This document outlines a proposed research study on how retailers can improve the customer experience through the use of mobile technologies. The study will use qualitative interviews to understand how consumers interact with innovative technologies like mobile devices during their in-store shopping journey. The objectives are to gain insights into how mobile can enhance the in-store experience and compare customer decision-making for low and high involvement purchases. The methodology will use interpretivism and constructivism approaches with thematic analysis of 10-15 interviews. The findings aim to provide retailers insights on investing in digital technologies to improve customer experience and increase return on investment.

1. The use of Mobile for a better customer experience in the Retail Industry
by Cristina Botet Jolonch · ID: 9522424
MSc Marketing · Manchester Business School
Introduction
The retail industry is certainly key to the United Kingdom’s economy (Rhodes, 2014). As
stated by the UK government, not only do the figures speak for themselves (average weekly
spend in the retail industry is £6.6 billion) (ONS, 2015), but this industry also affects every
community, touching everyone’s lives (Department for Business Innovation & Skills, 2013).
Changes in the environment have constantly pushed firms within the retail sector to adapt
their business activity to meet profitable customers’ needs and wants, looking for their spot
in a highly competitive market (Grewal et al., 2009). In the last decade, the growth of new
technologies has been one of the factors responsible for revolutionising the retail landscape
(Meuter et al., 2003)
Theoretical Background
Customer
Service
Satisfaction Loyalty Profit
Firm
Market
Value
• The fierce competition in the retail market encourages organisations to focus on the
quality of their services (see Figure 1). To act as a clear differentiator, services demand to
be wrapped with experiences (Wiles, 2007; Pine and Gilmore, 1998).
• Therefore, stores need, not only to be considered just a place to sell merchandise, but a
space for people to enrich their lives (Morse and Johnson, 2011; Verhoef et al. 2009).
• Technology can be an ally for retailers to improve customer’s service experience (Grewal
et al., 2009). So far, customer-technology encounters in retail have proven to enhance
convenience, control, speed, autonomy, enjoyment and social interaction (Collier et al.,
2015; Rohm and Swaminathan, 2004, Christodoulides and Michaelidou, 2010).
• Smartphones, considered an extension of human bodies are not only used for social
stimulation, but also as part of the shopping experience. Hence, this device has the
potential to enable retailers to improve consumers’ journey experience anyplace at
anytime (Shankar et al., 2010; Persaud and Azhar, 2012).
• Retailers can’t influence each stage of the consumer journey to the same extent. There
is a need to know which is the best moment to be there (Birss, 2014).
• Customer journey, and so decision making process, is not a linear static process.
Involvement, among other variables is an influencer of the stages adopted by consumers
(Petty et al. 1983)
Figure 1: Customer Service Profit Chain adapted and tested by Wiles (2007)
Research Objectives
• Understand consumers’ interaction with current innovative technologies during the
customer journey with special focus in store
• Gain specific insights into the possibilities of mobile devices to improve consumers’ in
store experience
• Compare and contrast consumer decision-making process in low and high involvement
scenarios
Methodology
• Interpretativism: Aim to understand a reality constructed
by consumers. Therefore the researcher opts for a
subjective and multiple understanding of reality
(Malhotra et al., 2012)
• Constructivism: ‘Knowledge’ will be accomplished thanks
to social actors (i.e. the researcher and participants will
play an active role in shaping the ‘phenomenon’)
(Bryman and Bell, 2011).
• Convenient sample: 10 to 15 Individuals aged from 18 to
30 actively involved in shopping in store at least once per
week.
• Recruited through personal contacts and snowballing
effect from participants’ referrals.
• Face-to-face, in depth, semi-structured and conversational
interviews (Manson, 2004)
• Interviewee considered an active participant in the
construct of ‘knowledge’ (Kvale, 2008)
• The procedure will follow Miles and Huberman (1984)
components of data analysis: flow model
• Phenomenological analysis: data reduced to themes
trying to draw these together to interpret the meaning
(Byrman and Bell, 2011)
Sample
Technique &
Recruitment
• Inductive approach: This study intends to to build theories
from the data collected and analysed.
• Qualitative method; exploratory approach: The purpose
of the research is to try to understand a social
phenomenon, encapsulating consumers’ behaviour,
experiences and feelings towards technological
interaction during their consumption journey; and provide
insights of the nature to the retail industry.
Data
Collection:
Interviews
Data
Analysis:
Thematic
analysis
Theory &
Research
Epistemology
& Ontology
Research
method &
approach
The findings of the study will help retailers to have a deeper understanding of customers’
needs and wants regarding innovative technologies, with special focus on mobile,
throughout their customer journey. Therefore, practitioners will better know how to invest in
digital to get a higher ROI by improving their customers’ shopping experience.
Nevertheless, certain limitations of the research proposed should be considered:
• The knowledge resulting from the research will be context dependent and time bounded
due to its dynamic, participant constructed and evolving nature (Malhotra et al., 2012).
• The limited size and convenient sampling technique will also restrict the validity,
generalizability and objectivity of the results.
