For defensibility of an enterprise business model and avoiding the software morality play, the key in Fred’s view is gaining network effects in data contributed by the users of the service.
Data contributed by users is key. It is not sufficient to pull data from internal or public sources; instead each user must send back data. Usage then potentially builds an insurmountable lead in the network, since an entrant cannot catch up merely by replicating the service and pricing it cheaper.
So what are concrete examples of data network effects? Some examples of the data contributed by usage come from the USV platform:
- Work Market: Company customers put their entire “contingent labor” or freelance workforce onto to the platform, creating a supply platform accessible to all customers.
- Pollenware: Company customers bring their suppliers onto the platform in order to bid on accounts receivables.
- Return Path: Return Path provides email software to heavy email senders in exchange for the information as to who are good or bad senders
In a data network effects model, every new user makes the network more valuable through the contribution of some sort of data. Every new user makes it harder for all users to get off.