User Experience Measurement: Recent Practice of E-Businesses

User Experience Measurement: Recent Practice of E-Businesses

Oryina Kingsley Akputu, Kingsley Friday Attai
DOI: 10.4018/978-1-7998-3756-5.ch015
OnDemand:
(Individual Chapters)
Available
$37.50
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

User experience (UX) measurement has become a powerful component in determining the usability success or failure of products or services that are marketed via e-business channels. Succcess in the e-business does not only depend on building stellar software interfaces but also on competitive receptiveness to customers experience or feedback. Only e-businesses that can effectively measure the UX to forecast and understand the future are able to stay afloat and not get drown in the highly competitive market. The development of various UX metrics and measurement techniques have helped to quantify user feedack but most of these rely on different contextual assumptions. As a result, choosing appropriate UX techniques that match a particular business need becomes difficult for most e-business concerns. This chapter provides an overview of recent UX measurement techniques that are relevant to the e-business settings in the Web 2.0 era. The objective is to elaborate on what tools that have been employed in literature to measure UX and possibly how these can be employed in practice.
Chapter Preview
Top

Introduction

An e-business refers to a company that does most of its commerce of buying and selling electronically or over the internet, using sales and marketing information systems. Typical examples of such businesses as shown in fig.1, with no preferential order, include, Zara, Jumia, Konga, ebay, Walmart and many others. About 80% of a chunk of data and product information for similar line of businesses which are however, brick and mortar, in the past were unstructured and found in many forms (Alalwan & Weistroffer, 2012). Information assets of those businesses such as product sale, purchase and usage of products or services were neglected as employees and customers alike had to search extensively for the information they needed.

For someone searching what information is available, where to find it, and what information is consistent, up-to-date, and correct often experienced information overload. However, the current era of web 2.0 has offered convenient techniques in the collection of customer experience data regarding usage of products or services. The e-business systems now are improved in information search accuracy and speed with reported reduction in overload issues (Gan et al., 2020; Tang, Wang, Guo, Xiao, & Chi, 2018; Wu, Huang, & Jiang, 2019). One concern of most e-business applications has remained making products and services more customer centered, hence the emergence of “user experience (UX)” concept. The UX concept is successor to “usability”- a widely accepted measure of quality of most products and services in the information system domains. Most e-business outlets have succeeded today partly on the basis that, they offer a stellar UX for their products and services; others have failed due to a terrible UX. It is no longer myth that UX can make or break any potentially great e-business; a good UX management has contributed to many success stories in the e-business market.

Therefore, the first critical consideration for any e-business concern is for their product or service to meet customer’s needs and expectations. The business offering has to be highly usable, look, and feel good, the way the customers expect it to be.

Figure 1.

Selected examples of e-businesses

978-1-7998-3756-5.ch015.f01

In 2018, Forbes.com, a renowned global media company published an article describing why Zara, the world’s largest clothing retailer, succeeds above its competitors. Zara had introduced an Augmented Reality technology to improve customer UX in shopping in its online outlets. The Augmented Reality is a technology that offers capability of superimposing a computer-generated image on the user's view of the actual world, thus creating a composite view (Azuma et al., 2001; Carmigniani et al., 2011). By analyzing customers purchase behavior over time, Zara professionals discover patterns that could be used to interpret buying habits of each shopper. The shoppers could engage their mobile phones to view models wearing a variety of selected fashion styles by clicking on sensors displayed on AR-enabled shop windows. The AR-enabled technology was initially launched in 120 stores worldwide irresistibly pulling customers, mostly the millennial and other customer segments into the stores. With the AR application and in many other ways Zara excels more than its closest competitor H&M that remained fixed on old form of market model for success. Two more case studies for Amazon and Walmart can be found in Appendix 1.

Key Terms in this Chapter

User: Someone that uses a product or service such as sales app.

Micro Interactions: Either events, transformations, or animations that creates engaging moments when an end-user interacts with the UI of an electronic device.

Experience: Knowledge acquired when using a system or product or due to a person's participation in an activity.

Machine Learning: Application of AI that makes systems to instinctively learn and get better from experience without the use of explicit instructions.

Feedback: Remarks made by a user as a reaction or as an opinion to offer useful information on how to improve a product or service.

Expert: An individual that is highly skilled or has great knowledge in a particular area or field.

Machine: An electronic device that is programmable; it is capable of executing a programmed list of instructions given to it.

Return on Investment: A business condition when investment cost compares lower to its gains or profits.

Business Concern: A commercial enterprise and its labor force including the executives.

Augmented Reality: A technology that has to do with computer induced scenario of an interactive real-world environment where object residing in it are enhanced with perceptual information across multiple sensory cues (e.g., visual, auditory, haptic, etc.).

Product: A thing that is manufactured or bought for sale by a business concern.

Customer: An individual that pays for a product or service.

Complete Chapter List

Search this Book:
Reset