Loading...

Big Data. Implementation of a big data based mobile application

Seminar Paper 2016 23 Pages

Business economics - Business Management, Corporate Governance

Excerpt

Table of Contents

II. List of Abbreviations

III. List of Figures

IV. List of Tables

1. Introduction
1.1 Relevance of the topic
1.2 State of research
1.3 Research question
1.4 Limitations
1.5 Procedure

2. Theoretical background
2.1 Customer knowledge in sales
2.2 Big data
2.3 Mobile shopping applications
2.4 Department stores

3. Potential for Sales Managers
3.1 Sales Objectives
3.2 Tracking data
3.3 Analyzing data
3.4 Activities to achieve sales objectives

4. Conclusion & Forecast

5. Bibliography/Reference list

II. List of Abbreviations

illustration not visible in this excerpt

III. List of Figures

Figure 1: Rough big data adoption strategy

Figure 2: Instruments of customer research (Rudolph 2005, p. 67)

IV. List of Tables

Table 1: Overview of central customer information (Homburg et al. 2012, p. 197)

Table 2: Opportunities of a mobile shopping application (own presentation)

Table 3: Goals of commerce policies (own presentation)

Abstract

The following research paper states out the analysis of the potential of a big data based shopping application for a sales manager of a store department in Germany. Based on a theoretical-conceptual analysis the paper gives a theoretical background regarding the necessary customer data in sales, big data, mobile shopping applications and the store departments. Considering the importance of big data in commerce and the rising amount of data generated by mobile applications, the paper at hand presents which data can be tracked, which analysis can be conducted with the data and what are potential activities for a sales manager to achieve mentioned aims in the different marketing policies and the overarching aim to increase profit. The findings of the analyses demonstrate that the implementation of a mobile shopping app offers many activities to achieve or support sales and marketing goals but the complex situation of store departments also needs to be taken into account.

1. Introduction

One of the buzzwords in the actual digital change is “Big Data”. A vast amount of data is produced in nearly every process thinking of software equipped devices and the use of social media, payment via bank card, bookings and orders and so on. Every month in 2015 approximately 4.4 Exabyte of data traffic runs over mobile data connection worldwide and it will be round about 15.9 Exabyte in 2018 (Wilkens 2013). Popular companies like Google, Facebook or Amazon show how diverse Big Data can be used in the value chain. The storage of data is getting cheaper while computers and data processors are getting faster. The resource data is becoming as important as the resources labour and capital (Cukier 2010). This resource can be used. Change data to knowledge means to optimize processes, to make better decisions and to develop completely new business models (Bloching et al. 2015, p. 9). Someone who draws the right conclusion out of data can be ahead of the competitors. Data can be effectively used online but also offline. Here as well, the purchase experience can be improved, concrete purchasing decisions can be triggered and more customers can be attracted to the store (Schwarz 2015, p. 11).

1.1 Relevance of the topic

Data is everywhere and new data is produced in every second. The challenge in Big Data is how to evaluate the data and how to use the data. The selection between important and unimportant data is the harder the bigger the amount of data is. A company should know what data they need and what tools they need to evaluate the data efficiently. In a lot of cases the data that a company produces or gets is not linked. As the forecasts of developments and buyer behaviour are getting harder to draw up it is awkward for a company not to know how to handle the data. They have the necessity to act faster and quicker. This is only possible if they have relevant information in a way that they can derive action approaches (Hoffmann 2015, p. 44).

1.2 State of research

During the last years a few books were published about big data. In 2015 the book “Smart Data” was published. It focuses on the change from big to smart data. That means that it is more important to have the right data in the right variance which then is called smart data (Bloching et al. 2015, p. 10). Kling points out that the six aspects namely data, ethics, society, and culture, organization, legal situation and technology are concerned by big data. She represents the potential and the barriers of the use of big data in the context of companies (King 2014). Also the book “Big Data im Marketing” which was published in 2015 examines aspects of big data that are important for marketers for an effective customer approach (Schwarz 2015) as well as the book “Smart Big Data Management” from 2014 does. From the point of view of information technology big data is considered in the book “Act Big”, which links big data to the providing and the use of information (Knauer 2015). These books generally point out what is important in the context of big data for marketers and sales managers but less research can be found on the special use of big data in the context of mobile application apps and even not in the context for store departments.

1.3 Research question

As it was mentioned in the relevance of the topic it is important for a company how to handle data. This paper focuses on the data a sales manager can get from a big data based application and how to use this data. The question for commerce is how big data helps and that leads to the following research question: Does the implementation of a big data based mobile application enhance a department store’s sales manager’s possibilities to increase profit?

