23 Nov 2020

How to Monetize Data Networks: Focus on Acquisition and Usage

Data Network Monetization


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 a direct impact on the way they monetize. For one, it automatically invalidates one of the monetization models used by other networks — interaction taxes (or commissions). Since there are no direct interactions between participants, they cannot be taxed. So data networks are left with five of the six monetization models I have previously listed

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9 Nov 2020

The Marketplace Monetization Map: Complexity and Asymmetry


Marketplace Monetization

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 are constraints involved. Depending on these constraints, marketplaces can choose between five out of the six possible monetization models

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19 Oct 2020

The Network Monetization Map: Aligning Incentives with Revenue

Network Monetization

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 monetize than traditional business models. This is because they primarily create value by connecting participants, not just by developing a standalone product. So in order for value creation to continue, their monetization model needs to be aligned with the incentives of all participants. As a result, the relationship between these participants exerts an outsized influence on the choice of monetization model. 

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5 Oct 2020

Platform Liquidity: Why Economic Incentives Matter

Platform Economic Incentives

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 with existing adoption. So, as we saw with SaaS-enabled marketplaces, it is natural to assume that platforms can leverage these existing customers to attract a critical mass of developers. Wouldn’t they have liquidity right from the get-go? Not always.

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21 Sept 2020

Data Networks and Liquidity: How to Avoid Dead Ends

Data Network Liquidity

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 each other — they just interact with a product that is augmented by crowdsourced data. This results in even more trade-offs that add to the complications of building a data network.

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7 Sept 2020

The Network Liquidity Map: Why Time Matters

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 this principle in all situations can be dangerous. Time-delayed behavior can sometimes be a requirement to gain critical mass, in particular for interaction networks — ones that connect specific users to enable interactions, e.g. social networks.

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24 Aug 2020

How to Disrupt Network Effects

Disrupt Network Effects

Network effects are among the most powerful economic forces in technology and have created trillions in value. The reason for this value creation is not just compounding, but also the defensibility created by network effects. These advantages have allowed network effect-based startups to disrupt incumbent SaaS players. But there are also immensely valuable incumbents who are built on network effects themselves. Is there any way to disrupt them? 

10 Aug 2020

When is a Marketplace No Longer a Marketplace?


Marketplaces in name only

The wave of unicorns we have seen over the past decade has been partially populated by what VCs and founders call “managed marketplaces”. This term has been used to describe a dizzying range of business models including consignments, verified matchmakers, iBuyers, asset rental services, etc. So, much like the term “platform”, the term “managed marketplace” has been used so broadly that it has lost all meaning. Let’s take a deeper look at what managed marketplaces really are and what happens when they can no longer be categorized in that bucket.

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27 Jul 2020

How Network Structure Shapes Defensibility and Scalability

Network Structure

Most attempts at understanding network businesses revolve around studying user engagement. This is measured by a range of metrics including frequency of use, time spent, number of payments, etc. However, this tends to gloss over a very important fact — engagement is an effect, not a cause. If we want to truly understand what makes network startups work, we need to begin with the underlying cause of their engagement pattern — their network structure.

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13 Jul 2020

Layering Network Effects: How to Multiply Unfair Advantages

Layering Network Effects

So far, I have discussed four different types of business models built on network effects — marketplaces, interaction networks, data networks, and platforms. Including the sub-categories I previously explained, this covers all discrete forms of software-based network effects. However, it is still not exhaustive because many startups fall under more than one of these categories. In fact, combining multiple forms of network effects, like Slack, Carta, and Poshmark have done, is one of the most effective ways to strengthen both defensibility and scalability.