Network Effects!
😻 "Network Effects (NFX) occur when a company’s product or service becomes more valuable as usage increases"
Found a cool post from @NFX about them and I'll aggregate the information here 😽
🧵👇 for all mapped NFX types and research source!
📝 The research was done by @NFX and can be found integrally in this link: nfx.com/post/network-e…
⚠️ DISCLAIMER on how to approach this map:
In this map we can see the NFXs are divided into:
🔵 Direct
Agents communicate directly with each other
🔴 2-Sided
Split into supply/demand groups
🟤 Data
When more data means more value
🟡 Tech
When tech performance impacts the number of users
🟠 Social
People relations
🔵 Physical
Examples: Roads, trains, electricity, sewage, natural gas, broadband internet
When spread they are really hard to replace. We can observe this since those tend to keep running even when offering substandard services.
🔵 Protocol
Examples: VHS, Ethernet, Fax, Bitcoin, Ethereum
Also really hard to replace when spread since it declares standard ways to deal with data and becomes embedded in all products that use it.
🔵 Personal Utility
Examples: WhatsApp, Telegram, Discord, Slack
Ties in personal identities with something like a username. Essential for professional and personal life and really hard to opt-out without getting isolated from social groups.
🔵 Personal
Examples: Facebook, Instagram, Twitter
These networks are strong but are not essential for the maintenance of your daily life. They also tie in identity with some type of username, and reputation is constantly at stake. Enables people to create a public image.
🔵 Market
Examples: HoneyBook, DotLoop
Market Networks start by enhancing a network of professionals that already exists offline. They avoid becoming 2-sided (🔴) NFX, retain the direct communication between participants, and tries to amplify professional relations.
🔴 Marketplace
Examples: eBay, Etsy, Amazon Marketplace
The 2 sides are buyers and sellers.
The network is what provides the majority of the value, not the app or website itself. Products like eBay and Craigslist can afford to look essentially unchanged after 16 years.
🔴 Platform
Examples: Windows, Mac, Linux, Nintendo
The 2 sides are developers and users
In this case, the platform features provide great value. For example, users know Nintendo switch has the poorest hardware of the consoles, but the game library around it makes up for it
🔴 Asymptotic Marketplace
Example: Uber, Lyft
Asymptotic comes from "limit". They have a limit for how much they can grow and stale in value provided. They are more vulnerable to competition since new players can reach critical mass fast while old players deals with limits
🟤 Data
Examples: Google, IMDB, Amazon
This nfx happens when the increased data usage leads more useful data production. Waze is a good example of app with increased usage that benefits users and developers. Some data nfx can be asymptotic.
🟡 Tech
Examples: BitTorrent, VPN
"Networks with tech performance nfx become better (faster, cheaper, or easier to use) the bigger they get. As more nodes (devices) join the network, the performance of the whole improves."
(paragraph replicated from source)
🟠 Language
Examples: Catchy company names that stick as pioneers to an action: Google it, Bitcoin, Call an Uber, Xerox
People use language to communicate, if your product happens to have a name people start to use to describe an action you might ride this NFX to the moon!
🟠 Belief
Examples: Currency, Religion, Ideology
Gold is valuable because we believe it’s valuable, the same goes for Bitcoin. Beliefs become more valuable to believers the more people believe, the cryptocurrencies movement grows every time someone onboard in a blockchain
🟠 Bandwagon
Example: FOMO-inducing tactics, Linkedin, GitHub
This effect forms when people join a product/service for the pure fear of being left out and losing the hype-train. Competition often looks in disbelief since it's normally not based on rational product choices.
🐈 I hope you enjoyed the ride!!
You can certainly dig really deep into each NFX, if you identified one you want to learn more you can now dive in!
Knowing about these models will certainly help me think about trade-offs for distribution of the projects I build 😻 thanks @NFX!!
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