Why did Facebook pay $19 billion for Whatsapp? Facebook’s valuation of Whatsapp (and it’s Network Effects) must be that high.
As discussed in the previous part, Whatsapp is known for its tightly-knit cluster of users and has one of the strongest Network Effects. I totally understand, Network Effects wouldn’t be the only factor that defined the value of Whatsapp for Facebook.
But it was definitely one of the major factors – Whatsapp has a large subscriber base, especially in some developing nations which will add value to the existing Facebook network of users.
So, how do you value Network Effects? Are there laws associated with the value of a network? Why was Facebook as a social network for users more valuable in its early days as compared to today? Let’s understand.
THIS IS PART 2 OF MY NETWORK EFFECTS SERIES.
- WHAT ARE NETWORK EFFECTS AND WHY ARE THEY IMPORTANT – PART 1
- HOW DO YOU VALUE NETWORK EFFECTS AND THE LAWS OF NETWORK VALUATION – PART 2
- TYPES OF NETWORKS EFFECTS AND VALUING FACEBOOK USING NETWORK EFFECTS – PART 3
- HOW TO BUILD, MAINTAIN & APPLICATIONS OF NETWORK EFFECTS IN DAILY LIFE – PART 4
If you haven’t already, read Part 1 of the series before reading Part 2.
PART 1 SUMMARY
- Network Effect occurs when an additional node (user) has an impact on the network
- The value of the network will increase as more users use the business/product
- Each new user node has different properties. These user nodes and the links between them define a network
- Network Effects are important because the value of the network grows exponentially while the cost (might) increase linearly
- They provide strong defensibility to businesses while being comparatively cheap to implement compared to other defensibilities for Digital Businesses
- Network Effects is so valuable because it facilitates the exchange of information
If there is one thing you have to remember about Network Effects it is that the value of the network increases as more people use it.
HOW DO YOU VALUE A NETWORK? – THE NETWORK LAWS
Let’s start by understanding how you value a network before we dive into valuing Network Effects.
There are 3 main laws when it comes to valuing a network that could translate to valuing the power of Network Effects of that network.
The laws are not scientifically proven. But generally agreed upon with criticism. Just like everything else on the internet.
Some of these laws are outdated but it is important to understand them. It is always good to start from the base.
SARNOFF’S LAW
David Sarnoff who led the Radio Corporation of America noted that on the broadcast radio, the value of a network is proportional to the number of users.
The value of such a network increases linearly. V ∝ N.
An example of this could be radio shows, the value of a show is proportional to the number of users listening to it. Sarnoff observed the effect when he was running a radio show.
It could be somewhat applied today as well – a YouTube channel with 100 subscribers will be less valuable than a YouTube channel with 100,000 subscribers.
But it is not as simple, right? As we moved away from radio show days, the law wasn’t as directly applicable. If we consider YouTube vs. Radio; a YouTube channel has much more functionality such as likes, comments, subscribers which others can see and behave upon compared to radios which are not connected.
Today networks have become more complicated. And the value derived from the network has increased.
METCALFE’S LAW
Robert Metcalfe is the pioneer of the internet and attributed with inventing the Ethernet.
During his research, he observed that the value of the network increases proportionally to the square of nodes of the users connected in the network.
The value of the network increases geometrically i.e. V ∝ N^2.
As NfX states, “Although originally formulated to describe communication networks like Ethernet, fax, or phone networks, with the arrival of the internet it has evolved to describe social networks and marketplaces as well.”
Imagine Facebook users connecting to each other on the platform. I am talking about just the users and not the Facebook groups. This is the network without clusters.
You can see in the diagram above that as the number of nodes increases the links increase significantly and the value derived from such a network will increase n^2 times.
It can also be observed in the book club posts that you see on Instagram, select one person you will be sending a book to and you will get ‘x’ books in return. The bigger the reader network, the more value each reader derives and the more books they get in return.
However, as it applies to most of the ideas in technology, they get outdated as technology progresses.
As networks get more complex, these laws fall apart. For example, it assumes that the value derived from each node is the same. But we have understood in the previous part, the properties for each node are different in networks today.
Another criticism it draws is that the value derived from each user is not the same in the digital world. The law is a simplification of human behavior. Human engagement pattern on any network is far more complex and the timing of user’s joining the network will vary as well. As such, the value derived from each node will be different.
REED’S LAW
David Reed is an American computer scientist and known for his early work on TCP/IP and UDP.
He observed that the value of the network increases based on the ease of sub-group networks that can be created on the network, and hence the value increases exponentially.
The value of such a network is exponential i.e. V ∝ 2^n.
Reed’s Law was published by David Reed of MIT in 1999. While Reed acknowledged that “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.
NfX Bible
These networks allow the formation of clusters and make it really easy to form them. These sub-groups make the network effects really powerful!
“Even Metcalfe’s law understates the value created by a group-forming network [GFN] as it grows. Let’s say you have a GFN with n members. If you add up all the potential two-person groups, three-person groups, and so on that those members could form, the number of possible groups equals 2n. So the value of a GFN increases exponentially, in proportion to 2n. I call that Reed’s Law. And its implications are profound.”
