Path Analysis: A Good Use of Time?

Is doing Path Analysis a good use of time? In my humble opinion the answer is a rather emphatic no, except for one exception (which I'll discuss below). Almost always Path Analysis tends to be a sub optimal use of our time, resources and any money that is expended on buying tools that do 'great' Path Analysis.

Kaushik, Avinash. Occam's Razor (2006). Articles>Web Design>User Centered Design>Log Analysis

References Available Upon Request  

Find out where your visitors come from.

Fleishman, Glenn. Adobe Magazine (1999). Design>Web Design>Audience Analysis>Log Analysis

Server Log Analysis

Server log files are records of Web server activity (or server activity for any digital medium). They provide details about file requests to a server and the server response to those requests. Collecting and analyzing these files can provide: information about who is coming to your Web site; what information they're requesting; their navigation and behavior. What types of data you collect on your server depends on how it has been set up and defined by the technical staff.

Usability.gov (1998). Articles>Web Design>Usability>Log Analysis

Standard Metrics Revisited: Bounce Rate

Bounce rate is a beautiful way to measure the quality of traffic coming to your website. It is almost instantly accessible in any web analytics tool. It is easy to understand, hard to misunderstand and can be applied to any of your efforts.

Kaushik, Avinash. Occam's Razor (2007). Design>Web Design>User Centered Design>Log Analysis

Statistics for Traffic Referred by Search Engines and Navigation Directories to Useit

The following table shows the number of visits that have been recorded in the Useit server logs as coming from search engines and directory services (so-called 'portals') in a one-month period (March) in each of the years from 1998 through 2003.

Nielsen, Jakob. Alertbox (2003). Design>Web Design>Statistics>Log Analysis

Stop Obsessing About Conversion Rate

Perhaps there is no other single metric that is abused as much as conversion rate, none that is perhaps more detrimental to solving for a holistic customer experience on the website because of the company behavior it drives.

Kaushik, Avinash. Occam's Razor (2006). Articles>Web Design>User Centered Design>Log Analysis

Tracking the Growth of a Site

When analyzing numbers related to the growth of a website, I normally recommend looking at them on a logarithmic scale. The reason is that the Web and the Internet both experience exponential growth. Therefore, Web statistics are better analyzed in terms of growth rates than in terms of linear growth.

Nielsen, Jakob. Alertbox (1998). Articles>Web Design>Usability>Log Analysis

Tracking Your Users in the Access Logs

Most server log analysis applications on the market simply present usage information grouped by date with sub-groupings like daily averages and top downloads by file size. While this can be useful, it doesn't begin to touch the range of information available to be gleaned from the logs with a little creativity.

Hoyt, Philip. evolt (2005). Articles>Web Design>Audience Analysis>Log Analysis

Traffic Log Patterns

The relative popularity of a site's pages, the number of visitors referred by other sites, and the traffic from search queries continue to follow a Zipf distribution.

Nielsen, Jakob. Alertbox (2006). Articles>Web Design>Assessment>Log Analysis

Trinity: A Mindset and Strategic Approach

The goal of the Trinity mindset is to power the generation of actionable insights. Its goal is not to do reporting. Its goal is not to figure out how to spam decision makers with data. Actionable Insights and Metrics are the uber-goal simply because they drive strategic differentiation and a sustainable competitive advantage.

Kaushik, Avinash. Occam's Razor (2006). Articles>Web Design>User Centered Design>Log Analysis

Unsuspected Correlations Are Sweet!

Tracking web usage with a one dimensional mindset (or in a silo) means that you will end up missing so much of the picture.

Kaushik, Avinash. Occam's Razor (2006). Articles>Web Design>Audience Analysis>Log Analysis

Using Your Web Stats for SEO: Search Marketing Analysis from Web Stats

Last week, Jennifer covered the basics of web statistics and what they should mean for you. Now that you have a fairly good handle on what all these statistics mean, how do you put them to work for you? These concerns are answered in this article.

Sullivan Cassidy, Jennifer. SEOchat (2005). Articles>Web Design>Audience Analysis>Log Analysis

Visits, Visitors, and Hits  

What do people mean when they talk about 'hits,' 'visits,' and 'visitors?'

Fleishman, Glenn. Adobe Magazine (1996). Design>Web Design>Audience Analysis>Log Analysis

Web Analytics, Demystified

Measurement is a crucial part of a successful search marketing campaign, but understanding and using web analytics tools can be daunting. A new book demystifies the process, showing you how to implement your own effective measurement strategies.

Sherman, Chris. Search Engine Watch (2005). Articles>Web Design>Assessment>Log Analysis

Web Analytics: Insights From the Front Line, Part 1

In many companies Web and Web analytics have been a silo that someone else is taking care of. Web sites are becoming the most important customer touch point and the most important revenue generator, even for businesses that are not first of mind.

Mazon, Neil. ClickZ (2008). Articles>Web Design>User Centered Design>Log Analysis

Web Analytics: Insights From the Front Line, Part 2

2008 will see a more serious attempt to get Web analytics to become a part of business analytics. We're still a silo in most companies (data and people). We'll see more collaboration and innovation in helping Web data become a core part of the company data to truly give end-to-end visibility (and maybe the holy grail of multichannel analytics/impact).

