Abstract
There are multiple evaluation approaches (methods, instruments, and tools) that can be used for evaluating the CX0. However, these may not be considered by different companies/organizations because they assume that these are not related to the CX. This research analyze 29 evaluation approaches identified in a previous study (Rojas and Quiñones 2021) used in the areas of usability, user experience (UX), and satisfaction. We differentiate and examine these evaluation approaches indicating: (1) the type of participants required to apply them (experts or users); (2) the overall costs needed to use them (cheap or expensive); (3) some disadvantages or potential risks of them; and (4) the CX dimensions that could be evaluated. We found that: (1) most evaluation approaches (69%) require representative users rather than expert evaluators; (2) most evaluation approach (86,2%) are inexpensive to use since they do not need equipment or training; and (3) the most evaluated CX dimension corresponded to “sensorial”, while the least evaluated CX dimension was “emotional”.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Rawson, A., Duncan, E., Jones, C.: The truth about customer experience. Harv. Bus. Rev. 91(9), 90–98 (2013)
Lewis, J.R.: Usability: lessons learned. and yet to be learned. Int. J. Hum. Comput. Interact. 30(9), 663–684 (2014). https://doi.org/10.1080/10447318.2014.930311
Rusu, V., Rusu, C., Botella, F., Quiñones, D., Bascur, C., Rusu, V.Z.: Customer eXperience: a bridge between service science and human-computer interaction. In: Ahram, T., Karwowski, W., Pickl, S., Taiar, R. (eds.) IHSED 2019. AISC, vol. 1026, pp. 385–390. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-27928-8_59
Morville, P.: User Experience Design, Semantic Studios (2005)
Rojas, L., Quiñones, D.: Customer eXperience evaluation methodologies: a literature review. ACM Int. Conf. Proc. Ser. (2021). https://doi.org/10.1145/3488392.3488398
Schmitt, B.: Experiential marketing. J. Mark. Manag. 15(1–3), 53–67 (1999)
Meyer, C., Schwager, A.: Understanding customer experience. Harv. Bus. Rev. 85(2), 116–124 (2007). https://doi.org/10.1108/00242539410067746
Gentile, C., Spiller, N., Noci, G.: How to sustain the customer experience: an overview of experience components that co-create value with the customer. Eur. Manag. J. 25(5), 395–410 (2007). https://doi.org/10.1016/j.emj.2007.08.005
Verhoef, P.C., Lemon, K.N., Parasuraman, A., Roggeveen, A., Tsiros, M., Schlesinger, L.A.: Customer experience creation: determinants, dynamics and management strategies. J. Retail. 85(1), 31–41 (2009). https://doi.org/10.1016/j.jretai.2008.11.001
Lemke, F., Clark, M., Wilson, H.: Customer experience quality: an exploration in business and consumer contexts using repertory grid technique. J. Acad. Mark. Sci. 39(6), 846–869 (2011). https://doi.org/10.1007/s11747-010-0219-0
Lemon, K.N., Verhoef, P.C.: Understanding customer experience throughout the customer journey. J. Mark. 80(6), 69–96 (2016). https://doi.org/10.1509/jm.15.0420
ISO 9241–210. “ISO 9241–210 : 2010 Ergonomics of human-system interaction—part 210 : Human-centred design for interactive systems. International Standard (2019). https://www.iso.org/standard/77520.html
Norman, D., Nielsen, J.: The Definition of User Experience (UX). Nielsen Norman Group. https://www.nngroup.com/articles/definition-user-experience/
Dam, R., Siang, T.: Affinity Diagrams – Learn How to Cluster and Bundle Ideas and Fact. Interaction Design Foundation (2020). https://www.interaction-design.org/literature/article/affinity-diagrams-learn-how-to-cluster-and-bundle-ideas-and-facts
Meng, L.: Literature review. In: Gender in Literary Translation. CIS, vol. 3, pp. 9–28. Springer, Singapore (2019). https://doi.org/10.1007/978-981-13-3720-8_2
Álvarez, T.: Metodología para la evaluación de la experiencia del usuario de sistemas de software interactivos para usuarios ciegos. Universidad veracruzana (2019)
Sherwin, K.: Group Card Sorting: Uncover Users’ Mental Models for Better Information Architecture. Nielsen Norman Group (2018). https://www.nngroup.com/articles/card-sorting-definition/
Jordan, P.W.: Designing Pleasurable Products: An Introduction to the New Human Factors, vol. 53, no. 9 (2000)
Interaction Design Foundation, How to Conduct a Cognitive Walkthrough. Interaction Design Foundation (2020). https://www.interaction-design.org/literature/article/how-to-conduct-a-cognitive-walkthrough
Moran, K.: Setup of An Eyetracking Study. Nielsen Norman Group (2019). https://www.nngroup.com/articles/eyetracking-setup.