David P. Reed’s, “The Law of the Pack”,
Imagine Facebook groups or Whatsapp groups. Facebook has an added defensibility in the network i.e. it not only allows the users to connect with each other but also creates groups. Hence, it is one of the businesses with the strongest Network effect.
Here is a good summary of the three laws –
It is important to note that these laws have been criticized. Even though the value of these networks can be seen as growing linearly, geometrically, and even, exponentially, when you look at them realistically for businesses, the chances of them holding true are less.
I mean, how many people do you engage with on Instagram or Whatsapp? Even though your network is huge, are you really adding value to every node on your network? And if the users are not adding value, is the network really valuable?
CRITICAL MASS
A network gains value once the critical mass is attained. After the network has reached critical mass, the value of the network increases for existing users.
To imagine this, think of Etsy. If Etsy had one seller and one buyer, the network wouldn’t have had any value. However, once Etsy reached a critical mass of sellers and buyers then only did it become more popular. The network created more value than the product (Etsy) and the competition.
Critical Mass value is different for individual networks.
Lower the critical mass value, quicker the network will create value for the users, and quicker will it grow!
ASYMPTOTIC NETWORK EFFECTS
The simplest definition of Network Effects is that the value of a network increases as more users are added to the network.
However, in some cases, the value stops increasing after it reaches a certain threshold. The value provided by the network stagnates for the users which is called as Asymptotic Network Effect.
A good example could be be Lyft.
Initially, when there are 5 drivers and 100 riders in a new city, the wait time to get a ride will be huge. The value is still low for users to use the network. Once, it reaches its Critical Mass, more users and drivers add more value to the network. But after the network reaches a certain threshold, the wait time will become stagnant. Your wait time will never be less than 4-5 minutes, even after Lyft adds 100 more drivers (riders will increase as well).
The value of such a network and associated Network Effects is low as compared to an exponential network.
Additionally, for businesses, this could depend on the stage of maturity of the network. A network could grow exponentially initially but stagnate after a certain point.
CHICKEN AND EGG PROBLEM
The chicken and egg problem is common in a marketplace network. How do you derive value if your network has neither buyers or sellers?
The sellers need users to buy their products. If there are not enough buyers, how do they sell? On the other hand, if there are buyers but not enough sellers, why would more buyers sign up?
So who should you focus on first to build value for your network? There are a bunch of strategies to solve this problem. 19 strategies to be specific (you can read the chicken-egg strategies here).
The most common way to solve the problem is to have one side derive value from the network and then develop the other side i.e. create a single-player product first.
Facebook users initially used the social network just for networking. This was the value. Facebook marketplace was launched after it reached a certain number of users. By then, the buyers were already on the platform!
NEGATIVE NETWORK EFFECT – NETWORK CONGESTION AND NETWORK POLLUTION
In some instances, the value of the network can decrease if there is an increase in network usage and your network is not built for it.
For example, if servers for Twitter can’t handle the traffic because of increased usage, it will lead to downtime. This phenomenon is called Network Congestion.
Another way the value can decrease is if the quality of the network decreases because of unwanted content. This is called Network Pollution.
Facebook was a tool used largely by college students but as the network grew in size, the type of users in the network changed. Now we find grandma’s commenting on posts on Facebook. This was unwanted content for college students and hence, the value decreased.
OTHER METRICS
If you’re running a business or product, there are a lot of other metrics that could define the value of your network such as competition, retention, cost, and so on.
Andreessen Horowitz has done an amazing job of compiling these metrics which can help you value your network as a product; I won’t reinvent the wheel.
KEY TAKEAWAYS
What did we learn about valuing a network which has Network Effects?
- Understand the type of network to understand its value. The derivation of the value of the network could be based on one of the three laws (Sarnoff, Metcalfe, Reed). It can also be a case where all 3 laws are applicable depending on the type of network
- Remember each node is different and has different properties (refer to Part 1 for more details)
- A network could have a negative value – understand where the network you’re evaluating stands
- Network Effects are valuable once a business/product/network reaches a critical mass. In some cases, the network can asymptote after reaching a threshold. Understand where the network stands while evaluating
- If a network has just started and faces the chicken-and-egg problem to evaluate the critical mass and which single-player product is the network targeting first
- Each network is different and could have a different Network Effects
These were some of the factors in determining the value of your network and how powerful are the Network Effects on your network. That’s it for PART 2!
In the next parts, we will cover types of Network Effects and it’s real-life application
- WHAT ARE NETWORK EFFECTS AND WHY ARE THEY IMPORTANT – PART 1
- HOW YOU VALUE A NETWORK AND THE LAWS OF NETWORK – PART 2
- TYPES OF NETWORKS EFFECTS AND VALUING FACEBOOK USING NETWORK EFFECTS – PART 3
- HOW TO BUILD, MAINTAIN & APPLICATIONS OF NETWORK EFFECTS IN DAILY LIFE – PART 4
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