Designing metrics to evaluate the help center of Baidu cloud

Help centers are mainly designed to assist users with their product uses. The question as to how we measure the quality of a help center remains unanswered. As the first step of a joint research initiated by Peking University and Baidu Cloud that aims to develop a set of computable metrics to evaluate the quality of help centers, this experience report shares the results of data analysis on correlation between user behavioral data and technical documentation quality. The documents and data we use are a suite of cloud computing services provided by Baidu Cloud. The report begins with an introduction of the research goal; following reviews on the related work, it then lays out the design of the experiments with user data collected from Baidu Cloud. In our experiments, we categorize all documents into three groups and try to identify which metrics would affect documentation quality most. The result shows that the key index that contributes most to the model is PV/UV. At last, the report concludes with our current experimental efforts and future work in our plan.