This is the final part in a primer on network effects.

• In Part 1, I listed the nfx’s 16 types of network effects. That’s a pretty useable list.
• In Part 2, I listed my checklist for network effects. That’s more comprehensive in terms of theory.

But there are a couple of network effects ideas floating around that I’m still trying to figure out.

Specifically, can you get network effects from things like belief? From tribal identity? What about from group psychology? Is mass delusion a network effect?

We start with the idea that network effects are about networks. These can be protocol networks, physical networks or people / company networks.

When we look at belief and identity, we are talking about people networks. Which look like this.

As people become connected, we can sometimes see improvements in the product or service based on increasing numbers of connected people.

Our key question is:

“How does the marginal user or activity increase the value and/or utility to current and potential users?”

But within this question, there are two versions.

• Increasing utility. This is all about functionality. Think communications and payments. You look at the number of connections and interactions.
• Increasing user value. This can be more complicated as value (especially for consumers) can include emotions, aspirations, entertainment and many other factors. We can see lots of human psychology.

But what about mass psychology? What about when groups of people interacting change each other based on their interactions? We can think of mild version of this, like joint events at concerts. We can also see extreme version like riots and mass delusion.

In this, I want to lay out 4 versions of network effects, based on such psychology. And they go from mild to extreme. A lot of this is from the nfx network effects list.

Shared “Expertise” Can Definitely Be a Network Effect. And a Switching Cost.

Nfx lists 16 network effects. On their list, #14 is Expertise. And they list Microsoft Excel as an example. They put it low on the list, so it’s weaker.

Here is how NFX describes an expertise network effect.

“Products that can develop “expertise” network effects are typically tools used by professionals to do their job — the instruments with which they ply their craft. As professionals become more skilled in their jobs, they also level up their expertise in tools required to do their jobs. If the tools are sophisticated enough, the tools require particular expertise of their own.”

“Here are some examples of industries and products where you see strong expertise nfx:

• Accounting Software (QuickBooks)
• CRMs (Salesforce, Hubspot)
• Analytics (Google Analytics, MixPanel)
• Computer Languages (Python, React)
• Spreadsheets (Microsoft Excel)
• Architecture (Revit, Autocad)
• CMS platforms (WordPress)
• Design software (Adobe, Figma, Invision)
• Video editing (Adobe, Final Cut, Avid)
• Mechanical Engineering (SolidWorks, CAD, Avid)”

That is pretty good. And I agree with most of that.

However, I put this under standardization and interoperability network effects. If you standardize a profession and its commonly used skills, that plays out in several ways.

• If everyone uses the same tools (Adobe, QuickBooks), this saves costs and lets everyone interoperate much more efficiently. You can share files. You can talk a common language.
• If there is a standard skill list and career path, employers and contractors can more easily hire who they need. Employers can hire people based on specific skills. Employees can do training in certain skills in a progression.

It meets our definition of network effects.

“How does the marginal user or activity increase the value and/or utility to current and potential users?”

Expertise as a network effect plays out in the tools, the expertise, in employment and in workflows. It really is pretty significant. We can see this in lots of companies that create tools like Microsoft Word and Adobe. But we can also see it in LinkedIn and Upwork for hiring. And within training schools and companies.

However, training in advanced skills takes time. So I think there is also a switching cost. Both at the individual level and within companies. And within industries. When everyone uses HubSpot in a company, it takes time and effort to switch to another program. When everyone is coding in Java, it takes time and effort to learn another language.

Shared “Language” Is Another Clear Network Effect

Language is a type of expertise. It’s a skill. And there are big interaction benefits to speaking the same language. It’s why every country usually operates in one language. And why programmers all use certain languages. It just makes communication and other interactions much more efficient.

NFX lists language as #11 in their network effects. Although they sort of mix it in with branding and the use of certain names.

I also put this as a type of Standardization and Interoperability Network Effect. On a people network. Without a platform business model. Languages become more valuable the more then are used. And communication becomes cheaper and more efficient.

Here is their summary:

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Ok. Those two are clear examples of network effects in people networks. Now let’s get into the fuzzier areas.

“Tribal” Behavior Can Be a Network Effect. But It’s Usually “Share of the Consumer Mind” Plus Switching Costs.

