  The Internet service provider industry is currently experiencing intense
competition as companies strive to provide top-notch services to their
customers. Providers are introducing cutting-edge technologies to enhance
service quality, understanding that their survival depends on the level of
service they offer. However, evaluating service quality is a complex task. A
crucial aspect of this evaluation lies in understanding user experience, which
significantly impacts the success and reputation of a service or product.
Ensuring a seamless and positive user experience is essential for attracting
and retaining customers. To date, much effort has been devoted to developing
tools for measuring Quality of Experience (QoE), which incorporate both
subjective and objective criteria. These tools, available in closed and
open-source formats, are accessible to organizations and contribute to
improving user experience quality. This review article delves into recent
research and initiatives aimed at creating frameworks for assessing user QoE.
It also explores the integration of machine learning algorithms to enhance
these tools for future advancements. Additionally, the article examines current
challenges and envisions future directions in the development of these
measurement tools.
