摘要
基于所采集的某视频网站用户访问行为数据,重点从浏览量和访问次数等两个引流指标以及转化率、跳出率和视频类型喜好等三个粘性指标进行了深入分析挖掘。发现了隐藏在数据背后的用户访问行为规律,包括浏览量变化的影响因素,用户访问网站的时间规律,转化率与等待时间的相关关系,对视频网站的兴趣程度以及对不同视频类型的偏好等。根据所获取的用户访问习惯,提出了网站改进的相关建议以吸引并留住更多用户,改善其使用体验,促进视频网站的快速发展。
Based on the acquisition of a video site user access behavior data, according to diversion indicators including the page view and visits and sticky indicators including conversion rate, bounce rate and video type preferences data analysis and mining are carried out in-depth. User behavior patterns of video website are found behind the data. The patterns include the influencing factors of the page view, the time of the user's visit to the website, the relationship between conversion rate and waiting time, the degree of user's interest in the video site, and the preference for different video types. Based on the user's access habits, suggestions are made to improve the website to attract and retain more users. So this could improve the experience of user and promote the rapid development of video sites.
出处
《电脑知识与技术（过刊）》
2017年第4X期187-190,共4页
Computer Knowledge and Technology
关键词
数据分析与挖掘
在线行为分析
引流指标
粘性指标
网站优化
data analysis and mining
online behavior analysis
diversion indicator
sticky indicator
website optimization
