Web log analysis software

Short description: Software for analyzing log files of web servers

Web log analysis software (also called a web log analyzer) is a kind of web analytics software that parses a server log file from a web server, and based on the values contained in the log file, derives indicators about when, how, and by whom a web server is visited.[1] Reports are usually generated immediately, but data extracted from the log files can alternatively be stored in a database, allowing various reports to be generated on demand.

Features supported by log analysis packages may include "hit filters", which use pattern matching to examine selected log data.[2]

## Common indicators

* Number of visits and number of unique visitors
* Visit duration and last visits
* Authenticated users, and last authenticated visits
* Days of week and rush hours
* Domains/countries of host's visitors.
* Hosts list
* Number of page views
* Most viewed, entry, and exit pages
* File types
* OS used
* Browsers used
* Robots used
* HTTP referrer
* Search engines, key phrases and keywords used to find the analyzed web site
* HTTP errors
* Some of the log analyzers also report on who is on the site, conversion tracking, visit time and page navigation.

## See also

* List of web analytics software

## References

1. ↑ Baez, Sarhad (2022). "Design a Web Analytics Software Tool in Order to Identify and Recognize the Behavior of Users That Visit Website". https://d1wqtxts1xzle7.cloudfront.net/110153943/506_Article_Text_5698_2_10_20221103_5_-libre.pdf?1704665877=&response-content-disposition=inline;+filename=Design_a_Web_Analytics_Software_Tool_in.pdf&Expires=1783528209&Signature=JnsT1Z1iT1ylQJrGMq0UThSAGmHJ~nQNP8FdqgQmoAumYQEABlWZ55q2OaSv5vB8PCBYEYVS8XLJ079a9-bvDJa5cutGxhZ3PNz63gvvvANrnUClH4XSwIK55-L0ZA6TBCd7NKKzdYpltzXtqLrtJ9XdMZJ7zXuz3cfrfXBB674CfypDpBpqCQLkkpXi7IdZZrzm9oKikqp6qH-c-~aIKoxbkPsC5icrWyfP62IqWGrEzP6XDvuLoBOzk3oYARJwreyHnL~W2J4J5z7X9wvYr5txSj4zegno8lh88lnuIQr8zkYn2A3POiZdQDz1PJZtD3s0US0AfrVZY-ew4tWZpw__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA.
2. ↑ Kipf, Andreas (January 13, 2020). "Advancing Analytical Database Systems". https://mediatum.ub.tum.de/doc/1525981/1525981.pdf.

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