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 analysis 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.
Table of Contents
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
Objectives & Research Focus
This paper examines how the implementation of a big data-based mobile application can enhance a department store's sales manager's ability to increase profit by leveraging consumer data for targeted marketing and operational optimization.
- Analysis of the potential of big data in the context of mobile shopping applications.
- Evaluation of customer data tracking and analysis methodologies.
- Identification of activities for sales managers to support marketing goals and improve sales performance.
- Assessment of the specific relevance for German department stores such as Galeria Kaufhof and Karstadt.
Excerpt from the Book
3.2 Tracking data
Before the activities that can be implemented through the data of a big data based application, the relevant data and information must be tracked, concerning the necessary data of customers which were outlined in chapter 2.1. The basic data, who a customer is, can be detected within the registration to the app. A customer has to insert his or her gender, name, birthday, mail, telephone number and address. Further can be asked for preferences of the customer to get to know which are important sections in the department store and if he has preferences for brands. The Bluetooth technologies and the GPS technology offer the possibility to get to know when a customer enters a store, which way he walks through the store, how long he stands at which shelf or section and when he leaves the store as well as the information how often he visits the store. In addition, the app gets to know wherever a customer is at any time using the GPS if the customer allows the app to track this information. Offering a point system for the list of purchased products it will be known which products in which amount a customer buys. Having the opportunity to enter a shopping list at the app it can be compared what is planned to be bought and what the customer really bought. The IBeacon technology of Apple detects when a customer is passing by the installed IBeacon in the store. With a save option to notice special offers, products or shops it will be known what preferences a customer has and it also can be compared if he really makes use of them. Providing the option to enter information from the customer or even a real-time chat the company offering the app gets deeper insight information of, for example, complaints, dissatisfaction or wishes. Through a bar-code or QR-code scanner function that offers deeper product information it can be seen in which products a customer is interested or which products are unclear.
Summary of Chapters
1. Introduction: This chapter defines the significance of Big Data in the modern digital age and establishes the research question regarding the profitability of mobile shopping apps.
2. Theoretical background: This section provides a conceptual foundation covering sales excellence, the definition of big data, and the role of mobile shopping applications in retail.
3. Potential for Sales Managers: This chapter details the sales objectives, the methods for tracking and analyzing customer data, and actionable strategies for sales managers.
4. Conclusion & Forecast: The final chapter summarizes the findings, addresses the challenges for department stores, and provides a future outlook on digital retail trends.
5. Bibliography/Reference list: A comprehensive list of academic sources and industry studies used to support the analysis.
Keywords
Big Data, Sales Management, Mobile Shopping Applications, Department Stores, Customer Insights, Profitability, Retail Strategy, Digital Change, Marketing, Data Analysis, IBeacon, Shopping Experience, Consumer Behavior, Smart Data, Sales Objectives.
Frequently Asked Questions
What is the core focus of this research paper?
The paper focuses on the potential for sales managers in German department stores to utilize data generated by mobile shopping applications to drive profit and improve customer engagement.
What are the central thematic areas?
The main themes include Big Data analytics, mobile commerce integration, retail management, and the specific application of customer data to optimize in-store sales policies.
What is the primary research question?
The research asks: Does the implementation of a big data based mobile application enhance a department store’s sales manager’s possibilities to increase profit?
Which scientific method is applied?
The author uses a theoretical-conceptual analysis to evaluate how data from mobile applications can be translated into actionable marketing and management strategies.
What does the main body cover?
The main body details the theoretical background of sales excellence, describes technical tracking methods like GPS and IBeacon, and outlines specific activities to achieve sales objectives.
Which keywords best characterize this work?
The work is characterized by terms such as Big Data, Mobile Shopping Applications, Sales Management, and Customer Insights.
How do Galeria Kaufhof and Karstadt differ in their approach?
The analysis notes that the companies have distinct strategies; Galeria Kaufhof focuses on a younger, service-oriented customer, while Karstadt tends to target an older demographic, affecting the applicability of app-based solutions.
What is the role of the "Big-data adoption strategy model"?
This model serves as the logical framework for the third chapter, guiding the process from initial information gathering and planning to data source selection.
What future scenarios are mentioned in the forecast?
The author highlights the potential for future integration of mobile payment systems and the "renting instead of buying" business model within shopping apps.
- Citar trabajo
- Miriam Kröner (Autor), 2016, Big Data. Implementation of a big data based mobile application, Múnich, GRIN Verlag, https://www.grin.com/document/344326