Here’s some stuff on tribal network effects from nfx.

“Tribal network effects most often develop in alumni networks of schools, military units, fraternities and sororities, accelerators, languages, regions, and religions.”

“We suspect this was the very first network effect historically, as Homo sapiens evolved as a pack animal, trying to survive. The ones that built the best tribes survived to procreate, so we are all descendants of the best tribe builders. Those who weren’t good at building or joining tribes died off. Thus, our brains are wired to join tribes.”

I mostly agree with that. It is definitely a psychological pull to join a tribe. However, that is not the same thing as having a tangible benefit to having a larger tribe (which would be a network effect). I think most of the above description is for “share of the consumer mind”. Making a tribe part of your identity is a big deal. But that’s not a network effect.

nfx has other comments about the benefits of being in a tribe. Again, I think these are very good descriptions of tribal value (i.e., share of the consumer mind). But not a network effect. It doesn’t increase with additional members.

“In contrast to the in-group of the tribe, there is an out-group that the tribe is actively NOT. A different group, a rival, an enemy, a force to be fought.”

“A perception of higher-status attributes of members of the tribe, creating prestige and pride. Evidence or reasoning that members of the tribe are more committed, more “right”, more justified, smarter, stronger, etc.”

nfx does make one compelling argument that a shared tribe can be a network effect  – saying:

“Network members within the tribe are taught to be intentional about building the value of the tribe by:

1. adding value to other tribe members,
2. defending the tribe’s reputation,
3. receiving value from the tribe members, and
4. growing the tribe.”

“This intentional value creation and defense of a network is distinct from other types of network effects, where nodes largely contribute value and drive network effects unintentionally.”

Ok. that’s a good argument. They also argue that there is a threshold for joining a tribe. This increases its quality over time.

1. “Members of the tribe endure shared hardship or adversity, such as training for the marines, studying for tests in college, founding a company, or going through a boot camp of some kind.”
2. “Tribe network members overcome a barrier to get into the tribe. There must be a believable reason for your inclusion, and some demonstration of your worth or “fitness” for inclusion. There is often a period of worrying you won’t “get in.” This creates exclusivity and belonging in the minds of the tribe members, reinforcing the other five attributes.””

“As with other network effects, network size and network density also matter in the formation and strength of Tribal network effects. The larger the tribe, up to a point, the more valuable it becomes because you are more likely to encounter and form relationships with other nodes. College alumni networks, for example, often have clusters in many different cities and companies where alumni seek each other out. Tribal networks also have a higher density of relationships between nodes because self-identification between tribe members causes them to look for shared affinities and motivates them to altruistic behavior towards other nodes in the network.”

“That, in turn, leads to a higher proportion of shared connection between tribe members than in other types of networks, which incentivizes further relationship-formation and sets off a virtuous cycle. In a tribal network, people (often unconsciously) recognize that potential connections are more likely to materialize into actual connections, causing a self-fulfilling propensity to try harder to build in-tribe network connections. This creates a denser lattice of links between the nodes, driving network effects, and network value.”

Ok. That’s a compelling argument. I just don’t think it’s that common.

In business, tribe and identity can be very important phenomena. We talk a lot about community building as a retention strategy. If you can get people to identify with a group, they are really unlikely to leave. I consider tribal behavior mostly:

• Share of the consumer mind based on identity (us vs them)
• Retention strategy based on community content and activities
• A switching cost
• And sometimes (rarely) it can be a network effect.

This is the image I think of for this tribal behavior and network effects.

Here is my summary graphic.

Ok. On to the next one.

Shared “Belief” Can Be a Particularly Powerful Consumer Phenomenon and Network Effect.

I have recently been writing about how consumers behave when a product / service is more about psychology than functionality. I wrote about fan behavior. And gambling behavior. That is a different approach than looking at a consumer product from its utility and features (sneakers, water, etc.).

We can do the same with consumer behavior and network effects resulting from connected consumers. We can look at network effects in terms of the utility of the product (phones that call more people). But we can also look at it from the psychology dimension. Does something become more valuable as a service when more people believe in it?

Tribal was a mild version of this. Belief is a more powerful form.

The nfx list has “Belief” as a network effect. And under this category, they talk about currencies, ideologies and religions as network effects based on belief.

