Website Statistics System Content Analysis

Copyright statement: original works can be reproduced. During reprinting, you must mark the original publication, author information, and this statement in hyperlink form. Otherwise, legal liability will be held. Http://blog.csdn.net/mayongzhan-ma yongzhan, myz, mayongzhan

For more information about how to obtain the page of JS, see my other article. about adsence. to 51. LA is a model (because it is simple and intuitive, I also have an account. of course, you can also use Gg Analysis) Website OverviewAddress: blog.csdn.net/mayongzhan's on-line number of people: person-on-line technology: On-line statistics (of course, access starts to end) TrafficTotal amount: 981492 IP 2431098 PV today's traffic: 300 IP 600 PV yesterday's traffic: 600 IP 1200 PV the technology here is: access records (one visit is counted as an IP address and PV, duplicate IP addresses only record PV) RecordingAlexa: 100 Google PR: 7google indexed: 1400baidu indexed: 2500yahoo indexed: 1000 obtained through the APIs of these websites AnalysisBy time period analysis by day segment analysis by week month analysis other analyses are the same as the traffic analysis. It is also recorded based on a record and then analyzed Access detailsToday's details yesterday's details this Monday details this month's details visit search engine keyword lailu System Browser language Time Zone screen color screen size IP header area Alexa regular visitor browse deep entry page browse here much of the data is also needed the most resource-consuming part of the entire system should obtain the above content like the content here In general, it is to get the visitor's IP, Time, Access portal, Access address, Region, Time zone, System, Browser, Search engine ( This is determined by the portal)Of course, when data is available, it is the focus of statistics. I will discuss it later.