A directory of resources inthe field of technical communication.

Log Analysis

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1.
#37250

The 10/90 Rule for Magnificent Web Analytics Success

For every $100 you invest in web analytics, you should spend $10 on tools and $90 on people with the brain power to think about the results from the tools.

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

2.
#31409

Alternative Ways to Measure the Effectiveness of Your Intranet Sites

When you measure hits on inter/intranet sites, you are measuring overall volume of usage -- how many times parts of your site have been opened. However, hits don't distinguish between the opening of an entire page or a single illustration. There are many additional ways of measuring usage. However, measuring the "userability" of a site is just as important in order to improve usage numbers. But the first place any communicator should start when measuring the effectiveness of electronic communications is to identify the original objectives for putting something on-line. Conducting some baseline audience research upfront to make sure your electronic solutions will be as effective as possible and then measuring afterward to see if the intended objectives are being met.

Sinickas, Angela D. Sinickas Communications (2000). Articles>Web Design>Intranets>Log Analysis

3.
#35112

Analytics According to Captain Kirk

By seeing all of the available data in one chart, associations, patterns and conclusions can be drawn simply by comparing the relationships as they are presented. This is something that I learned from Edward Tufte.

Bailey, Matt. Lyris (2008). Articles>Web Design>Technical Illustration>Log Analysis

4.
#29624

Analyzing Web-Based Help Usage Data to Improve Products   (PDF)

This paper describes how user assistance can streamline deliverables and improve product design by analyzing usage patterns from server-based content. We can then base decisions about how to improve deliverables on a thorough understanding of how customers use help content to find information and solve problems. This approach enables user assistance to add more value to both our companies and our customers by creating a three-way dialog between user assistance, the customer, and the product team. It also broadens the definition of assistance to include helping to design products that people can use without the need for instructions.

Raiken, Nancy. STC Proceedings (2005). Articles>Documentation>Audience Analysis>Log Analysis

5.
#32756

Analyzing Your Traffic   (PDF)

Discover your site’s findability triumphs and tragedies with traffic analysis systems.

Walter, Aarron. Building Findable Websites (2008). Articles>Web Design>Audience Analysis>Log Analysis

6.
#32988

Are You Using the Wrong Web Metrics?

Do you base success on measuring the volume of visitors and page impressions? Such measures may in fact reflect the failure--rather than the success--of your website.

McGovern, Gerry. New Thinking (2006). Articles>Web Design>Audience Analysis>Log Analysis

7.
#30868

The Awesome Power of Visualization 2: Death and Taxes 2007

Visuals that provide insights come from 1) a deep understanding of the goal / objectives 2) from thinking beyond what standard trend lines or stacked bar graphs can provide. Something non-normal to grab attention and yet communicate insights (sort of already contain recommendations and action items and not just data).

Kaushik, Avinash. Occam's Razor (2007). Articles>Graphic Design>Technical Illustration>Log Analysis

8.
#21434

Benutzertests durch Spurenverwertung   (PDF)

In most cases a technical writer cannot do any user tests. If you have access to the user log of a web server you can derive quite interesting facts like how often and how long a specific page was viewed and how the surfers navigated.

von Obert, Alexander. Techwriter.de (2003). (German) Design>Web Design>User Centered Design>Log Analysis

9.
#36965

Beyond the Screen: Visualizing Visits to a Website as an Experience in Physical Space   (peer-reviewed)   (members only)

This article describes an applied investigation into a concept of information visualization where data are not rendered as graphs, charts or diagrams on the screen but as a sensual experience beyond the screen in physical space. It introduces predecessors such as calm technologies and ambient displays among a number of poetic and applied examples from related backgrounds to establish the context and relevance for communication design and graphic design, and presents a current research undertaking in which the social activity of visiting a website is visualized in multiple sensorial modalities in real-time in the form of a kinetic and sensual display.

Hohl, Michael. Visual Communication (2009). Articles>Web Design>Visual Rhetoric>Log Analysis

10.
#21060

Bimodal Distributions Contain Clues

One of the most unusual aspects of data about people and nature is its uneven distribution. Explore the non-normal distribution called bimodal distribution.

Allen, Cliff. Allen.com (2001). Design>Web Design>Statistics>Log Analysis

11.
#38476

Bounce Rate Demystified

What is the industry standard for bounce rate? The simple and short answer is that there is no industry standard. I know you don’t want to hear that, but it is true. There is no industry standard. There are some ranges that I will share shortly but we can’t call them industry standards. There are a lot of factors that influence the bounce rate, so you really can’t compare bounce rates of one site (or page) to another.

