Holmes Institute HC2022 Marketing Research Report: Tech Impact

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AI Summary
This report, prepared for JWS Research, a Sydney-based marketing consultancy, investigates the impact of technology on marketing research in today's business environment. It focuses on how JWS can leverage data analytics, social media, and mobile technologies to enhance its services and provide more efficient and accurate results for its clients, which include government and healthcare organizations. The report explores the influence of social media, improvements in data collection through new software, the enhancement of mobility in data analysis, and the role of data analytics in personalizing marketing approaches. It highlights the benefits of adopting these technologies, such as improved customer insights, personalized marketing, and the ability to conduct full-funnel marketing. The report emphasizes the importance of adapting to the digital landscape to better serve a diverse clientele and concludes by advocating for the adoption of data analytics to customize services and make perfect data analysis for the clients.
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Running head: MARKETING RESEARCH
MARKETING RESEARCH
Student’s Name
University Name
Author’s Note
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Executive Summary
In the following report a detailed analysis of the data analytics technology and how wit can
create value towards the organisation have been highlighted. Focusing on the advantages that
the potential market researchers reap out of the business research software and how they
implement the data accumulated in order to develop their clientele have been highlighted. In
this regard, the company that have been focused upon, have been working with major
organisations which include a large and variegated clientele and as an impact they need the
implementation of analytics to recover third party data as they might have an insight of the
business prospects. Although the clientele of the company here includes a health care
institute, the business perspective of that client has only been considered here.
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Table of Contents
1. Introduction............................................................................................................................4
2. Discussion...............................................................................................................................4
2.1 Influence of the social media...........................................................................................4
2.2 Improvements in the data collections..............................................................................4
2.3 Enhancement of mobility in Data analysis.......................................................................5
2.5 Full Funnel marketing in an age of digitalisation.............................................................6
3. Conclusion..............................................................................................................................6
4. Reference List.........................................................................................................................7
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1. Introduction
In the following report a strategy making framework have been suggested to the JWS
consultancy firm so that they can adapt to an approach of data analytics, mobility and other
digital market researching media. This report provides an insight regarding the usage and
adaptation of these digital tools and suggest ways in which the executive management of the
company can consider the implementation of the following described technologies in the
context of their clientele.
2. Discussion
2.1 Influence of the social media
The landscape of market research is expanded by the advent of social media websites
like Facebook, Twitter, Google+, and LinkedIn and so on. Various exciting ways of market
research is being implemented by the social media. However, it requires the consultancy firm
to undertake the development of new set of skills. An environment of unfiltered feedback is
fostered by social media. Social media channel are highly favourable for the reputation
management of brands and also creating brand awareness (Archenaa and Anita 2015). Market
researchers can enhance their database with raw data about the customers. Hence the use of
social media would allow the market researchers to remain updated with the current
knowledge about the target market and the demographic trends in the target market.
2.2 Improvements in the data collections
A stream of new software are coming up in order to facilitate market analysts to
collect data. Other than the traditional data collection media like focus groups, and surveys or
interviews, technology have enables the market researchers to become more specific in
measuring current data and becoming more updated with the feedback (Manogaran et al.
2017). In case if the Gold Coast Airport wants the company to undertake a mood sensing
survey, in order to personalise some of the features they want the customer enjoy in order to
gain a competitive advantage. The mood sensing software collects the input data of the
customers and analyses the average customers satisfaction rate to sense what aspects the
company’s services are mostly liked by the customers and what they despised or felt to
require improvements. This is a very popular retail analysis tool for sales studying that
analyses the market acceptance by analysing the share purchase trends of the company and
linking the data with the customer acquisition rate.
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2.3 Enhancement of mobility in Data analysis
Mobility is the most important technological inclusion that is making the market
research faster. Mobility provi8dees and easier and faster access to the consumers. Majority
of the consumers are nowadays carrying a mobile device along with them which is synced
with their various databases in which they have an account. Hence customer feedback
software which particularly have a mobile component are able to collect insights anytime and
from any person. An example can be provided. The South Australian government might want
to conduct an internal demographic based survey regarding the advantages of the recent
government implementation (Wang et al. 2016). Surveys which are mobile responsive like
SMS based surveys, QR codes based surveys or even social media based surveys can help the
consultancy firm to gather better and more perfect responses from the potential respondents
(Idreos, Papaemmanouil and Chaudhuri 2015). More than 50% of the Australians are
claiming access to internet and according to Mobile usage Ratings report about 7 million
Australians are accessing internet over tablets and other devices and as such mobility have
provided researchers a broad scope for communicating with the focus group of the surveys
(Gahi, Guennoun and Mouftah 2016). With the use of mobility software and other
information channels, the company can now send survey requests to more than 20000
respondents and about 1.2 millions in the span of a year.
