How Network Effects Work?
In the first part of the Network Effects series, we talked about 16 types of networks and their importance, which is one of the most important topics that enhance the power of startups and digital products against competitors or other alternatives. Today's article will discuss the principles and characteristics of building a network in more detail and the growth laws of networks.
Table of Contents:
What is a network?
A network consists of links and nodes where nodes represent the entities or parties of the network, and links represent the relationships, transactions, and interactions between these parties. These transactions can be in the form of money, information, communication, or anything else that can be transferred.
Network Properties:
The network density is the ratio between the links and nodes. The higher the ratio, the higher the network density and thus the stronger the network's impact. For example, on Facebook, each person represents a node, and each friendship between two people represents a link. The network density is not evenly distributed throughout the network; some parts are denser than others, creating the clustering phenomenon, which we will explain shortly. In building digital products, you can design the product to reach the highest possible network density by taking the most densely populated and active center of the network and changing the product's properties to match the rest of the network's parties, so they act the same way as the center of the network.
2. Directionality:
Directionality refers to the direction of the link and relationship between any two points in the network and can be directed or undirected. Directed relationships mean that one party consults another in a non-reciprocal manner, such as Twitter followers for a celebrity or politician. On the other hand, an undirected relationship is a relationship where both parties consult each other reciprocally, such as communication media like WhatsApp or Messenger. Most networks have a mix of directed and undirected links.
3. Value Creation Orientation - Same Side Vs Cross Side Vs Indirect:
The first form of value creation orientation is the "Same Side Effect" where the value of one side of the network increases when a new participant joins the same side. A positive example of this is Windows or Google Drive users who benefit from an increase in the number of users on their side as they can share files with a larger number of people. A negative example of this principle is Uber, as having more passengers means higher prices and more waiting time, and having more drivers means higher competition among them.
The second form is the "Cross Side Effect" where the value of one side of the network increases when a new participant joins the other side. The most popular example of this is marketplaces like Amazon and Uber, where there are buyers and sellers.
The third form is the "Indirect Network Effect" which is a combination of the first two forms. It is the same-side value increase effect that happens in conjunction with cross-side value creation. An example of this is Amazon, where there is value creation - Cross Side - between sellers and buyers, but at the same time, there is also an indirect effect between sellers as the existence of more sellers means more customers, which means more benefit for the sellers again.
The final form of the indirect effect differs from the first form of the direct effect from the same side. We can see in this principle that the same network - such as Uber - can have more than one form of value creation orientation at the same time, such as the first, second, and third types. An example of Uber includes a direct and negative network effect from the same side for passengers and drivers, a direct and positive network effect from one side to the other between passengers and drivers, and an indirect and positive network effect between drivers and each other and passengers and each other.
4. One-to-one Vs One-to-Many:
Links in a network can be between two parties - One-to-one - like the relationship between a Facebook user and another user, or it can be a relationship between one party and many - One-to-Many - like the relationship between a content creator on YouTube and their viewers. To connect the different network properties together, you will find that One-to-Many links are directed and interaction moves in one direction, while One-to-One links are undirected and interaction moves in both directions.
5. Clustering:
It is not unusual for networks to be distributed evenly; in reality, there are local clusters that are more connected to each other than to the rest of the network. In the real world, we see the principle of Clustering everywhere, like when you find gold, fabric, or furniture merchants located side by side. In the digital world, we can see Clustering in Facebook groups that can be more active and engaging than the rest of the network. Clustering is an important principle in networks because it is one of the factors that help networks grow exponentially, and you can use tactics to increase the clusters in your network for your benefit.
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6. Irregularity:
This means that the relationships between the parties in the network are unequal, and you will find active clusters and dead spots. We can see real examples of irregular relationships in human relationships, such as the difference between the relationship between a manager and an employee versus the relationship between an employee and their colleague. Another example is the difference in the type of relationships and interactions between a company with ten employees versus a company with a thousand employees. Understanding irregularity is important because it allows you to focus on designing your product starting with the active or central points in the network before expanding to different parties in the network.
7. Identity - Real Identity vs Pseudonymity vs Anonymity:
The identity of network parties can take three forms. The first form is completely unknown - Anonymity. The second form is the pseudonym, which TikTok and Twitter sometimes use. The third and final form is the real identity, like Facebook and LinkedIn. Some networks may offer a combination of identity forms, and usually, the network becomes stronger when real identity is used, especially on multi-sided platforms, because it creates a sense of trust and reputation.
8. Asymmetry:
This concept applies specifically to multi-sided markets and platforms. It refers to the unequal distribution of supply and demand accessibility. In some networks, it is easier to access the demand first, while in other markets, it is easier to access the supply first. Upwork is an example of a network that first monopolizes the demand, followed by the supply. On the other hand, Uber and Talabaat are examples of networks that first monopolize the supply. I discussed this principle in depth in an article I wrote three years ago called "Supply-Constrained Vs Demand-Constrained Markets." You can read it here: https://bit .ly/3sajUMl.
9. Homogeneous vs. Heterogeneous Networks:
Homogeneity in networks refers to when every node in the network performs the same basic function as any other node, such as in a telephone network. On the other hand, heterogeneous networks involve nodes performing at least two or more different roles, such as in platforms and multi-sided markets where the roles of sellers and buyers differ.
10. Switching Costs:
Switching costs refer to the costs a user incurs when switching from one product to another. These costs can be in the form of money, effort, or time. The higher the switching costs, the stronger the customer's connection to a product, which creates a lock-in effect. Companies with sufficient defensive power can make their products incompatible with competitors' products to create higher switching costs. Apple is one example of a company that creates such product incompatibility, as it is difficult to use a Mac computer and an Android phone in terms of effort and time, which locks customers into using future Apple products.
Network Growth:
Types of Growth - Linear Vs Exponential:
There are two types of growth, either Linear Growth - which is growing at a constant rate over time, or Exponential Growth - which is growing at an increasing and proportional rate over time, creating a much larger increase and growth over time. Companies without the influence of networks and without viral spread will usually follow Linear Growth.
Network Growth Laws:
Networks do not grow in the same pattern or speed, there are 3 mathematical laws that can measure network growth.
1.Sarnoff’s Law:
The law states that the value of the network grows in proportion to the number of users (V=n) where N is the total number of users on the network. The law is attributed to David Sarnoff, one of the pioneers of radio and television who held the American radio.
2. Metcalfe’s Law:
The law states that the value of the network grows in proportion to the square of the number of users (V=n^2) where N is the total number of users on the network. And this law is more accurate because the links actually increase mathematically closer to the square of the number of users. The law is attributed to Robert Metcalfe, one of the inventors of Ethernet.
3. Reed’s Law:
The law states that the value of the network grows exponentially with the number of users (V=2^n) where N is the total number of users on the network. And this law suggests that the fastest mode that can be achieved for the network will occur due to clustering, so its equation is larger than the other laws. The reason why the equation became "2 to the power of N" instead of "N to the power of 2" is that the growth of links will not only be based on the number of nodes - N, but also on the number of possible clusters and clusters between them.
Critical Mass:
Critical Mass refers to the point at which the value of a network exceeds the value of the product itself. This point varies for different types of networks and is inversely related to the strength of the network. The stronger the network, the lower the Critical Mass point. Most products strive to reach this point to take advantage of the defensive network effect, as the product is weak and does not provide enough value to its users before reaching this point.
Ultimately, it is important to understand the key characteristics of network building when developing digital products to avoid mistakes that have already been made. In the third part, we will learn about the drawbacks and cons of networks such as the chicken-egg dilemma, platform leakage, and the multi-tenanting problem. We will also look at some proposed solutions for these issues.