• Moreover, only one variable (high vs. low involvement) will be considered when studying
the consumer decision-making process.
Implications & Limitations
Ethical considerations
Voluntary participation and consent of data
being collected
Transparency ensuring participants have a
clear understanding of the purpose and the
use of the data collected
Opportunity to opt out of the study and
subsequent use of its data
Anonymity will be ensured. Avoidance of
sensitive topics
Measures for personal safety
Reference List
BIRSS, D. 2014. The Day Before Tomorrow: The Future of Retail. The Drum Studios.
BRYMAN, A. & BELL, E. 2011. Business research methods 3e, Oxford University Press.
CHRISTODOULIDES, G. & MICHAELIDOU, N. 2010. Shopping motives as antecedents of e-satisfaction and e-loyalty. Journal of Marketing Management, 27,
181-197.
COLLIER, J. E., MOORE, R. S., HORKY, A. & MOORE, M. L. 2015. Why the little things matter: Exploring situational influences on customers' self-service
technology decisions. Journal of Business Research, 68, 703-710.
DEPARTMENT FOR BUSINESS INNOVATION & SKILLS. 2013. A Strategy for Future Retail - Industry and Government delivering in partnership October 2013 ed.
GREWAL, D., LEVY, M. & KUMAR, V. 2009. Customer experience management in retailing: An organizing framework. Journal of Retailing, 85, 1-14.
KVALE, S. 2008. Interviews : an introduction to qualitative research interviewing London, SAGE.
MALHOTRA, N. K., BRIKS, D. F. & WILLS, P. 2012. Marketing Research: An Applied Approach, Essex, Pearson Education Limited.
MANSON, J. 2004. Semistructured Interview. In Michael S. Lewis-Beck, A. Bryman, & Tim Futing Liao (Eds.), The SAGE Encyclopedia of Social Science Research
Methods. (pp. 1021-1022). Thousand Oaks, CA: Sage
MEUTER, M. L., OSTROM, A. L., BITNER, M. J. & ROUNDTREE, R. 2003. The influence of technology anxiety on consumer use and experiences with self-
service technologies. Journal of Business Research, 56, 899-906.
MILES, M. B. & HUBERMAN, A. M. 1984. Drawing valid meaning from qualitative data: Toward a shared craft. Educational researcher, 20-30.
MORSE, G. & JOHNSON, R. 2011. Retail Isn't Broken. Stores Are. Harvard Business Review.
OFFICE FOR NATIONAL STATISTICS. 2015. Retail Sales, February 2015 [Online]. UK. Available:
http://www.ons.gov.uk/ons/rel/rsi/retail-sales/february-2015/index.html [Accessed 22nd April 2015].
PERSAUD, A. & AZHAR, I. 2012. Innovative mobile marketing via smartphones: are consumers ready? Marketing Intelligence & Planning, 30, 418-443.
PETTY, R. E., CACIOPPO, J. T. & SCHUMANN, D. 1983. Central and Peripheral Routes to Advertising Effectiveness: The Moderating Role of Involvement.
Journal of Consumer Research, 10, 13.
PINE, B. J. & GILMORE, J. H. 1998. Welcome to the Experience Economy. Harvard Business Review.
RHODES, C. 2014. The Retail Industry: statistics and policy. In: STATISTICS, E. P. A. (ed.).
ROHM, A. J. & SWAMINATHAN, V. 2004. A typology of online shoppers based on shopping motivations. Journal of Business Research, 57, 748-757.
SHANKAR, V., VENKATESH, A., HOFACKER, C. & NAIK, P. 2010. Mobile marketing in the retailing environment: current insights and future research avenues.
Journal of Interactive Marketing, 24, 111-120.
VERHOEF, P. C., LEMON, K. N., PARASURAMAN, A., ROGGEVEEN, A., TSIROS, M. & SCHLESINGER, L. A. 2009. Customer experience creation:
Determinants, dynamics and management strategies. Journal of Retailing, 85, 31-41.
WILES, M. A. 2007. The effect of customer service on retailers’ shareholder wealth: the role of availability and reputation cues. Journal of Retailing, 83, 19-31.
Gantt Chart
An overview to the whole process of the research to help having clearer schema of the
different stages and the time the researcher is planning to invest in each of them.
The timeline is subject to external factors affecting the development of the procedure.
MARCH APRIL MAY JUNE JULY AUGUST SEPTEMBER
Topic selection 2 weeks
Background and Literature Research
14 weeks
Methodology
4 weeks
Interview Guide
4 weeks
Participants Recruitment
3 weeks
Data Collection
4 weeks
Data Analysis
3 weeks
Discussion
3 weeks
Conclusion
2 weeks
1st Draft
Revising Chapters
3 weeks
2nd Draft
Editing and proofreading
2 weeks
Binding
Deadlines
Poster Day
29th
Research Proposal
6th
Ethics form
29th
Dissertation Submission
7th
• There is very little evidence in the existing literature regarding how and when mobile
devices can contribute to enhance the customer shopping experience.