Nielsen, J., Molich, R.: Heuristic evaluation of user interfaces. In: Conference on Human Factors in Computing Systems - Proceedings, pp. 249–256 (1990). https://doi.org/10.1145/97243.97281
Business Research Methodology, Observation (2011). https://research-methodology.net/research-methods/qualitative-research/observation
Hackett, G.: Survey research methods. Pers. Guid. J. 59(9), 599–604 (1981)
Burmester, M., Mast, M., Jäger, K., Homans, H.: Valence method for formative evaluation of user experience. In: Proceedings of the 8th ACM Conference on Designing Interactive Systems, pp. 364–367 (2010)
User Interface Design GmbH, Attrakdif (2013). http://www.attrakdiff.de/
Desmet, P., Overbeeke, K., Tax, S.: Designing products with added emotional value: development and appllcation of an approach for research through design. Des. J. 4(1), 32–47 (2001). https://doi.org/10.2752/146069201789378496
Voss, K.E., Spangenberg, E.R., Grohmann, B.: Measuring the hedonic and utilitarian dimensions of consumer attitude. J. Mark. Res. 40(3), 310–320 (2003)
Watson, D., Clark, L.A., Tellenge, A.: Development and validation of brief measures of positive and negative affect: the PANAS scales. J. Pers. Soc. Psychol. 1988(6), 1063–1070 (2017)
Lewis, J.R.: Psychometric evaluation of the post-study system usability questionnaire: the PSSUQ. Proc. Hum. Fact. Soc. Ann. Meet. 36(16), 1259–1260 (1992)
Bradley, M.M., Lang, P.J.: Measuring emotion: the self-assessment manikin and the semantic differential. J. Behav. Ther. Exp. Psychiatry 25(1), 49–59 (1994)
Parasuraman, A., Zeithaml, V., Berry, L.: SERVQUAL: a multiple-item scale for measuring consumer perceptions of service quality. J. Retail. 64(1), 1–30 (1988)
Brooke, J.: SUS: A ‘Quick and Dirty’ Usability Scale. Usability Evaluation in Industry, pp. 207–212 (1996). https://doi.org/10.1201/9781498710411-35
Laugwitz, B., Held, T., Schrepp, M.: Construction and evaluation of a user experience questionnaire. In: Symposium of the Austrian HCI and Usability Engineering Group, pp. 63–76 (2008)
Tague, N.R.: The Quality Toolbox, vol. 600. ASQ Quality Press Milwaukee (2005)
Acknowledgments
This work was supported by the School of Informatics Engineering of the Pontificia Universidad Católica de Valparaíso – Chile. Luis Rojas has been granted the “INF-PUCV” Graduate Scholarship. Luis Rojas is supported by Grant ANID BECAS/DOCTORADO NACIONAL, Chile, No 21211272. Daniela Quiñones is supported by Grant ANID (ex CONICYT), Chile, FONDECYT INICIACIÓN, Project Nº 11190759.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Appendices
Appendix A: Participants, Costs and Disadvantages of Each Evaluation Approach
Evaluation approach | Participant | Cost | Disadvantages |
---|---|---|---|
Affinity diagram [14] | Experts | Cheap | •It requires having previously collected information •It may require a lot of time depending on the variety of information |
AttrakDiff [25] | Users | Cheap | •Not much information is available about this instrument •The original publication is in Deutsch |
Automated usability evaluation software [15] | Experts | Expensive | •Usually, these software are not free to use •Software with lack of flexibility and customization |
Blind finger tracking [16] | Users | Cheap | •A screenshot must be taken each time the user performs a function on the mobile device |
Card sorting [17] | Users | Cheap | •This method may not go deep enough •The results can be very variable and inconsistent |
Cause and effect diagram [34] | Experts | Cheap | •It is difficult to represent the interrelated nature of problems and causes •It is not very useful to represent complex problems |
Co-discovery [18] | Users | Cheap | •The researcher cannot control the direction of the discussion •Not all problems can be identified, only those related to defined tasks |
Cognitive walkthrough [19] | Experts | Cheap | •Experts’ experience may cause them to overlook problems •Not all problems are identified, only those related to defined tasks |
Critical to quality (CTQ) tree [34] | Experts | Cheap | •It depends on other methods to identify needs •It is not very useful to represent complex problems |
Emocards [26] | Users | Cheap | •Difficulty in differentiating emotions by users •The method do not measure the actual emotion, it only measure the perceived pleasantness and arousal |
Eye tracking [20] | Users | Expensive | •Eye tracking equipment and training can be expensive •It is difficult for users to control eye position accurately all times |
Focus group [18] | Users | Expensive | •Participants usually know they are being observed so the answers might be dishonest •This method is not as efficient in covering maximum depth on a particular issue |
Hedonic utility scale [27] | Users | Cheap | •The scale can be interpreted subjectively •Its results may vary depending to the mood of the participant |
