Data network effects are challenging to kickstart. In order to reach critical mass data networks like Waze need to carefully balance three factors—the rate of data decay, geographic constraints, and most importantly, the method of data acquisition.
Localized and real-time data networks like Waze tend to be liquidity challenged compared to cross-border and static data networks like Mapbox and UIPath. In addition, data networks that use passive crowdsourcing (e.g. Mapbox, UIPath) have an easier time reaching critical mass as compared to those that use active crowdsourcing (e.g. Waze).
Factors that strain liquidity should ideally be balanced out by those that ease it. This is why the vast majority of localized, real-time networks use passive crowdsourcing—Waze being the only exception. Read on to find out what makes Waze unique.