Understand the Network to Design for Growth and Defensibility
By: Simone Cicero
Tags: Growth Hacking, Marketplaces, Growth, Platform, Network Effect

The network properties (dependent on the type of relationship between supply and demand)

We have identified so far a set of seven key properties of a network (or better of the relationship underlying the network):

the level of supply commoditization/differentiation; the symmetry or asymmetry of the core relationship (likely a supply-demand relationship); the flexibility of location: Locally or globally bound; the single tenancy or multi-tenancy; the transaction frequency and lifetime; the value of the transaction; the monogamous or polygamous nature of the relationship.

“Network Types” an illustration: from the Growth Module of our certfication Bootcamp.

Level of supply commoditization/differentiation

This property describes how the perception of the value of the demand side of the spectrum perceives the supply side. Is every supplier different? Are all perceived as comparable? what value is attributed to the supplier?

A good explanation of this property comes with an archetype of the platform economy: ridesharing. It doesn’t matter how good a Uber driver is, she will be always perceived as a cost to be minimized, as the landscape putting in competition different alternatives for local mobility is largely price competitive. Furthermore, the very nature of the experience notoriously caps the value perceived by the user at a certain point: you don’t want your car to arrive in less than 3 minutes (this wouldn’t even let you time to say goodbye) and this effectively caps the “need” for suppliers to a certain extent. Much different is the situation in which, let’s say, a learning marketplace where every different provider of a certain learning experience can specialize in infinite niches, the object of the exchange is heavily praised as a key aspect of our lives, and therefore is much harder to imagine a commoditization process: supply, in this case, is heavily differentiated.

Symmetry or asymmetry of the core relationship (likely a supply-demand relationship)

Most of the networks have asymmetric weights of their supply and demand for a very simple reason: suppliers can normally serve many more customers than the other way around. This is clearly true in, again, a ride-hailing service or in a short distance food distribution platform (such as The Food Assembly) but may not be true, for example in marketplaces that connect non-professionals (e.g.: with second hand reselling marketplaces).

The flexibility of the location: is the network locally or globally bound

Another very complex aspect to understand in network properties is related to the degree to which the relationship between suppliers and demand is more or less constrained to a certain location. The flexibility related to that attachment limits or enables the growth of the network. One extreme of this spectrum is a network that needs both locally residing providers and consumers (à la Thumbtack, or Rover where the providers and the suppliers are both insisting on the same area for the long term), and the other extreme is when there’s no relationship whatsoever between the place of living and the consumption of services (think Upwork). Related to this property we often talk about a key concept, the so-called canonical unit (Dan Hockenmeier spoke about this in this seminal conversation at Venture Stories). The Canonical Unit is the unit where liquidity needs to be sought: as an example, in a network such as that of Thumbtack, according to Hockenmeier people seek for a particular profession — such as a plumber — at a particular location, such as New York. Overall, in networks where local implications are bigger, competitive advantage is harder to sustain and the chance that a more traditionally managed model can outperform a marketplace are higher. When — instead — there’s at least one player in the network that is global, the advantages may be harder to displace and the nature of the network may help the growth engine: think Airbnb; despite growth was hard to attain in a city, the “spillover” effect (travellers coming back home with the idea to start a room rental activity) helped the platform organically land on new cities.

Single tenancy or multi-tenancy

When participants from the supply and the demand side of the experience are able to juggle through multiple platforms, we call this phenomenon multi-tenancy. Normally platforms do not have the capacity to enforce “single-tenancy” if not by artificial constraints (e.g.: terms of services, regulation).

Transaction Frequency and Lifetime

It is defined as how often a participant goes through the key transaction/experience in the platform and how long this can last. Sustainable growth is hard to attain in contexts where transaction frequency is very low: this is also why in Real Estate platforms — for example such as Crexi or Zillow — the focus is often also on realtors and real estate agencies because they are transacting more often than actual buyers (one, or few, transactions in a lifetime). Particularly interesting on this topic is the podcast episode at Two-Sided featuring Crexi on “embracing the middlemen”.

Transaction Value (AOV)

Clearly, also the Average Order Value exchanged within the network has an impact on the network effects and defensibility and it’s important because it is connected with the frequency of transactions and nonetheless with the lifetime value of a user — that is an essential part of the unit economics. The sweet spot would clearly be that of a high frequency of transactions and a high AOV, like it may happen in some cases such as holiday booking, or space rental platforms like Spacebase. A low AOV must be compensated by really high-frequency transactions to make unit economics stand (we’ll see this later and in other posts). Paradoxically, very high AOV doesn’t ensure great defensibility for marketplaces and ink towards more managed approaches to the market, just because the size of the transaction makes the case for more efforts to be poured into making them happen, especially if the frequency is low and the network is local.

Monogamous vs Polygamous

Another obvious key aspect to keep in mind is the relationships between the two parties involved in the exchange: sometimes these relationships may require relevant time, effort or trust between the demand side and the supply side in order to create a relationship. In that case, the relationship tends to be long term and stable (monogamous): a good example would be the relationship between a caregiver and an elderly person, the relationship between a student and a teacher or the one between a cleaning person and a homeowner. Some others just need a quick check-in or even a “plug&play” interaction (polygamous) with less trust required.