Connective Tissue or T1: The first part of creating a two-sided network is building the connective tissue that brings both sides together.
In Uber’s case that is building the application for Apple’s and Android’s app stores. From the definitional post, a network should treat both the providers and users as customers. Each industry will have different attributes to focus on and those attributes will change as the network matures. Accordingly, the first iteration should be highly focused and completely centered around getting users and providers. To do that, you have to remove the friction around signing up and using it. Examples will help drive this point home:
Providers: Sign-up, payments, and use of the app are incredibly simple and allow individuals to become drivers near instantaneously. Certainly, much faster than interviewing for a comparable waged job.
User: The first iteration was a sign-up and then map with your location and availability of drivers nearby. It was simplistic and easy to understand.
Providers: Take a few pictures, fill out an “ad”, and boom you have listed your belongings for sale with far greater reach than a garage sale.
Users: It’s a straightforward marketplace website…
Before you complete T1 (it will never truly be completed as the network will evolve and be iterated) its helpful to think through what T2 will look like, as that will inform your decisions around T1.
T2 – First User OR Provider Adoption: In the definitional post there were a few questions that pertained to T2: How do you determine the friction/reward ratio? How much should a company subsidize and what does subsidize mean exactly?
For the first question, think through a user and provider’s use cases. (Additionally, when thinking through where the friction lies, adopt a mindset of one very resistant to change and work.) In the case of Uber:
Friction: Signing up for anything is a pain, how will I ultimately get paid, I’ll have to file taxes as a 1099 employee, how will my current employer react, will my car be insured for this, what kind of passengers will I be driving around, is this even legal, new company that doesn’t know what they are doing, etc.
Reward: monetary rewards (job replacement / augmentation level income), more autonomy, working/growing with a startup, other non-monetary based feelings.
Friction: Signing up for anything is a pain and you will have to trust someone you have never met (in a transaction that is foreign to you) and get into their personal car.
Reward: cheaper, more available, better vehicles, real-time updates, and nicer drivers
While friction and rewards are presented in aggregate, the reality is each individual has unique perspectives on what friction exists and what reward would be necessary to compensate them for that friction. Additionally, it changes over time. “Nicer drivers” isn’t necessarily a reward for a first-time user, they are more likely to focus on “availability” and “cheaper”.
During T2, the point is to develop a view on who has the greatest reward to friction ratio. In Uber’s case, it is clearly drivers. From the above, Drivers have more friction, but their reward is much higher. For a Provider, Uber could become a new job, provide a livelihood. At the end of the day, the max benefit a User will have is saving a few dollars and an increase in convenience.
T3: The Other side of the Network
T2 and T3 have to be nearly simultaneous for a network to be built successfully. In Uber’s case, the Users would be the other side of the network. Users can be acquired through providing a dramatically reduced price or a service that is markedly better than what is currently available. For Uber, price was the main focus with the better service coming from being able to order an on-demand transportation method through your phone (which varied by geography, in cases where there are high concentrations of cabs this is less valuable to the User, so they needed to compete on price).
This is defined as when the user and provider network have reached optimal capacity. This capacity shifts and the network cycles back between adding users and providers, but, at T4, the ratio of drivers to users is optimal such that there is enough liquidity for users to get a service and for providers to make money. This optimal ratio is dependent on the population. Meaning, a subset of users may want to have a car (using Uber as an example) in 5 seconds or less, where another subset is ok waiting 5 minutes. Thus, market maturity is a very fluid concept.