Part I. Why Network Effects Are Important

Network effects are mechanisms in a product and business where every new user makes the product/service/experience more valuable to every other user.

Network effects are important because they are the best form of defensibility, and thus value creation, in the digital world (the three other major defensibilities are brand, embedding, and scale)

Part II – How Networks Work

networks are interconnected systems of people or things

Nodes and Links

networks are made up of nodes and links

Nodes are the network participants: consumers, devices, customers, buyers, sellers, brokers, etc. Different types of nodes can have very different roles within the same network.

Nodes within the same network can differ in terms of their levels of impact, influence, power, and value

Central nodes are the nodes in a network with a high number of links and are often more valuable

Marginal nodes have relatively few links and typically have less value — although there can be exceptions if marginal nodes are connected to a few powerful nodes themselves

network size can be measured by the total number of nodes in a network

size of a network alone doesn’t determine value, because the amount of activity in a network can vary

Links are the connections between nodes or groups of nodes in a network

Links vary in terms of strength, which is a function of the durability, closeness, and activity between two nodes

Network Density

The density of a network is determined by its ratio of links to nodes. The higher the ratio, the denser the network.

the higher the density of a network, the more powerful its network effects are

Look for the “white-hot center” of your network — the densest, highest activity part —and focus the product features and language on activating other users to behave more like that group. Their activity will attract other nodes who will be inspired by the activity of the “white-hot” group, and it will radiate outward from there much faster than you might think.

Directionality

In graph theory, which is an aspect of network science, a link between nodes can be either directed or undirected

Whether a graph is directed or undirected depends on the nature of the connections between the nodes of a network. If the connections are directed, it means that one node points to the other in an unreciprocated fashion.

The direction of a link between nodes in a network is determined by which way, if any, the interaction between nodes in a network flows.

Clustering

When two clusters are connected by a solitary link, but are otherwise unconnected and isolated from each other, that link is called a bridge

The networks with higher degrees of clustering, measured by a “clustering coefficient”, can have the very powerful network effects as described by Reed’s Law

posits exponential increases in value as a network grows

network with a high clustering coefficient will increase exponentially in value while it grows, while a network with low clustering will increase in value at a slower rate

Critical Mass

critical mass of a network refers to the point at which the value produced by the network exceeds the value of the product itself and of competing products. This can happen at different times depending on the type of a network

Most products with network effects must ultimately reach critical mass in order to fully take advantage of the defensibility provided by their network effects

Before the size of the network reaches critical mass, the product remains quite vulnerable and may not have much value to users. For such products, the challenge is often to build enough initial value to incentivize early adopters to start using the product even before the network effects value has kicked in.

The Network “Laws”

They’re simply math concepts that describe the relationships between different types of networks and the value of those networks

Sarnoff’s Law

Sarnoff observed that the value of his network seemed to increase in direct proportion to the size of the network — proportional to N, where N is the total number of users on the network.

accurate description of broadcast networks with a few central nodes broadcasting to many marginal nodes (a radio or television audience).

Metcalfe’s Law

Metcalfe’s Law states the value of a communications network grows in proportion to the square of the number of users on the network (N^2 where N is the total number of users on the network).

Metcalfe’s Law seems to hold because the number of links between nodes on a network increase mathematically at a rate of N^2, where N is the number of nodes

Reed’s Law

many kinds of value grow proportionally to network size” and that some grow as a proportion to the square of network size, he suggested that “group-forming networks” that allow for the formation of clusters (as described above) scale value even faster than other networks

Group-forming networks, according to Reed, increase in value a rate of 2^N, where N is the total number of nodes on the network.

reason why Reed suggested a formula of 2^N instead of N^2 is because the number of possible groups within a network that “supports easy group communication” is much higher than 1, so that the total number of connections in the network (the network density) is not just a function of the total number of nodes (N^2).

function of the total number of nodes plus the total number of possible sub-groupings or clusters, which scales at a much faster rate with the addition of more users to the network

Part III – Network Properties

Irregularity

Networks are not usually uniform in real life. They just look that way in diagrams. They have clusters, hot spots, and dead spots. These mirror the irregularities of complex systems in the real world

You need to recognize these irregularities, find the “white-hot center” within the network, and focus on it initially to build up a network effect before you expand your focus to the broader network.

Real Identity vs Pseudonymity vs Anonymity

Networks with profiles tied to a node’s real identity, like your real personal name or real company name, are typically more effective at building network effects than networks with pseudonymous profiles

Real Identity is also critical in two-sided marketplace and platform network effect businesses where trust and reputation facilitate the liquidity of transactions.

One caveat: there are some applications, in crypto or government spy work, where anonymity is a necessary feature of the network.

Privacy is different from anonymity.

Asymmetry

relates mostly to marketplaces, whether that marketplace is 1, 2, 3, or N-sided. In nearly every marketplace, one side, or one type of node, is harder to acquire than the other.

harder side of the marketplace is the demand side — the buyers. Usually in this scenario, if you can manage to attract people who are willing to pay (buyers), suppliers (sellers) will show up quickly and without as much effort. We call this a “demand-side marketplace”.

harder side is the supply, and demand-side users are attracted to the marketplace organically once the supply side is robust. We call this a “supply-side marketplace.”

Another asymmetry in marketplaces relates to the asymmetry within a side or within a type of node. In other words, not all supply or demand is made equal. Typically, there are certain nodes who will prove more valuable to get on your network, sometimes proving up to 1,000X more valuable than other nodes.

Homogeneous vs. Heterogeneous Networks

Homogeneous networks are networks where all the nodes have the same function in the network. One user is interchangeable with the next in the basic function they perform

Heterogeneous networks are networks where there are two or more classes of nodes categorized by both function and utility

Asymptotic Network Effects

Asymptotic network effects are network effects with diminishing returns

Recall the basic definition of network effects: as usage of a product grows, its value to each user also grows.

Growth in an asymptotic network, after a certain size, no longer benefits the existing users