Coventry the evidence of the big data how

 

 

 

 

Coventry University

 

Can big data help to improve
sales & profits of consumer products?

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BSc(Hons) Computing (Full
Time)

 

 

 

 

Author: Chan Ka Wai

Academic Year:
2017/2018

Student ID: 177102394

SID: 82939651

Modules: A300CAW

 

 

Abstract

The purpose of this study is
to explore is to explore the impact of big data for sales and profits of
consumer products and to answer the following

 

The literature review
examined both the concept of the operating of big data, also the relationship
between the big data and improve the sales and profits, as well as big data how
can help to improve sales & profits of consumer products.

 

This study is secondary research from the literature and academic
articles. For these research to show the big data boost up the sales and
profits of consumer products. And discuss the opportunities and benefits of big
data to improve the consumer products.

 

This research confirmed the big data can boost up the sales
and profits of consumer products. Using the big data to analytics the
customer’s need, aim to meet the market demand.

 

1.    
 

1. 
Introduction

Big data mean major includes a large of information, this sizes
beyond the human and ordinary software tools to handle and process data within
a tolerable elapsed time.

 

According to the big data, how can improve sales &
profits of consumer products? Due to Big data always to update the information
and moving target. For the big data, how to impact the marketing activities
from the physical, human, and organizational capital. First, the process of
collecting and storing of consumer activity as Big Data. Also, the process of
extracting consumer insight, and the process of utilizing consumer insight to
enhance dynamic/adaptive capabilities.

 

The goal of this report is to discuss big data how can
impact sales and profits of consumer products. The report includes the
literature and academic articles about the definition of big data.

 

This report also compares tradition sales method to
determine the big data importance. the conclusion of opportunities and benefits
of big data to consumer products. and recommendations how to use efficiently
big data bring the advantage.

 

2. 
Review of Literature

About the review of
literature of big data. most of the literature confirms the importance of big
data. The purpose of this section is to provid the definition of big data.

Moreover, the evidence of the big data how can improve the sales and profit of
consumer products.

 

2.1  The definition of big data

About the definition,
the explanation of Andrea De Mauro said that Big data is a concept and it has
uncertain origins. (Andrea De Mauro,2015) However, much conceptual vagueness
still shrouds its meaning. This term is described the concept is approved,
identifying emerging trends and suggesting opportunities for future development
and provide a consensual definition by mixing common themes of now existing
works and patterns in previous definitions.

 

Another the definitions
of the explanation are from Amir Gandomi. Big data require specific technology
and analytical methods to transform into value. (Amir Gandomi,2015).

 

Big data potential value
is only when leveraged to drive decision making. The organizations need more
efficient to process high volumes of fast-moving and diverse data into
meaningful insights. (Amir Gandomi,2014). Big data can be broken down into five
stages for the overall process of extracting insights. The two major
sub-processes of these five stages are data management and analytics. For the
data management, it involves processes and supporting technologies to receive,
also store data to intend and retrieve it for analysis. On the other hand,
Analytics refers to techniques used to analyze and receive information from big
data. So, Big data analytics can be thought as a sub-process in the overall
process of insight extraction from big data.

A summary of definition
of big data is specified in Figure 1 below

Figure 1: Big Data
Process (Gandomi and Haider, 2015)

2.2  Current of using Big data improve consumer
products for sales and profits

 

In this moment, Big data
is getting more popular. as the result, big data analytic the marketing needs,
and targeted products and service can then be offered through personalized
messages specific to each stage of the consumer cycle such as awareness,
engagement, consideration, conversion, and loyalty. For example, some people
options in to receive marketing messages from a retailer who has an outlet in
the local message. GPS tracking detects that the customer is near the store,
and sends the message to the customer alerting them have a special discount. The
offer is driven by what the retailer already knows about this customer, based
on personalized messages. Aim to the customer’s interest, customer into the
store and purchases using the coupon code in the text message. In this case, it
can improve the opportunity for consumer products for sales and profits. (Michael
Abramow,2014)

 

Big data can get the
real-time insights on product demand. The retailers can visit data on product
demand levels on a minute-to-minute basis across their stores. In this moment,
the retailers can real-time adjustment (Barbara Thau,2016). Big data also can
get the information for customer’s store loyalty details and the credit card
purchases. this information can be used to foresee customer’s needs ahead of
time. For example, the grocers can use big data to analytics to determine how
often customers buy milk, condiments, or different products, and then send each
different coupon based on their specific purchasing habits. (Barbara Thau,2016)

 

At the market competitiveness of manufacturing,
integrating data from research and development, engineering, and manufacturing
units to enable concurrent engineering can significantly save time to market and
raise quality. For the Sales revenues and profitability,
McKinsey said that the retailers using big data analytics can improve the
operating margins by more than 60%.

 

Figure2. Big Data
Analytics Industry Value.(Michael Abramow,2014)

3. 
Discussion

The

 

4. 
Outline Plan

Steps

Analysis

1.   
Circle the directive verbs, if there are any. Think about what they are
asking you to do.

 
 
 
 
 

2.   
Underline the main content words. Think about what they mean.

 
 
 
 
 

3.   
Think about what kind of information you will need to participate in the
discussion in order to support your point of view.

 
 
 
 
 
 
 

4.   
Make the points into headings for your note-taking

 
 
 
 
 

5.   
Think about what kinds of text would have the information you are looking
for.

 
 
 
 
 

 

In this paper, the definitions of big data.

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