Evaluation of Web Site User Experience

User attitude is continually shaped throughout their interaction with a Web site. You want to collect as much attitude data as you can for various reasons, including: providing interpretation of ambiguous behavior, such as long dwell time that can indicate interest or confusion; monitoring general attitude trends over time that result from marketing efforts and repeated exposure to the site; gathering user feedback and suggestions that can trigger direct action or further research.

The process of capturing such data might interrupt the user experience and alter the user’s attitude, which could corrupt the data and reduce its value. So, the method used to collect attitude data must be non-invasive and be incorporated into the user’s experience at the site.

Automating user experience testing of any Web site is a difficult challenge at best, especially in light of the need to balance data quality and quantity: gathering rich data is essential to deriving meaning and understanding, and a sufficient quantity of data is essential to making findings valid and statistically significant.

  

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Web Application Performance Measurement and Tuning

To combat the growing problem of poor web application performance and safeguard the rising amount of business revenue gained via online channels, load testing strategies, tools and services have experienced a transformation in terms of both awareness and adoption.

Business requirements for web application load testing and application performance testing as a means for ongoing performance measurement and tuning have become more rigorous over the past several years.

Measurements derived with load testing tools should provide a clear understanding of where performance bottlenecks reside and aid in infrastructure and capacity planning of computing resources. When derived from meaningful load tests, results serve as a guide to helping IT staff make informed decisions about the performance of their applications and infrastructures.

A solid load testing strategy must complement performance monitoring and analysis in a production environment and, in turn, production monitoring and analysis should be leveraged to improve the accuracy of load tests.

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Challenges of creating and managing robust applications

Application availability is the first quality encountered by customers, but the last one to be determined by the development process, because it depends on the quality of everything else that happens during design, development, and testing web applications. A chain is only as strong as its weakest link, and developing RIAs will uncover any weaknesses in an enterprise’s development and SLM processes.

RIAs inevitably involve running complex code on the client, and use more complex and application-specific strategies to manage the communication between browser and server. Making such complex code efficient and bugfree is not a task to be taken lightly.

Better tools are needed to help us meet the challenges of creating and managing robust applications; today, while the Adobe suite of Flash tools is a little more mature, Ajax development and application performance testing tools are still in their infancy. The Open Ajax initiative may help to address this issue. Therefore deploying an RIA successfully will demand more resources— skills, tools, process, time, and (of course) money—than would be required to deploy a more traditional Web-based application in which all application logic is executed on the server. Enterprises that decide to employ the technology must be prepared to invest more in design, development, testing and management to make it successful.

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Challenges And Surprises With Web Load Testing

To gauge a Web site’s capacity and scalability, web load testing is one of the most effective ways. But the load tests need to simulate real scenarios. The huge numbers and ranges of variables involved in Web site load testing will always present challenges and surprises.

A load testing scenario can be made significantly more realistic by simulating the behavior of tolerant and

an intolerant user. Familiarity is a major factor in how quickly a simulated user navigates from one page to the next. As with latency tolerance, different people will behave in different ways: users that are very familiar with the Web site move more rapidly (therefore creating more load per unit of time) than users who are visiting the Web site for the first time and need to read and understand how the Web site is organized to go from one page to the next.

You can also run simple in-house experiments using employees and their friends and family to determine, for example, the page viewing time differences between new and returning users.

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