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Network Effects Advisor & Investor, part of the Atomico Angel Program. Please direct all pitch decks and consulting requests to sameer@breadcrumb.vc.

Platforms face unique constraints that make them very sensitive to friction — this limits their monetization options to just 3 out of the 6 models used by other types of networks

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Platforms share many characteristics with marketplaces. They create value by connecting demand with supply — specifically, they connect users with app developers. So it is natural to assume that platforms have the same monetization options available to them as marketplaces do. …


Data networks can use five out of six possible monetization models, depending on the way they acquire data from users and the way that data is consumed

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Data networks are unique within the world of network effects. Most network types create value by allowing participants to interact with each other in some way. Data networks, however, do not connect participants directly. Instead, they crowdsource data from participants to improve the product for all of them. This has…


Marketplace monetization depends on two factors — Transaction complexity and the asymmetry in value to the demand and supply sides

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Like other types of startups built on network effects, marketplaces create value by connecting participants. Specifically, they connect demand with supply to enable transactions. This gives them an obvious way to monetize — take a cut of every transaction. However, this cannot be blindly applied to all marketplaces as there…


Interaction networks can use one or more of six possible monetization models — the choice between them depends on the structure of their network

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Startups succeed by uncovering a unique insight to create value for their users. This value creation is only sustainable if they can find a way to capture some of it themselves, i.e. monetize. This is just as true for startups built on network effects. However, they are more complex to…


Instagram is the new Facebook: Increasing UX complexity and a shift from social interactions to broadcasting makes Instagram vulnerable to a new wave of “unbundlers”

Facebook is among a handful of truly generational internet companies. Its journey to over $1T in value started with a simple idea: a social network based on actual identities and real-world social connections. …


There is a long list of metrics that attempt to measure network effects — putting them in context is the best way to identify the most relevant KPIs for each situation

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Metrics (or KPIs) are among the most well-researched topics within the startup ecosystem. This is just as true for those built on network effects. There are great resources available from A16Z, Point Nine Capital, and Speedinvest Pirates just to name a few. The goal of this post is not to…


There are two types of negative network effects in the software realm — networks can choose between five curation mechanisms to overcome them

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So far, I have explained various characteristics of network effects and their impact on scalability, defensibility, liquidity, and monetization. The implicit assumption here is that interactions between participants are positive for everyone involved. This is true most of the time, but not all of the time. Interactions between network participants…


The economic incentives of a platform determine its liquidity barriers — but they also create long-term trade-offs with the effectiveness of developer marketing programs

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Network effects can only take hold when a product has reached a minimum threshold or critical mass of users (also called liquidity) — this is true for marketplaces, interaction networks, and data networks. Platforms, on the other hand, are unique because they are always built on top of another product…


The rate of data decay, geographic constraints, and the method of data acquisition combine to define liquidity barriers for data networks — traits that strain liquidity should ideally be balanced by those that ease it

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Data network effects are a tricky beast and come with a difficult set of trade-offs. But these trade-offs only become meaningful after the data network has gained critical mass. The considerations for gaining critical mass on a data network are largely unique from other models because users don’t interact with…


Synchronous networks like Meerkat and Clubhouse are susceptible to liquidity challenges because they need users to be active at the same time — pivoting to emphasize asynchronous features is one way to overcome these challenges

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In the startup world, time is primarily viewed as a hurdle to be removed — everything needs to be instant and real-time. This is certainly valuable as a general principle, and it can even be critical to the defensibility of certain types of startups, i.e. data networks. However, blindly applying…

Sameer Singh

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