Network Effect:

Introduction

Over the last 25 years, global internet adoption, the rise of cloud computing, and the explosive growth and usage of smartphones have impacted nearly every aspect of our lives. However, the impact of these technologies isn’t limited to individual consumers. Several companies in the technology sector have benefitted greatly from the “network effect”–the phenomenon where the value of a product or service increases as more people use it. Take WhatsApp and Instagram as examples. As more users join the apps, the more likely they are to find friends, family, and groups to engage with through pictures, videos, and posts.

This is the second article in our series of articles on “A Brief Overview of Moats: Creating Undeniable Advantage for Businesses”. In this article, we discuss network effects as a source of a sustainable competitive advantage and discuss an analytical framework.

Network effect moat definition

A network Effect moat is a phenomenon whereby a good or service becomes more valuable when more people use it. Network Effect relates to a company’s network of its services or customers. Every additional user contributes to the value of the company’s product or service and makes its competitive advantage stronger. It is also important to remember that all network effects are not necessarily good and may be detrimental to equity if the quality of service deteriorates due to having too many users. The network effect moat is a strong one, however, and can remain sustainable even if a business is run by inefficient management. Network effects can also ensure that there are high barriers to entry. The dominant player in a network enjoys a virtuous cycle that causes the smaller networks to shrink.

The term "critical mass" is often used in connection with the network effect. If the user base for a product or service reaches a critical mass, the network is likely to expand under its own power. Ultimately, however, a company’s ability to monetize a network is also important to consider before the network effect can be assigned as a moat source.

Examples Of Network Effects

Many of today’s most popular companies and startups are heavily influenced by network effects, such as:

• E-Commerce: eBay, Etsy, Amazon, Alibaba

• Ticket Exchange: StubHub, Ticketmaster, SeatGeek

• Rideshare: Uber, Lyft

• Delivery: Grubhub, DoorDash, Uber Eats, Instacart, Postmates

• Social Media: Facebook, Twitter, Instagram, LinkedIn, Snapchat, Pinterest

Direct And Indirect Network Effects

Not all network effects are the same. They’re often broken into two different types: direct and indirect.

Direct network effects occur when the value of a product, service, or platform increases simply because the number of users increases, causing the network itself to grow. Social media platforms primarily benefit from direct network effects because the service's value grows as a direct result of attracting more users. Direct network effects are also known as same-side effects. Another example of Direct network effects is the telephone, it is only useful if the people that you need to reach also have telephones.

Indirect network effects, on the other hand, occur when a platform or service depends on two or more user groups, such as producers and consumers, buyers and sellers, or users and developers. Indirect network effects are also known as cross-side effects. As more people from one group join the platform, the other group receives a greater value amount. Taking Uber as an example, as more riders (i.e. consumers) join the platform, the more useful and valuable it is to drivers (i.e. producers) because they have more business opportunities.

Network Effects and Pricing

Before pricing your product, service, or platform, it’s crucial to understand whether your market is subject to network effects. Why? Because the underlying logic that guides a typical pricing strategy reverses itself in markets where network effects are felt strongest.

To maximize profit margin, businesses typically price their products as high as possible without exceeding their customers’ willingness to pay. But when a market is subject to network effects, the driving concern isn’t so much profit as it is market share—especially early on.

This is because future customers’ willingness to pay depends on the number of existing users. By growing your market share early, you increase your ability to raise prices at a later date, once you’ve taken advantage of network effects and driven adoption of your offering as much as possible. For this reason, many companies price their products low early on or give them away for free.

Optimizing For Network Effects Using 5C

Beyond user acquisition, platforms can be designed with features that boost network effects. These five features can be broken down into five design steps called The 5 C’s of Network Effects: Connection, Communication, Collaboration, Curation, and Community.

Step 1: Connection

Connection refers to user onboarding and their ability to find others on the platform. How easy is it for users to find the right counter parties to buy from, sell to, share and collaborate with, etc.?

Step 2: Communication

Communication between users should be as seamless as possible, allowing for the greatest ease-of-use. Seamless mobile syncing is a must-have as well.

Step 3: Curation

Curation maintains the usability and integrity of your platform by keeping the quality of your users and content high and easily searchable. To ensure quality, platforms must focus on two aspects of the platform: user access (who is on the platform) and content/catalog curation (what is on the platform). For example, eBay bans the sale of live animals on its platform. Secondly, from a design perspective, it should be easy for users to find any product, service, content or counterparty.

Step 4: Collaboration

Collaboration enables users to self-organize into new networks that advance the specific agendas that are important to them individually. For example, Etsy users self-sort by interest into groups within the marketplace. Reddit’s subreddits perform the same function within the content platform.

Step 5: Community

The final step, community, grants users a sense of ownership of the platform, such as when a user edits a fact on Wikipedia, rates an app in Google Play, or flags inappropriate content on Facebook. In a sense, it’s user-enforced curation. It not only gives users a sense of ownership over the platform’s quality, but it also provides platform managers with invaluable user feedback. For example, what type of content are users of Facebook finding objectionable, and why?

Once a platform has optimized The Five C’s, the growth generated through network effects can be a powerful force that leads to scale that’s unachievable with linear business models. Curation and Community feedback and participation provide steady guardrails for runaway growth, while Connection, Communication, and Collaboration attracts users and keep them coming to the platform over and over again.

Financial returns of network effects

As a platform scales, its costs per unit sold decreases logarithmically (see figure below). In comparison, linear businesses are constrained by a U-shaped cost-per-unit curve as they increase sales. To understand why, consider a linear business manufacturing lumber. Initially, as the company grows, it benefits from economies of scale as its operations become more efficient and can process large quantities of wood at lower costs. However, to address the total market available to the lumber company, it must invest significant resources in expanding its capacity in order to produce more lumber and sell more inventory.

In contrast, a platform grows not by buying more assets, but by acquiring more users, which has a near-zero cost. For example, when Uber wants to add more cars to its platform, it just needs to attract new drivers to its network, not buy more cars. This costs the platform next to nothing.

Conclusion

Network effects are the strongest forms of competitive advantage. While these moats have platforms at their hearts, all platforms do not make for NE-based moats. Neither do all networks make for moats. The width of competitive advantages that such moats possess means that these businesses are very hard to unsettle. Yet, such moats are extremely rare. In a world where every other technologically driven business it being touted as a NE business, we hope that the framework we have discussed will help the analyst segregate the true network effect moats businesses from those posing as network effect moats.