Heuristic evaluation [21] | Experts | Cheap | •The relevance of the problems identified depends on the experience of the evaluators •Its costs can easily increase if many expert evaluators are required |
Interview [18] | Users | Cheap | •Participants usually know they are being observed so the answers might be dishonest •Its costs can easily increase making them expensive |
Observations [22] | Experts | Cheap | •The observer had limited control over physical situation •The relevance of the data observed depends on the experience of the evaluator |
Positive and negative affect schedule (PANAS) [28] | Users | Cheap | •The scale can be interpreted subjectively •Its results may vary depending to the mood of the participant |
Post-study system usability questionnaire (PSSUQ) [29] | Users | Cheap | •There is not as much information available for this instrument as others |
Quality function deployment (QFD) [34] | Experts | Cheap | •Categories are based on qualitative aspects and appears to be vague and not very clear |
Questionnaire [18] | Users | Cheap | •Participants may give wrong or unanswered answers •Participants answers might be dishonest |
Self-assessment manikin (SAM) [30] | Users | Cheap | •The scale can be interpreted subjectively •Its results may vary depending to the mood of the participant |
SERVQUAL [31] | Users | Cheap | •It evaluates customer perception in a general way •It only focuses only on service delivery and not on the outcomes |
Supply, Input, Process, Output and Customer (SIPOC) [34] | Experts | Cheap | •The tool is not applicable to all processes •Not very useful to represent complex problems |
Survey [23] | Users | Cheap | •Participants may give wrong or unanswered answers •Its costs can easily increase making them expensive |
System usability scale (SUS) [32] | Users | Cheap | •The instrument is a subjective measure of perceived usability •The instrument only provide quantitative data so it is difficult to know why participants assigned certain scores |
Thinking aloud [18] | Users | Cheap | •Participants limit their responses because they are observed •Not all problems can be identified, only those related to defined tasks |
UX questionnaire (UEQ) [33] | Users | Cheap | •Participants may have problems to interpret the items of the scale |
Valence method [24] | Users | Cheap | •Participants should use the product or prototype for the first time during the evaluation •Its results may vary depending to the mood of the participant |
Web usage analysis [15] | Users | Expensive | •There is not as much information available for this method as others |
Appendix B: Association Between CX Dimensions and Evaluation Approaches
Evaluation approach | CX dimensions | |||||
---|---|---|---|---|---|---|
Sensorial | Emotional | Cognitive | Pragmatic | Lifestyle | Relational | |
Affinity diagram [14] | X | X | X | X | ||
AttrakDiff [25] | X | X | ||||
Automated usability evaluation software [15] | X | |||||
Blind finger tracking [16] | X | X | X | |||
Card sorting [17] | X | X | X | |||
Cause and effect diagram [34] | X | X | ||||
Co-discovery [18] | X | X | X | X | ||
Cognitive walkthrough [19] | X | X | X | |||
Critical to quality (CTQ) tree [34] | X | |||||
Emocards [26] | X | X | ||||
Eye tracking [20] | X | X | ||||
Focus group [18] | X | X | X | X | ||
Hedonic utility scale [27] | X | X | X | |||
Heuristic evaluation [21] | X | X | ||||
Interview [18] | X | X | X | X | X | X |
Observations [22] | X | X | X | X | ||
Positive and negative affect schedule (PANAS) [28] | X | X | ||||
Post-study system usability questionnaire (PSSUQ) [29] | X | X | X | |||
Quality function deployment (QFD) [34] | X | X | ||||
Questionnaire [18] | X | X | X | X | X | X |
Self-assessment manikin (SAM) [30] | X | X | ||||
SERVQUAL [31] | X | X | X | |||
Supply, Input, Process, Output and Customer (SIPOC) [34] | X | X | ||||
Survey [23] | X | X | X | X | X | X |
System usability scale (SUS) [32] | X | X | ||||
Thinking aloud [18] | X | X | X | |||
UX questionnaire (UEQ) [33] | X | X | X | |||
Valence method [24] | X | X | X | |||
Web usage analysis [15] | X | X | ||||
Total | 21 | 9 | 20 | 15 | 10 | 10 |
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Rojas, L., Quiñones, D. (2022). Analyzing Methods, Instruments, and Tools for Evaluating the Customer eXperience. In: Meiselwitz, G. (eds) Social Computing and Social Media: Applications in Education and Commerce. HCII 2022. Lecture Notes in Computer Science, vol 13316. Springer, Cham. https://doi.org/10.1007/978-3-031-05064-0_24
Download citation
DOI: https://doi.org/10.1007/978-3-031-05064-0_24
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-05063-3
Online ISBN: 978-3-031-05064-0
eBook Packages: Computer ScienceComputer Science (R0)