Batra, Anil. Blogspot (2007). Articles>Web Design>Audience Analysis>Log Analysis

12.
#30226

Building a Data-Backed Persona

Incorporating the voice of the user into user experience design by using personas in the design process is no longer the latest and greatest new practice. Everyone is doing it these days, and with good reason. Using personas in the design process helps focus the design team's attention and efforts on the needs and challenges of realistic users, which in turn helps the team develop a more usable finished design. While completely imaginary personas will do, it seems only logical that personas based upon real user data will do better. Web analytics can provide a helpful starting point to generate data-backed personas; this article presents an informal 5-step process for building a 'persona of the people.' In practice, outcomes indicate that designing with any persona is better than with no personas, even if the personas used are entirely fictitious. Better yet, however, are personas that are based on real user data. Reports and case studies that support this approach typically offer examples incorporating data into personas from customer service call centers, user surveys and interviews. It's nice work if you can get it, but not all design projects have all (or even any!) of these rich and varied user data sources available. However, more and more sites are now collecting web analytic data using vendor solutions or free options such as Google Analytics. Web analytics provides a rich source of user data, unique among the forms of user data that are used to evaluate websites, in that it represents the users in their native habitat of use. Despite some drawbacks to using web analytics that are inherent to the technology and data collection methods, the information it provides can be very useful for informing design.

Wiggins, Andrea. Boxes and Arrows (2007). Articles>User Centered Design>Personas>Log Analysis

13.
#37113

Can RoboHelp Server Reports Really Improve Your Content?

We have two distinct sets of users; internal product consultants and end users. Prior to using RoboHelp Server we had little way of identifying who was looking at our documentation, when they were looking at it, or how often. That has now changed.

McAndrew, Colum. RoboColum(n), The (2010). Articles>Content Management>Documentation>Log Analysis

14.
#38681

Complete Beginner's Guide to Web Analytics and Measurement

Because each website appeals to its audience differently, the prudent user experience designer takes a measured approach when communicating, especially when they do so on behalf of their client. No matter what the vision and no matter how it’s executed, a design can always communicate more effectively.

Maier, Andrew. UX Booth (2010). Articles>Web Design>User Experience>Log Analysis

15.
#23810

Configure Web Logs in Apache

Traffic statistics have a huge impact on a Website's success, and Apache provides one of the most powerful and flexible logging features available today. Blane explains the nitty-gritty of configuring Apache Weblogs in this handy how-to.

Warrene, Blane. SitePoint (2004). Design>Web Design>Audience Analysis>Log Analysis

16.
#13794

Correlating Web-User Data

Everything served to a visitor -- from the first page through marketing, sales, and product fulfillment -- generates data about the customer. Web marketers can tap into this 'free' source of profile data for just the cost of converting existing data into a format that can be used by a data-analysis program.

Allen, Cliff. ClickZ (2001). Articles>Usability>Web Design>Log Analysis

17.
#21059

Correlating Web-User Data

The statistical term 'correlation' has found its way into popular business language. Often, though, no measurement of correlation has actually taken place. That's too bad. Because there's probably a correlation between measuring correlation and increasing revenue.

Allen, Cliff. Allen.com (2001). Design>Web Design>E Commerce>Log Analysis

18.
#30883

Data Mining and Predictive Analytics, Part 1

The cluster analysis process looks for groups of visitors in the data, where the people within the groups have something in common but the commonality is different from group to group.

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

19.
#30884

Data Mining and Predictive Analytics, Part 2

In part one of this series, I examined visitor segmentation, a data-mining technique. Now, let's look at how data mining can be used to understand important visitor behavior over time.

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

20.
#30866

Data Quality Sucks, Let's Just Get Over It

Data quality on the internet absolutely sucks. And there is nothing you can do about it. At least for now.

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

21.
#28049

Data Visualization of Web Stats: Logarithmic Charts and the Drooping Tail

Using a linear diagram to plot data from website traffic logs can lead you to overlook important conclusions. Sometimes advanced visualizations are worth the effort.

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

22.
#38760

Designing Better Experiences Through Data

The key to creating great service experiences lies with uncovering data and using it in meaningful contexts that have real benefits to users. Recent advances in wearable tech, location-based data and sensors are driving greater interest by consumers in personalized data experiences. Google Glass and the Nike FuelBand are pushing boundaries on what users can expect inside the services of tomorrow. For designers, however, data presents a very interesting challenge: How can we better understand the value of data and leverage it to make digital experiences more meaningful?

Napolitano, Jason. UX Magazine (2013). Articles>Web Design>User Experience>Log Analysis

23.
#27680

Don't Be a Slave to the Web Stats

Web stats are a tool and you need to know how to you that tool. Otherwise, you aren't accomplishing anything. At the very simplest level, your web stats should help you to figure out this overused business truism: 'Do more of what works. Do less of what doesn't.' But if you really want to derive value, you need to delve deeper. You need to understand what the numbers are telling you.

Improving Customer Experience (2006). Design>Web Design>Assessment>Log Analysis

24.
#32272

Employing Log Metrics to Evaluate Search Behaviour and Success: Case Study BBC Search Engine   (peer-reviewed)   (members only)

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

25.
#19027

The End of the Hit Parade

Once upon a time, if it was on the web, it was good. If it did tricks, so much the better. And how did a company know if its website was really good? Of course, by measuring traffic. The more traffic, the better, right?

Jaleshgari, Ramin. CIO Magazine (2000). Articles>Web Design>Usability>Log Analysis

 
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