Design And Implementation Of Fund Ranking APP Based On Event Tracking Technology

The iterative speed of the original App application is getting faster and faster,and it is facing the problem of continuous expansion of demand and continuous expansion of functions: On the one hand,how to accurately analyze the competitiveness of the products in the App and grasp the user’s preferences has become a major problem;On the other hand,how to accurately evaluate the effectiveness of this development in rapid iterative development has become another issue that major companies need to face.Based on the rapid development of a company’s online fund sales business and the continuous enhancement of investment and research capabilities,this paper revises and optimizes the fund ranking business.In the revised version of the fund ranking APP,React is used for front-end component development,Chair framework for efficient middle-level development,B/S architecture to achieve a new version of the ranking list with high concurrency,high robustness and good compatibility,a series of functions such as sorting,screening and viewing of fund rankings have been realized,and a set of reusable filter components,plug-ins and manual event tracking toolkits common to the business have been developed.For the two major issues of user behavior analysis and revision effect evaluation,front-end event tracking technology and ABTest technology are used respectively.The former uses customized Java Script scripts to collect user behavior data;the latter uses experimental configuration parameters to divide the user groups of the new and old versions.After the experiment has been conducted for a period of time,the collected data is used to analyze the significance of each indicator to obtain the effect of the revision,and to analyze the usage of the added functions to obtain the user’s product preference.Based on the completion of the ranking revision development,this article adds user behavior monitoring and experimental comparison between the new and old versions.Through the information reported by the event tracking and the results of the ABTest experiment,it is concluded that the new features in this iteration have a higher utilization rate,and the user conversion rate and transaction amount have increased,and the user’s product preference type has been analyzed.