features and unclear text, making it ideal for design, marketing, and content creation. Accessible to all users, it opens new possibilities for AI-driven visuals

OpenAI’s Agents SDK: The Future of AI-Powered Digital Employees

OpenAI’s Agents SDK enables developers to build AI-powered digital employees that perform tasks autonomously. With core primitives like Agents, Tools, and Handoffs, AI can now search, analyze, and collaborate seamlessly. The future of AI-driven automation is here.

The USB-C Moment for AI: Introducing the Model Context Protocol (MCP)

The Model Context Protocol (MCP) is the USB-C for AI, creating a universal standard for seamless AI-data integration. No more custom connectors—just secure, scalable, and efficient AI interactions. Companies like Block and Replit are already leveraging MCP to bridge AI with real-world datasets. Is this the future of AI integration?
Scroll to Top