To answer that question it is necessary to find out which data a sales manager needs to derive action approaches and what data he can get from such a mobile application. That will be presented for the branch of department stores.

1.4 Limitations

In this paper the technological aspects of big data that includes the implementation as well as the operation and maintenance and its storage won’t be mentioned. The focus is on the local department store market in Germany. That means that online purchase is not taken into account. It is also assumed that enough people would use such a big data based mobile application app and therefore no further research will be done in this field. Moreover no further aspects of other data generating programs or software like facebook for example will be considered. In addition, the legal regulations of the storage and use of the data won’t be stated in this paper.

1.5 Procedure

This seminar paper focuses on the data that can be generated by a mobile application and how this data can be used efficiently by a sales manager of a department store to increase profit. The used method in this paper is a theoretical-conceptual analysis. In the first part of the paper the importance of customer knowledge in sales, as well as big data and the mobile shopping application will be explained. Afterwards the branch of department stores and their special characteristics will be stated. In the second part of the paper it will be presented how the possibilities for a sales manager to create higher profit can be enhanced by the data of the shopping application. The decision for a big-data project can be developed with the following model (Schwarz 2015, p. 48):

illustration not visible in this excerpt

Figure 1: Rough big data adoption strategy

This big-data adoption strategy model forms the basis for the third chapter of this paper. The first step is to gather information and planning. Therefore, the sales objectives will be stated. The second step contains the selection of data sources and that will be done in the next part of chapter three. The detailed planning will then be considered. Step 4, the implementation, and step 5, the operation & maintenance won’t be considered in this paper as they cover the technical part of a big-data strategy. A conclusion that answers the research question and gives a short forecast will terminate the paper.

2. Theoretical background

This chapter points out the theoretical background of the customer knowledge in sales according to the sales excellence approach and the related Information Management. In the next step it will be explained what big data and therefore its opportunities are, what a mobile shopping application is and what opportunities it offers. In addition the branch of department stores will be presented.

2.1 Customer knowledge in sales

The sales excellence approach is used to optimize sales activities. It covers 4 fields which are the Sales Management, the Sales Strategy, the Information Management and the Customer-Relation-Management. Information Management deals with the question if the necessary information for a professional sales work is available. The main focus is on customer-oriented information. Furthermore Information Management deals with the challenge to integrate all the information into a Customer-Relationship-Management (Homburg et al. 2012, p. 9–12). Due to the fact that a sales strategy should be oriented on the market conditions it is necessary to put the customer in the focus of the Sales Strategy (Homburg et al. 2012, p. 27, 31). Especially in commerce where a high complexity, that features the behaviour of customers, exists it is necessary to focus on the customer and to answer the question which information is needed about the customer and how to get the information. Therefore, a customer competence must be built up (Rudolph 2005, p. 67).

illustration not visible in this excerpt

Figure 2: Instruments of customer research (Rudolph 2005, p. 67)

A company can use various instruments for the collection of data which are differentiated in quantitative, qualitative and observing methods (Rudolph 2005, p. 68). The sales excellence approach differentiates the customer data in four categories that can be seen in the following figure:

illustration not visible in this excerpt

Table 1: Overview of central customer information (Homburg et al. 2012, p. 197)

The amount and the difference of information rise to the challenge of an effective coordination of information in commerce. With significant information a company has the chance to gain knowledge edge towards the competitors. Information Management coordinates relevant information and demonstrates promising actions (Rudolph 2005, p. 176). The information and data of a customer combined with recommendations and findings can lead to the customer insight which is “fresh and not yet obvious understanding of customer beliefs, values, habits, desires, motives, emotions or needs that can become the basis for a competitive advantage" (Kracklauer 2015, p. 63, 67).

In general a company that wants to increase its company value has two approaches: the rationalization and growth. Rationalization is about cutting costs or investments or raising prices. Growth can be done within existing customers, new customers, new businesses or with one-time customers (Doyle 2008, p. 11).

[...]

Details

Pages
23
Year
2016
ISBN (eBook)
9783668341883
ISBN (Book)
9783668341890
File size
925 KB
Language
English
Catalog Number
v344326
Institution / College
University of Applied Sciences Neu-Ulm
Grade
1,3
Tags
Vertrieb Big Data Sales Management Galeria Kaufhof Karstadt

Author

Share

Previous

Title: Big Data. Implementation of a big data based mobile application