All You Need Is a Network Effect: How Great Tech and AI Products Compete
Every aspiring tech startup yearns to become an extraordinary company, but what exactly sets apart the great ones? Let us delve into the intriguing world of tech greatness together.
Top companies by market capitalization
Take a look at the most valued companies in the world and behold the power of tech. Out of the top ten, a staggering seven are tech giants: Apple, Microsoft, Alphabet, Amazon, NVIDIA, Meta, and Tesla. Four of these behemoths have reached the trillion-dollar milestone, while the others boast capitalizations in the hundreds of billions.
Products that generate 70%+ of the company revenue
Now, let’s turn our attention to the products responsible for the success of six out of these seven companies (we’ll save Tesla for later). Despite their diverse and extensive product portfolios, each of these companies relies on just two or three products to generate 70%+ of their revenue. Curious minds may wonder: if a mere two products can propel a company into trillion-dollar territory, why haven’t others copied their formula? Nevertheless, this list remains remarkably stable over the years, just like the products that keep these enterprises at the pinnacle of success.
This intriguing phenomenon suggests that there is something inherently difficult, if not impossible, about replicating these products. The cost of imitation holds the key to long-term success in the business realm. While capitalizing on fleeting trends and speculative expectations can yield hefty profits, a truly sustainable business strategy requires addressing a fundamental question: “Why can someone else not build a similar company and grab a part of our market share?” Today, we are going to explore how the companies on this list answer this pivotal question.
To unravel the sustainable competitive advantages employed by these tech giants, we can categorize their products into four distinct groups.
The first group constitutes platforms. Picture Apple’s iPhone and iMac, Microsoft’s Azure, Office, and Windows, Google Cloud, AWS, and NVIDIA’s Graphics and Compute series. These platforms lay the foundation for an array of third-party products that not only thrive individually but also contribute to the platform value experienced by their customers.
Take a moment to appreciate Windows, one of the most successful platforms of all time. As more and more PC users embrace Windows, its allure grows for software developers. And with each new application that supports Windows, the platform itself becomes increasingly valuable for new and new PC users. This virtuous cycle, embedded within the ingenious Windows 95 product strategy, propelled Microsoft to its eminent status and sent Bill Gates to the pinnacle of the Forbes list.
Now, let’s shift our focus to AWS, Amazon’s cloud platform. While it possesses a marketplace, the primary value feedback loop operates on a different premise. As developers build more products with AWS, their familiarity with the platform deepens, and the support for AWS among the open-source and third-party technologies expands. And consequently, the flourishing community of developers and the thriving technology ecosystem render AWS the platform of choice for more and more products and companies. This phenomenon is reminiscent of programming languages, where popularity fosters a rich framework, library, and technology ecosystem, consequently enhancing the language’s appeal to developers even further.
You may see the same platform effect in action in iPhone and iMac with AppStore, in Azure and Google Cloud, and in Microsoft Office and NVIDIA products as well.
Platforms possess an astounding resilience when faced with head-to-head competition. The perceived value of a platform stems from both the platform itself and the ecosystem it nurtures. In this equation, a weaker platform with a robust ecosystem beats a superior platform with a lesser ecosystem. There is a long history of failed head-to-head platform competition attempts, starting with operating systems of the 80th and 90th and ending up with Windows Mobile.
Interestingly, it may be hard to appreciate the platform when you see it at the early stage. When Apple announced iPhone, then-Microsoft CEO Steve Ballmer infamously predicted that “there’s no chance that the iPhone is going to get any significant market share.”
On the one hand, a bad analogy is here to blame: many experts compared iPhone to IBM PCs and expected it to follow the same route with the swarm of follow-up clones devouring the margins of the pioneering company. They did not realize that IBM made several intellectual property management mistakes that cost their IBM PC platform its market share, and Apple learned how to avoid them.
On the other hand, Apple almost failed iPhone in its unique Apple way: Steve Jobs at first resisted introducing SDK and AppStore, wanting Apple to be the only company building software for iPhone. Behind the scenes, Apple board member Art Levinson and SVP of worldwide product marketing Phil Schiller were pressing Jobs to change his mind. In many ways, their vision was pivotal to making Apple the company it is today. Without Levinson, Schiller, and others pushing for making iPhone a platform, we would have seldom talked about Apple or Steve Jobs today.
The second product group, clustered under Meta’s umbrella, are social networks.
