Citation

Lim, Zhou Yi (2024) Measuring engagement of online marketing website with Cluster-N-Engage framework. Masters thesis, Multimedia University.

Full text not available from this repository.

Abstract

With digital connectivity and virtual interactions becoming ubiquitous, business organisations are now recognising the potential of online platforms to reach their target audience. The mode of advertising has gradually shifted from offline advertising to online advertising. It is common for business organisations to use online marketing websites to share and promote information about their products or services. By creating an online presence, businesses can expand their horizons beyond geographical limits, allowing them to effectively target customers from different parts of the world. Therefore, measuring the advertising effectiveness of an online marketing website is important to help organisations in achieving its objective. Users invest more attention towards an online marketing website if they feel engaged and involved. The level of user attention while navigating a website is a key factor in determining its advertising effectiveness. Web usage mining can be performed on the weblog of the website to extract user navigational behaviour and gain valuable insights into the useful activities of the users. To measure the user engagement of the website, user engagement metrics are used. Existing literature have suggested to create a single engagement score that simplifies complex user navigational behaviour, providing organisations with the overall engagement of a website. However, the score falls short in identifying the user navigational behaviour that contributes to website engagement. With that said, this study has developed an engagement framework, known as the Cluster-N-Engage, which uses web usage mining and user engagement metrics to measure user engagement from the clusters of user navigational behaviour on online marketing websites.

Item Type:	Thesis (Masters)
Additional Information:	Call No.: ZA4235 .L56 2024
Uncontrolled Keywords:	Web usage mining
Subjects:	Z Bibliography. Library Science. Information Resources > ZA3038-5190 Information resources (General) > ZA4050-4775 Information in specific formats or media
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	29 Aug 2024 08:35
Last Modified:	29 Aug 2024 08:35
URII:	http://shdl.mmu.edu.my/id/eprint/12895

Downloads

Edit (login required)