高德(amap.com)：不止是“一张地图”

This case describes the development of Amap.com, a leading company in digital mapping area in China. It explains its transition from a B2B car navigation system provider for auto manufacturers to a B2C mobile Internet application provider. It also shows how Amap grows from a navigation service provider to a national platform in transportation. Amap has invested a great deal of manpower, material resources, and financial resources to build data production base. It adopts walking, vehicle, aviation and crowd sourcing to collect data. It also digitizes geographic locations to generate underlying big data on locations. The management of Amap believes that "the core and life of maps is data". Nevertheless, big data alone do not create a strong and reassuring barrier to continuous competition. In addition, due to fierce challenges from peers and without a clear profit model, Amap has been in a loss since its acquisition by Alibaba. Senior managers of Amap are confronted with the question of how to obtain value from location big data and look for new commercial scenarios while building sustainable barriers to competition. Amap has tried O2O business and used the map tool as a referral portal for offline stores, but this does not work. Later, the company has also opened data, technologies, and services to external developers so that they can invoke basic products such as maps, positioning and navigation. To better serve B-end users, Amap has launched a package of solutions to business scenarios including ride-hailing, freight, video game, e-commerce, etc. Amap's revenue mainly comes from service fees. Currently, senior management of Amap is exploring new commercial scenarios, such as smart transportation systems for government departments, smart scenic spots for local tourism management, aggregated ride-hailing model for different platforms, decision-making support for companies, etc. Should Amap choose these scenarios for breakthrough? What is the order of priority? How can Amap leverage its advantage in position big data around these new commercial scenarios to create value for clients or partners while finding an appropriate value creation model for itself? How can we analyze and answer these questions?