Market Research Report: Data Analytics for JWS Research (HC2022)

This report provides an executive summary of market research conducted for JWS Research, a company specializing in marketing research consultancy. The report emphasizes the importance of data analytics derived from social media platforms in today's business environment. It explores how data analytics can be applied to social media tools to improve business decisions, understand customer sentiment, and enhance marketing strategies. The report details the objectives of sentiment analytics, including the use of natural language processing and machine learning. It highlights the significance of data analytics in offering dedicated social media intelligence packages, improving customer service, and gaining a competitive advantage. The analysis covers various aspects such as competitive advantage, customer insights, and product/service improvements based on social media data. The report also references key performance indicators and the impact of social media on real-time consumer interactions, ultimately aiming to maximize earnings and reduce customer service expenditures. The conclusion emphasizes the opportunities social media creates for companies to engage with customers and drive revenue.

HC2022 Market Research
Report

Executive Summary
JWS research is one of the privately-owned company for handling the marketing research
consultancy. Here, the company is working on the enhancement of the technology with proper
services for the clients. It includes the details related to the ACT Government, Cancer Institutes,
Government of South Australia etc., where the major source of data is from social media. Hence,
the report will discuss about how the data analytics will work on the social media tools with
proper business environment setup.

Contents
Executive Summary.........................................................................................................................1
Introduction......................................................................................................................................2
Importance of Data Analytics based on Social Media.....................................................................2
Conclusion.......................................................................................................................................4
References........................................................................................................................................4

Introduction
In today’s time, the social media analytics is about the gathering of inform that is coming from
the different websites that will help in making different business decisions. Here, it determines
the customer sentiment to support the marketing and the other related customer service activities.
The data analytics approach is important for JWS research as it will help in improving the
standards for people to follow their presence on Facebook and interact with the people as well.
The objectives of the same are to work with involvement of sentiment analytics where the
natural language processing and machine learning helps in determining about quantifying the
scores based on social media interactions. The focus is on handling the offer packages that are
dedicated to social media intelligence.
Importance of Data Analytics based on Social Media
The data analytics are important for the company JWS research as it is able to offer the dedicated
package to the social media intelligence. The major problem comes with the artificial
intelligence where there is advancements focusing on the ability to deal with the information for
proper decision making. The bigdata includes the user information which is being collected on
the social networking platforms that allow the marketers in allowing a proper understanding
related to consumer behavior (Gandomi et al., 2015). The target for this is to focus on ability to
target the individuals and then work on providing the increased profits with lowered
advertisement costs. The target is about the receiving information about the products and
services. The data analytics help in determining influencing marketing strategies where the
techniques are for business using for the social media. The analysis is through the demographics
with working on the multiple social media platform. The social media analytics with data will
help in extracting the information which is important for the public to perceive the brand. It
includes the different products where the consumers likes, and the dislikes are seen apart from
the business to quantify the use of less reliable polling and the focus groups.
It also includes the process that relates to the stakeholder conversations on the digital media and
the processing is then structured to lead to a more information driven business decisions and
centrality for the brands and the business (Felt, 2016). The social media helps in analyzing the

areas with computer technology with human traces for determining about political standards. The
perspectives are determined with the data wider range and then establishing the subject’s with
properly identifying the data and the other subsets. They are mainly to focus on the interpretation
of the information and the noisy data with filtering of the same through only the relevant
information There are attributes which are defined to work with structural forms that includes the
formatting repository through database patterns. The social media content is then generated with
variety of venues like the news sites which includes the questions which needs to be addressed
through gaining the perspectives related to the in-depth analysis. The understanding is about how
the examination and understanding the audience. The social media analytics help in working
towards collecting the data from the social media where the evaluation is for making different
decisions (Fulgoni et al., 2016). This enables the enterprises to execute the focused engagements
with enhancing social collaborations for business functions like customer service, marketing,
support. The social media is important for the real time consumers, where JWS try to work on
figuring the business objectives and including maximized earnings and decreased customer
services expenditures. The key performance indicators help in data evaluation through:
a. Competitive Advantage: It allows the organization to work with competitive edge over
the competitors that leads to the facilitation of the brands.
b. Learning from the customers: The customers have generally effective solutions where the
products are determined through proper documentation and the chances related to use of
error increase.
c. Improvement in products and services: The major goal is about working on the higher
volumes of information that contains the consumer sentiments with evaluating user
experiences for product and services (Health, 2014).
Considering the business operations, the improvement of the products and services is done
through the tweets, blogs and the complaints for the product and services. There are huge volume
of information that contains the information which could be for evaluating the user experience
and the product or services (Raghupathi et al., 2014). This will help in improving the
performance of the companies. JWS needs to work on handling the comments of other customers
where virtual communities are focusing on discussing about the products and the companies
(Hussain et al., 2014). It gives the real time pulse of brand sentiment and adoption with focusing

on the collection and properly analyzing the data interpretations for the social media. It is
important data for the marketers where the firms have been able to create a special position and
work with interrelated factors to each other. The social networking analysis is mainly for
customer designing products and then selling them on the private homepage (Batrinca et al.,
2015).
Conclusion
Social media has been able to create new and different opportunities for the companies that tends
to engage mainly with the customers (Fan et al., 2014). The customers bind to companies with
driving the revenues that gains and reduces the costs which are related to the customer churning.
The social marketing includes the needs that needs to be monitored and managed where the
alternativeness can lead to work on adapting the different traditional marketing campaigns. It
include the social management with properly designing, initiating and then managing the social
media marketing campaigns and performing based on allowing the deep understanding and
effectiveness for monitoring the campaigns.
References
Batrinca, B. and Treleaven, P.C., 2015. Social media analytics: a survey of techniques, tools and
platforms. Ai & Society, 30(1), pp.89-116.
Fan, W. and Gordon, M.D., 2014. The power of social media analytics. Communications of the
ACM, 57(6), pp.74-81.
Felt, M., 2016. Social media and the social sciences: How researchers employ Big Data
analytics. Big Data & Society, 3(1), p.2053951716645828.
Fulgoni, G.M., Lipsman, A. and Davidsen, C., 2016. The Power of Political Advertising:
Lessons for Practitioners: How Data Analytics, Social Media, and Creative Strategies Shape US
Presidential Election Campaigns. Journal of Advertising Research, 56(3), pp.239-244.
Gandomi, A. and Haider, M., 2015. Beyond the hype: Big data concepts, methods, and
analytics. International Journal of Information Management, 35(2), pp.137-144.

Heath, S., 2014. System and method for using global location information, 2D and 3D mapping,
social media, and user behavior and information for a consumer feedback social media analytics
platform for providing analytic measurements data of online consumer feedback for global
brand products or services of past, present or future customers, users, and/or target markets.
U.S. Patent 8,909,771.
Hussain, A. and Vatrapu, R., 2014, May. Social data analytics tool (sodato). In International
Conference on Design Science Research in Information Systems (pp. 368-372). Springer, Cham.
Raghupathi, W. and Raghupathi, V., 2014. Big data analytics in healthcare: promise and
potential. Health information science and systems, 2(1), p.3.