Mason, Neil. ClickZ (2008). Articles>Web Design>Audience Analysis>Log Analysis

Web Analytics: The Voice of Users in Information Architecture Projects

How to use web analytics in designing web information architecture.

Hurol Inan (2005). Articles>Web Design>User Centered Design>Log Analysis

Web Measurement Strategies for Small Businesses

Tools to build an effective Web measurement strategy on a tight budget.

Mason, Neil. ClickZ (2007). Articles>Web Design>Research>Log Analysis

Web Site Stats: A Look Behind The Numbers

In the dot.com boom of the 1990s, an electronic goldrush began as companies flocked like new age prospectors seeking to plant their stake in this digital revolution that has today transformed the ways companies communicate and do business around the globe. Because the web is becoming a viable communications channel, it's important that communications professionals understand how the content they're putting up on a web site is delivering to users the kind of value that is realizing a return on their investment.

Gannon, Joseph P. Communication World Bulletin (2003). Articles>Web Design>Audience Analysis>Log Analysis

Web Statistics: The Truth is in There  

In this study, we assessed and restructured Web server log statistics to analyze our customers’ use of a large-scale Internet library. We formulated questions about how these users might be accessing and navigating the information, then developed our own tools to sort and gather relevant statistics from the log files. We discuss specific successful procedures as well as limitations of the methods. Some of our findings may result in further redesign of the Web site. We also identify areas of interest for further research.

Hood, Teresa L., Linda Jorgensen and Leo J. Smith. STC Proceedings (1998). Articles>Web Design>Audience Analysis>Log Analysis

Web Traffic Analytics and User Experience

As a specialist in the user, you gain knowledge through observation and direct questioning of individual users. Now, you can add to that insights gained from data pulled during their actions on the site. By looking at this information, you will get a fuller picture of user behavior, not in a lab, but in the true user environment.

Diamond, Fran. Boxes and Arrows (2003). Articles>Web Design>Statistics>Log Analysis

Webに関連する統計データの可視化：対数グラフと垂れ下がるテール

ウェブサイトへのアクセスログを線形グラフにするだけでは、データの大切な部分を見落とすことになりかねない。ときには、一歩進んだグラフ化にもやってみる価値があるものだ。

Nielsen, Jakob. U-Site (2006). (Japanese) Design>Web Design>Reports>Log Analysis

When Getting the Job Done Isn't Enough

Interface designers today are swirling within a blizzard of data. How many types of user data does your Web team collect?

Straub, Kathleen. Human Factors International (2006). Articles>Web Design>User Centered Design>Log Analysis

Site Navigation and Its Impact on the Content Viewed by the Virtual Scholar: A Deep Log Analysis    

is paper presents early findings of a unique analysis that related questionnaire data to site usage as recorded in the transaction log reports of ScienceDirect, for the same people. Its focus is the differences in the online behaviour of three types of navigational users: those accessing the site via a gateway (either via a reference hyperlink or subject search facility), those using the on site search facility and those employing menus. Towards this end 16,865 sessions were analysed and grouped by navigational entry and compared over three types of online behaviour: the viewing of articles in press (AIP), the number of different journals viewed in a session and the viewing of old material. A strong association was found between form of navigation and behavioural trait. Those using menus were more likely to view AIPs, while those using the search facility were more likely to view a greater number of different journals and were more likely to view older material. This supports a hypothesis proposed by Nicholas et al. (2006) that use of the online searching facility increases the visibility of material irrespective of journal and age and results in a greater use of older material and a more diverse journal use compared to other online and off-line information retrieval methods. Although research has been undertaken on the different strategies that users employ to navigate and find their way around a collection of content (e.g. a digital library), this we believe is the first time the effect of different navigational strategies on outcomes (for example, what is viewed) has been investigated.

Huntington, Paul, David Nicholas and Hamid R. Jamali. Journal of Information Science (2007). Articles>Web Design>Research>Log Analysis

Employing Log Metrics to Evaluate Search Behaviour and Success: Case Study BBC Search Engine    

This paper argues that metrics can be generated from search transactional web logs that can help evaluate search engine effectiveness. Search logs from the BBC website were analysed and metrics extracted. Two search metrics — the time lapse between searches and the number of searches in a session — were developed to see whether they could measure search success or satisfaction. In all, 4 million search statements by 900,000 users were evaluated. The BBC search engine possessed a number of functional attributes which sought to improve retrieval and these were subjected to the two metrics to help determine how successful they were in practice. There was some evidence to support the proposition that the search outcome metrics did indeed indicate the effectiveness of engine functionality. The authors argue that this result is significant in that the identification of search outcome metrics will pave the way for assessing the effectiveness of site specific search engines and a greater understanding of the effectiveness of search engine functionality.

Huntington, Paul, David Nicholas and Hamid R. Jamali. Journal of Information Science (2007). Articles>Web Design>Case Studies>Log Analysis