2.4 Data analytics in the personalisation of the marketing approaches
Data analytics have made it easier for the companies and research consultancy firms
to collect surface level data regarding gender, geographical location, age and customer’s
preferences and behavioural trends. A recent survey in Australia reveals that about 52% of
the customers are most likely to switch to different brands if they find that their preferred
brands are not making much efforts in personalising the channels of communicating with
them. Business analytics software like O2 or EasyJet allows the researchers to accumulate the
data of the pervious responses of the customers so that they feel that they are not data source
s to fill spreadsheets and they have a value as a person (Burmester et al. 2018). In this
context, the consultancy firm can consider appointing capable data scientist since only
accumulation of big data is not the criteria of the market research companies. The outcomes
achieved by the analysis of the data is of real significance. However, the customer interaction
is not enough to realise their multi-faceted reactions as individuals (Belle et al. 2015). Hence
many brands are now considering the augment augmentation of their collected first party data
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with the third party data. However in this context, it is necessary to authenticate the third
party data and check the reliability of the sources from where the third part data have been
collected. It is evident that of the internet users of Australia, about 30% uses a Virtual Private
Network (a VPN network). That is why the organisation should consider the cross device
tracking of the IDs of the various clients they serve so that they can provide the most perfect
analysis of the clients’ data to the most precious clients.
2.5 Full Funnel marketing in an age of digitalisation
The full panel strategy of approach is a well worm approach. Consumers nowadays do
not adapt to simple linear journey of finding a product and then simply going on to purchase
it. Instead the customers often conduct a roundabout way of research from the way of
corporate websites to social media networks. The industries in which the company is serving
involves a clientele that is aged 16 to 46 basically, excepting the Cancer institute. This group
consists of the most efficient social platforms users (Bates et al. 2014). Hence the consultancy
firm have to target as well as nurture the prospective customers so that they can entice the
customers through cross platforms to purchase a product and/or service through the full
funnel approach of marketing.
3. Conclusion
In the above undertaken research study the company under focus have contracts with
major national level clients whose customer base is equally vast and important. As an
outcome the usage of data analytics should be adapted by the company so that the services
can be customised and personalised. Nowadays majority of the potential consultancy
agencies adapt to the data analytics framework to make perfect data analysis for their clients.
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4. Reference List
Archenaa, J. and Anita, E.M., 2015. A survey of big data analytics in healthcare and
government. Procedia Computer Science, 50, pp.408-413.
Bates, D.W., Saria, S., Ohno-Machado, L., Shah, A. and Escobar, G., 2014. Big data in health
care: using analytics to identify and manage high-risk and high-cost patients. Health
Affairs, 33(7), pp.1123-1131.
Belle, A., Thiagarajan, R., Soroushmehr, S.M., Navidi, F., Beard, D.A. and Najarian, K.,
2015. Big data analytics in healthcare. BioMed research international, 2015.
Burmester, G., Ma, H., Steinmetz, D. and Hartmannn, S., 2018. Big Data and Data Analytics
in Aviation. In Advances in Aeronautical Informatics (pp. 55-65). Springer, Cham.
Gahi, Y., Guennoun, M. and Mouftah, H.T., 2016, June. Big data analytics: Security and
privacy challenges. In Computers and Communication (ISCC), 2016 IEEE Symposium
on (pp. 952-957). IEEE.
Idreos, S., Papaemmanouil, O. and Chaudhuri, S., 2015, May. Overview of data exploration
techniques. In Proceedings of the 2015 ACM SIGMOD International Conference on
Management of Data (pp. 277-281). ACM.
Manogaran, G., Lopez, D., Thota, C., Abbas, K.M., Pyne, S. and Sundarasekar, R., 2017. Big
data analytics in healthcare Internet of Things. In Innovative healthcare systems for the 21st
century (pp. 263-284). Springer, Cham.
Wang, G., Gunasekaran, A., Ngai, E.W. and Papadopoulos, T., 2016. Big data analytics in
logistics and supply chain management: Certain investigations for research and
applications. International Journal of Production Economics, 176, pp.98-110.
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