基于波士顿矩阵优化医院微信公众号

Optimizing Hospital's Wechat Public Subscription Based on Boston Matrix

本研究整理了北京大学人民医院面向患者大众进行健康教育的微信公众号开通一年以来的推送数据,并利用波士顿矩阵进行分析。发现可以将推送的健康新闻按照所涉及的知识类型分为"高阅读高点赞"、"高阅读低点赞"、"低阅读高点赞"和"低阅读低点赞"四类,可以分别通过增加科室约稿、基于读者角度优化新闻内容、改良标题结构、融合知识领域等方式提升文章的阅读量和点赞量,进而提升医院微信公众号的影响力。

This article summarized the pushing data from the Wechat public subscription which was set up by Peking University People＇s Hospital to carry out health education on patient and the public, and analyzed the data with Boston matrix. It is found that the health news could be classified into ＂large page views and large praising quantity＂, ＂large page views but small praising quantity＂, ＂small page views and large praising quantity＂ and ＂small page views and small praising quantity＂. We suggest increasing manuscripts with the clinical departments, optimizing the news from readers＇ view, improving title structures and merging knowledge to increase the page views and the praising quantity so as to improve the influence of hospital＇s Wechat public subscription.