A Review of Methodologies for Analyzing Websites

A Review of Methodologies for Analyzing Websites

Danielle Booth (Pennsylvania State University, USA)
Copyright: © 2009 |Pages: 22
DOI: 10.4018/978-1-59904-974-8.ch008
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This chapter is an overview of the process of Web analytics for Websites. It outlines how visitor information such as number of visitors and visit duration can be collected using log files and page tagging. This information is then combined to create meaningful key performance indicators that are tailored not only to the business goals of the company running the Website but also to the goals and content of the Website. Finally, this chapter presents several analytic tools and explains how to choose the right tool for the needs of the Website. The ultimate goal of this chapter is to provide methods for increasing revenue and customer satisfaction through careful analysis of visitor interaction with a Website.
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In order to understand the benefits of Website analysis, one must first understand metrics – the different kinds of available user information. Although the metrics may seem basic, once collected, they can be used to analyze Web traffic and improve a Website to better meet its overall goals. According to Panalysis (http://www.panalysis.com/), an Australian Web analytics company, these metrics generally fall into one of four categories: site usage, referrers (or how visitors arrived at your site), site content analysis, and quality assurance. Table 1 shows examples of types of metrics that might be found in these categories.

Table 1.
Metrics categories (Jacka, n.d.)
Site UsageReferrersSite Content AnalysisQuality Assurance
• Numbers of visitors and sessions
• How many people repeatedly visit the site
• Geographic information
• Search Engine Activity
• Which websites are sending visitors to your site
• The search terms people used to find your site
• How many people place bookmarks to the site
• Top entry pages
• Most popular pages
• Top pages for single page view sessions
• Top exit pages
• Top paths through the site
• Effectiveness of key content
• Broken pages or server errors
• Visitor response to errors

Key Terms in this Chapter

Log File: Log kept by a Web server of information about requests made to the Website including (but not limited to) visitor IP address, date and time of the request, request page, referrer, and information on the visitor’s Web browser and operating system.

Prospect Rate: KPI that measures the percentage of visitors who get to the point in a site where they can perform the target action (even if they do not actually complete it).

Alignment-Centric Performance Management: Method of defining a site’s business goals by choosing only a few key performance indicators.

Web Analytics: The measurement of visitor behavior on a Website.

New Visitor: A user who is accessing a Website for the first time.

Customer Loyalty: KPI that measures the ratio of new to existing customers.

Internal Search: A metric that measures information on keywords and results pages viewed using a search engine embedded in the Website.

Unique Visit: One visit to a Website (regardless of if the user has previously visited the site); an alternative to unique visitors.

Stickiness: KPI that measures how many people arrive at a homepage and proceed to traverse the rest of the site.

Visitor Path: A metric that measures the route a visitor uses to navigate through the Website.

Visit Value: KPI that measures the total number of visits to total revenue.

Depth of Visit: KPI that measures the ratio between page views and visitors.

Search Engine Referrals: KPI that measures the ratio of referrals to a site from specific search engines compared to the industry average.

Top Pages: A metric that measures the pages in a Website that receive the most traffic.

Unique Visitor: A specific user who accesses a Website.

Support/Self Service Website: A type of Website that focuses on helping users find specialized answers for their particular problems.

Returning Visitor: KPI that measures the ratio of unique visitors to total visits.

Average Time on Site (ATOS): See visit length.

Key performance indicator (KPI): A combination of metrics tied to a business strategy.

Online Business Performance Management (OBPM): Method of defining a site’s business goals that emphasizes the integration of business tools and Web analytics to make better decisions quickly in an ever-changing online environment.

Content/Media Website: A type of Website focused on advertising.

Visit Length: A metric that measures total amount of time a visitor spends on the Website.

Checkout Conversion Rate: KPI that measures the percent of total visitors who begin the checkout process.

Cost Per Lead (CPL): KPI that measures the ratio of marketing expenses to total leads and shows how much it costs a company to generate a lead.

Single Access Ratio: KPI that measures the ratio of total single access pages (or pages where the visitor enters the site and exits immediately from the same page) to total entry pages.

