Research On The Operation Mode Of Internet Medical Platform

Driven by multiple factors such as the Internet economy and the application of big data,the Internet medical industry has developed rapidly in recent years,with the development of online consultation,telemedicine,health management and other application scenarios.Influenced by the global COVID-19 epidemic in 2019,Internet medical platform enterprises are facing new opportunities and challenges.How to attract more users through efficient operation strategies is the key to the sustainable development of enterprises based on the Internet market.The first batch of Internet medical enterprises appeared in China around 2011.From 2014 to 2015,accompanied by the promotion of capital and policy guidance,the first peak of Internet medical development was achieved,and a wave of enterprises obtained high financing emerged.However,with the development of enterprises,continuous capital investment continues,but it is difficult to realize the large number of active doctors and patients on the platform,and capital withdrawal is under pressure.Internet enterprises begin to gradually change their business model and seek for the realization of traffic while actively changing their operation strategies.Based on the AARRR mode(user growth model),This paper explores and analyzes how China’s Internet medical platform adjusts its operation mode and analyzes the characteristics of the O2O operation mode of Internet medical platform through summarizing the commonalities of three types of different operating subjects.Among them,Ali Health,a head company in the Internet medical industry,is selected as the research object of case analysis.By users increase scale,using process and user feedback in three aspects analyze medical Internet platform user growth stage,the problem of,in turn,find out the inner reason of this a series of problems,mainly including the platform needs to improve the overall operational planning,lack of effective platform for marketing strategy,etc.,and puts forward realistic scenario optimization Suggestions.