Social networks are a realm familiar to most of us, as we have all interacted with them at some point in our digital lives. Within these products, each user creates value for all other users. These products are not as much about technology or algorithms as they are about people connections. In this niche, even a technically weaker product boasting a larger user base beats a superior one with fewer users. An attempt to grab a market share away from the established social network product in a head-on competition is an incredibly tough endeavour. Many of us still recall the rise and fall of Google Plus, a great product that ultimately succumbed to the overwhelming dominance of Facebook. As a wise teenage daughter of a Google Plus developer once remarked, “Dad, the social network is where the people are.”
The same effect determines the resilience of Instagram and WhatsApp products from this list.
The only marketplace product in this list is, though, truly colossal: it is Amazon Store.
Marketplaces bring together two distinct user groups: sellers and buyers. Within this environment, each buyer creates value for all sellers, and vice versa: each seller contributes to the product's value for all buyers. Engaging in head-to-head competition with a marketplace presents a formidable challenge. You must attract both groups and navigate the perplexing “chicken and egg” dilemma. To entice buyers to your marketplace, you need sellers, and to attract sellers, you must first have buyers.
The final group in this list constitutes AI products: Google Search and YouTube.
These products harness the power of artificial intelligence, accumulating vast amounts of data and utilizing them with machine learning techniques to continuously enhance product performance. The AI competitive advantage lies not in the algorithms but in the wealth of data these products possess. Google Search, for instance, leverages our historical search queries and interactions, complemented by the troves of data collected through various Alphabet products. Our Gmail emails, YouTube searches, views, and interactions, browsing data from Google Chrome, and even phone usage data from Android devices all contribute to the intricate user models and embeddings that Google meticulously constructs for each of us. These personalized user models and our search queries enable Google Search to present us with tailored and relevant search results. As the search results improve, we find ourselves returning to Google for further searches, thus providing the company with even more data to enrich our individual user models.
As an integral part of the Google ecosystem, YouTube follows a similar pattern. It harnesses your YouTube search, view, and interaction data, in conjunction with the data from other Alphabet products, to enhance your overall experience. The more YouTube videos you engage with, the better their recommendation systems become, offering you a wealth of captivating and relevant content to explore further. And as you take on these recommendations, you generate more data for YouTube to bring you even more relevant recommendations.
In simple words, AI competitive advantage boils down to the product design that benefits from the AI models combined with the AI models improving with the product usage data.
AI virtuous cycle
Remarkably, all these four strategies converge into a single phenomenon known as the network effect. In economic terms, the network effect refers to the concept that certain products grow more value to each individual customer as their customer base enlarges. This phenomenon has been studied extensively since the mid-20th century. One of the earliest examples can be found in the realm of early telecommunication companies: the more users a phone company has, the more valuable its phone service becomes for each of them. Among all the variety of tech products and companies, we can clearly see the largest and most successful of them thrive because of different forms of network effect strategies.
Network Effects in Big Tech products
Obviously, these are not the only business models offering a sustainable competitive advantage. You may build one relying on:
government-established monopolies, like Saudi Aramco,
personal connections and reputation, like Berkshire Hathaway,
patents, like Johnson & Johnson,
economy of scale, like Exxon Mobil,
chainlink effect, like Ikea,
or brand loyalty, like Coca-Cola and Tesla.
Or you can invent your own business model offering a sustainable competitive advantage. Remember, though, that it should have a clear answer to the question: “Why can someone else not build a similar company and grab a part of our market share?”
You may also notice that these big tech companies try to combine multiple competitive strategies to strengthen further their competitive barriers: Apple builds brand loyalty, Facebook includes platform capabilities, and YouTube adds social networking features. Yet, in this analysis, I tried to focus on a single competitive strategy that entrenches the product in its market: if iPhone loses brand power, it will lose a fraction of the market share, but if it loses AppStore, it loses it all.
Does implementing a sustainable competitive advantage strategy guarantee you success? By no means. In 2019, Harvard Business Review published a study of over 250 platform startups and why most failed. The reasons include pricing, trust, timing and the ability to learn from failures. But the absence of a competitive strategy almost certainly dooms your company since the emergence of a competent competitor is only a matter of time.
This blog is dedicated to AI competitive advantage, and we are doing our best to explain how it works and how you can build one for your product or company. You can check our other posts to get an extensive explanation of what the network effect is and how AI enables it, how to build an AI competitive advantage for your company, what culture helps you build the right AI products, what to avoid in your AI strategy and execution, and more.
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