Repeat Visitor: A user who has been to a Website before and is now returning.

Lead Generation Website: A type of Website that is used to obtain user contact information in order to inform them of a company’s new products and developments, and to gather data for market research.

Referrers and Keyword Analysis: A metric that measures which sites have directed traffic to the Website and which keywords visitors are using to find the Website.

Committed Visitor Index: KPI that measures the percentage of visitors that view more than one page or spend more than 1 minute on a site (these measurements should be adjusted according to site type).

Total Bounce Rate: KPI that measures the percentage of visitors who scan the site and then leave.

Traffic Concentration: KPI that measures the ratio of number of visitors to a certain area in a Website to total visitors.

Average Order Value: KPI that measures the total revenue to the total number of orders.

New Visitor Percentage: KPI that measures the ratio of new visitors to unique visitors.

Order Conversion Rate: KPI that measures the percent of total visitors who place an order on a Website.

Demographics and System Statistics: A metric that measures the physical location and information of the system used to access the Website.

Customer Satisfaction Metrics: KPI that measures how the users rate their experience on a site.

Abandonment Rate: KPI that measures the percentage of visitors who got to that point on the site but decided not to perform the target action.

Visitor Type: A metric that measures users who access a Website. Each user who visits the Website is a unique user. If it is a user’s first time to the Website, that visitor is a new visitor, and if it is not the user’s first time, that visitor is a repeat visitor.

Log File Analysis: Method of gathering metrics that uses information gathered from a log file to gather Website statistics.

Conversion Rate: KPI that measures the percentage of total visitors to a Website that perform a specific action.

Metrics: Statistical data collected from a Website such as number of unique visitors, most popular pages, etc.

Page Depth: KPI that measures the ratio of page views for a specific page and the number of unique visitors to that page.

Page Tagging: Method of gathering metrics that uses an invisible image to detect when a page has been successfully loaded and then uses JavaScript to send information about the page and the visitor back to a remote server.

Commerce Website: A type of Website where the goal is to get visitors to purchase goods or services directly from the site.

