Portland Community College | Portland, Oregon

Course Number:
CIS 235W
Course Title:
Introduction to Web Analytics
Credit Hours:
Lecture Hours:
Lecture/Lab Hours:
Lab Hours:
Special Fee:

Course Description

Focuses on the collection and analysis of user web traffic data for the optimization and monetization of web sites. Covers the content and format of web server logs, and techniques for enriching this data using cookies, Javascript, and user registration. Illustrates how web content can be aggregated by type and used to create saleable inventory for generating ad revenue. Shows how web metrics can be used to determine web site stickiness, effective content on the site, and to identify and fix navigational bottlenecks that cause user churn. CAS 180 is recommended prior to taking this course. Prerequisites: CIS 122 or instructor permission. Audit available.

Intended Outcomes for the course

On completion of this course the student should be able to:

  • Configure the Apache web server to log user access and referral data.
  • Identify user paths through web sites from web server logs.
  • Generate web analytic reports using off-the-shelf tools and simple custom programs.
  • Modify web pages to enrich the information gathered.
  • Optimize navigation and identify potential revenue sources using web analytics.

Course Activities and Design

This course is presented with a combination of lectures and labs. Students will be expected to participate in hands-on exercises, led by the instructor, involving web server configuration, analysis of web server data, and modification of web pages.

Lectures and labs will be augmented with assigned readings, in-class exercises, and online content.

Outcome Assessment Strategies

Mastery of the learning outcomes in this course will be assessed using a variety of strategies, including:

  • Students will take tests or quizzes to assess knowledge-based outcomes.
  • Students will be required to write discussion board postings to assess their understanding of the material.
  • Students will be asked to complete a variety of hands-on labs to assess performance skills.

Course Content (Themes, Concepts, Issues and Skills)


  • What data is available for analysis
  • What types of analysis does this data support
  • How can this analysis be used to improve the user experience
  • How can this analysis be used to produce revenue


  • IP addresses
  • Domain Name Services
  • HyperText Transfer Protocol
  • Web server configuration
  • Web traffic
  • Web logs
  • Page tagging
  • Cookies
  • Hits
  • Page views
  • Visits, visitors, repeat visitors and unique visitors
  • Dwell time
  • Impressions
  • Advertising models
  • Demographics
  • Geographics
  • Referrers
  • Landing pages
  • User path analysis
  • On-site and off-site analytics
  • User lifecycle analytics
  • Retention and churn
  • Missing analytic input
  • Noisy analytic input
  • Web log analysis software
  • Web analytics services
  • Click-through and click-off rates


  • Enabling the capture of high-quality user data
  • Effective analysis of user data
  • Applying analysis to web site optimization
  • Identifying potential revenue sources


  • Configure a commonly-used web server to track user data
  • Use CGI, Javascript, and HTML to augment user traffic data
  • Run off-the-shelf web analytics software
  • Write simple log analysis programs to generate custom reports
  • Modify web site navigation to reduce bottlenecks and improve stickiness
  • Aggregate page views by content, and use demographic information to create saleable advertising inventory