Here’s what nfx says (I added the bold):

“The belief network effect is something you can best see with gold, Bitcoin and religion. It’s a direct nfx.”

“Homo Sapiens are a pack animal. We want to be in the “in group” and be accepted by others. Sharing common beliefs is a critical part of that. If people believe in something, others are more likely to stick with it and believe in it, too.

As a result, there are big social consequences for not believing the things your friends believe, and perhaps worse consequences for ceasing to believe in what they believe. This is one factor that makes people stick with group thoughts, making them very resilient to contradictory information.”

That is interesting. Especially “group thoughts”. Which is a very different thing than “group identity”. 

Here’s how I view it in my mind. Compare this to the picture for tribal.

They continue:

“beliefs become more valuable to believers the more people believe.”

“Look at gold. Why is it valuable? You can’t eat it or sleep on it. It’s pretty, but lots of things are pretty. It has some industrial uses, but not that many. It’s valuable because — after we were done believing salt was valuable — people decided to believe gold was valuable instead. And for 5,000+ years, it has always stayed valuable. The past gives us confidence that everyone will continue to hold this belief in the future. That belief strengthens over time.”

“Ipso facto, gold is valuable because we believe it’s valuable…”

Note how similar that is to my discussion about fandom and collectibles. Old baseball cards are only valuable economically and psychological because other people value them. It is a cultural phenomenon. Baseball cards are valuable and tradable. Old refrigerators are not.

Nfx goes on:

“…The same is true of Bitcoin. The more people believe it’s valuable, the more valuable it gets for everyone. And we’re seeing that same “sand layering” with Bitcoin now. The more times its price crashes and then bounces back, the more people will believe it has value. And then when you layer some Ethereum “sand” on top of it, and the “sand” of the thousands of other cryptocurrencies in existence — all denominated in Bitcoin on the exchanges — the Bitcoin sand gets progressively more stable as a result of growing Belief nfx. What was once fluid and intangible transforms to something closer to rock.”

Below is their definition for belief network effects.

Here’s how I think about belief:

• Shared Belief (also called group thoughts) is mostly about share of the consumer mind. Shared beliefs can be very powerful. No doubt.
• Some shared beliefs can have network effects because belief creates a greater utility. The more that people believe in them, the more useful and functional. Like Bitcoin. This is the most predictable version because marginal utility can be measured.
• Some shared beliefs can greatly impact the perceived value of a product / service. Go to a religious or political gathering. You can see how more it becomes more powerful with more people sharing the belief.
• There is big retention in shared beliefs. It is a powerful form of switching costs. Much more than just tribal identity.

Here’s my image and graphic for this.

Shared Beliefs Can Tip into Mass Delusion. Which Can Be Powerful Consumer Phenomena and Network Effects.

I like the Joker as a villain. He’s a psychopath. And, in the comic books, he is always focused on manipulating populations. On starting riots. He’s trying to get normal people to do awful things. He’s basically in the mass psychosis business.

The recent Joker 2 movie (which I hear is awful), actually has a great name. Folie a deux. This is French for the “madness of two”. It’s a term for a shared psychosis or shared delusional disorder. It’s when a delusional belief is transmitted from one individual to another. It is also referred to as “induced delusional disorder”. And it can go to “folie a trois” (of 3 people), “a quatre” (or 4 people) and so on.

Here’s how I view it.

I’ve been thinking a lot about what it means to have humans now connected to each other digitally. And how we are constantly influencing each other, in real-time. I initially was thinking about how this created a powerful control point for information. Which tech firms and governments are currently wrestling for control of.

But now I’m thinking about how digitally connected people can share beliefs. Even false ones. How information control can enable programming of people. And how this can create network effects, which is the most powerful version of this. And how groups with shared beliefs can be delusional (think the Joker).

Food for thought.

That’s it for this topic. Network effects is an important subject. And it’s one I’m increasingly looking at from psychology, instead of utility.

Cheers, Jeff

• Nfx’s 16 Types of Network Effects (1 of 3) (Tech Strategy)
• My Checklist for Assessing Network Effects (2 of 3) (Tech Strategy)

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I write, speak and consult about how to win (and not lose) in digital strategy and transformation.

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