Complete Chapter List

Search this Book:
Table of Contents
Bernard J. Jansen, Amanda Spink, Isak Taksa
Chapter 1
Bernard J. Jansen, Isak Taksa, Amanda Spink
This chapter outlines and discusses theoretical and methodological foundations for transaction log analysis. We first address the fundamentals of... Sample PDF
Research and Methodological Foundations of Transaction Log Analysis
Chapter 2
W. David Penniman
This historical review of the birth and evolution of transaction log analysis applied to information retrieval systems provides two perspectives.... Sample PDF
Historic Perspective of Log Analysis
Chapter 3
Lee Rainie, Bernard J. Jansen
Every research methodology for data collection has both strengths and limitations, and this is certainly true for transaction log analysis.... Sample PDF
Surveys as a Complementary Method for Web Log Analysis
Chapter 4
Sam Ladner
This chapter aims to improve the rigor and legitimacy of Web-traffic measurement as a social research method. I compare two dominant forms of... Sample PDF
Watching the Web: An Ontological and Epistemological Critique of Web-Traffic Measurement
Chapter 5
Kirstie Hawkey
This chapter examines two aspects of privacy concerns that must be considered when conducting studies that include the collection of Web logging... Sample PDF
Privacy Concerns for Web Logging Data
Chapter 6
Bernard J. Jansen
Exploiting the data stored in search logs of Web search engines, Intranets, and Websites can provide important insights into understanding the... Sample PDF
The Methodology of Search Log Analysis
Chapter 7
Anthony Ferrini, Jakki J. Mohr
As the Web’s popularity continues to grow and as new uses of the Web are developed, the importance of measuring the performance of a given Website... Sample PDF
Uses, Limitations, and Trends in Web Analytics
Chapter 8
Danielle Booth
This chapter is an overview of the process of Web analytics for Websites. It outlines how visitor information such as number of visitors and visit... Sample PDF
A Review of Methodologies for Analyzing Websites
Chapter 9
Gi Woong Yun
This chapter discusses validity of units of analysis of Web log data. First, Web log units are compared to the unit of analysis of television to... Sample PDF
The Unit of Analysis and the Validity of Web Log Data
Chapter 10
Kirstie Hawkey, Melanie Kellar
This chapter presents recommendations for reporting context in studies of Web usage including Web browsing behavior. These recommendations consist... Sample PDF
Recommendations for Reporting Web Usage Studies
Chapter 11
Seda Ozmutlu, Huseyin C. Ozmutlu, Amanda Spink
This chapter summarizes the progress of search engine user behavior analysis from search engine transaction log analysis to estimation of user... Sample PDF
From Analysis to Estimation of User Behavior
Chapter 12
Gheorghe Muresan
In this chapter, we describe and discuss a methodological framework that integrates analysis of interaction logs with the conceptual design of the... Sample PDF
An Integrated Approach to Interaction Design and Log Analysis
Chapter 13
Brian Detlor, Maureen Hupfer, Umar Ruhi
This chapter provides various tips for practitioners and researchers who wish to track end-user Web information seeking behavior. These tips are... Sample PDF
Tips for Tracking Web Information Seeking Behavior
Chapter 14
Sandro José Rigo
Adaptive Hypermedia is an effective approach to automatic personalization that overcomes the difficulties and deficiencies of traditional Web... Sample PDF
Identifying Users Stereotypes for Dynamic Web Pages Customization
Chapter 15
Brian K. Smith, Priya Sharma, Kyu Yon Lim, Goknur Kaplan Akilli, KyoungNa Kim, Toru Fujimoto
Computers and networking technologies have led to increases in the development and sustenance of online communities, and much research has focused... Sample PDF
Finding Meaning in Online, Very-Large Scale Conversations
Chapter 16
Isak Taksa, Sarah Zelikovitz, Amanda Spink
Search query classification is a necessary step for a number of information retrieval tasks. This chapter presents an approach to non-hierarchical... Sample PDF
Machine Learning Approach to Search Query Classification
Chapter 17
Seda Ozmutlu, Huseyin C. Ozmutlu, Amanda Spink
This chapter emphasizes topic analysis and identification of search engine user queries. Topic analysis and identification of queries is an... Sample PDF
Topic Analysis and Identification of Queries
Chapter 18
Elmer V. Bernstam, Jorge R. Herskovic, William R. Hersh
Clinicians, researchers and members of the general public are increasingly using information technology to cope with the explosion in biomedical... Sample PDF
Query Log Analysis in Biomedicine
Chapter 19
Michael Chau, Yan Lu, Xiao Fang, Christopher C. Yang
More non-English contents are now available on the World Wide Web and the number of non-English users on the Web is increasing. While it is... Sample PDF
Processing and Analysis of Search Query Logs in Chinese
Chapter 20
Udo Kruschwitz, Nick Webb, Richard Sutcliffe
The theme of this chapter is the improvement of Information Retrieval and Question Answering systems by the analysis of query logs. Two case studies... Sample PDF
Query Log Analysis for Adaptive Dialogue-Driven Search
Chapter 21
Mimi Zhang
In this chapter, we present the action-object pair approach as a conceptual framework for conducting transaction log analysis. We argue that there... Sample PDF
Using Action-Object Pairs as a Conceptual Framework for Transaction Log Analysis
Chapter 22
Paul DiPerna
This chapter proposes a new theoretical construct for evaluating Websites that facilitate online social networks. The suggested model considers... Sample PDF
Analysis and Evaluation of the Connector Website
Chapter 23
Marie-Francine Moens
This chapter introduces information extraction from blog texts. It argues that the classical techniques for information extraction that are commonly... Sample PDF
Information Extraction from Blogs
Chapter 24
Adriana Andrade Braga
This chapter explores the possibilities and limitations of nethnography, an ethnographic approach applied to the study of online interactions... Sample PDF
Nethnography: A Naturalistic Approach Towards Online Interaction
Chapter 25
Isak Taksa, Amanda Spink, Bernard J. Jansen
Web log analysis is an innovative and unique field constantly formed and changed by the convergence of various emerging Web technologies. Due to its... Sample PDF
Web Log Analysis: Diversity of Research Methodologies
About the Contributors