eThesis - Kauppakorkeakoulun sähköiset gradut

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Objectives of the Study:

The unique measurability of websites allows the collection of detailed information about the behavior and characteristics of website visitors. This thesis examines the value of different web metrics based on the behavior of website visitors. The objective is to develop and test a method for identifying key metrics that are the most valuable for site developers to follow. The key web metrics are expected to contain the most useful and relevant information about the website visitors. The value of the web metrics is evaluated by examining the relationships of the metrics towards website conversions. This thesis also suggests how different web metrics can be analyzed to reveal important characteristics of site visitors and how web metrics can be used to evaluate the effectiveness of the different aspects of a website.

Academic background and methodology:

This thesis draws from the field of web analytics. Based on the previous work on the field, a new framework for the role of web metrics analysis in website development is presented. The framework forms the basis for the case study conducted in this thesis. The case study examines one corporate website by following fourteen different web metrics during a period of six months. The relationship analysis between the web metrics and conversions is conducted using correlation and regression analyses. The objective of the case study is to test if meaningful key metrics can be identified using the method proposed in this thesis.

Findings and conclusions:

The case study conducted in this thesis identifies two key web metrics for the site under examination: search engine traffic and the rate of return visits. Search engine traffic was selected as a key metric based on the relationship analysis and the rate of return visits was chosen based on the examination of the visitor characteristics. The successful identification of relevant key metrics suggests that the framework proposed in this study can be used as the basis for web metrics analysis. Based on the results of the case study, this thesis proposes that in addition to aggregated metrics, segmented web metrics are needed in order to achieve a more diverse view of the web users.