NAME OF THE MODULE: INTRODUCTION TO BUSINESS ANALYTICS AND
INTELLIGENCE (BUSI49150)
TITLE: WIRKKALA CUSTOMER ANALYSIS TO SUPPORT DATA-DRIVEN
DECISION MAKING FOR THE LAUNCH OF NEW AD CAMPAIGN
NAME: NIKHIL ANIL GANGURDE
DATE OF SUBMISSION: 19 FEBRUARY 2023
WORDCOUNT: 2950
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,Table of Contents
1.0 EXECUTIVE SUMMARY.....................................................................................................................3
2.0 INTRODUCTION................................................................................................................................4
3.0 BACKGROUND..................................................................................................................................5
3.1 Background to the Case Study.....................................................................................................5
3.2 Structure of the Data...................................................................................................................6
3.3 Transforming/Cleaning Data........................................................................................................8
4.0 DATA ANALYSIS AND RESULTS.........................................................................................................8
4.1 Customer Demographics..............................................................................................................9
4.2 Customer Segmentation............................................................................................................11
4.3 Regional Analysis.......................................................................................................................15
4.4 Discussion..................................................................................................................................16
5.0 RECOMMENDATIONS....................................................................................................................17
6.0 REFERRENCES.................................................................................................................................19
7.0 APPENDICES...................................................................................................................................20
Appendix a: Confidence Interval Calculations for Monetary Value..................................................20
Appendix b: RFM Measures of Central Tendency, Dispersion and Confidence Intervals.................20
Appendix c: Amount Purchased, Sum of Total and Average of Total Paid per Month.....................21
Appendix d: 2020 Sales by Region and Month.................................................................................21
Appendix e: Most Purchased Items.................................................................................................22
Appendix f: Calculations to Determine RFM Segment Eligibility Criteria.........................................22
Appendix g: RFM Segment Eligibility Criteria...................................................................................23
Appendix h: RFM Value Criteria to Determine Customer Segment.................................................23
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, 1.0 EXECUTIVE SUMMARY
This business research examines the Wirkkala 2020 Detailed Customer Database, which
includes a sample of the company's client base from both of its shop facilities in the
Midlands and London. Based on recentness, frequency, and monetary values, clients
were divided into four categories using customer relationship management strategies.
The qualifying requirements for each of the segments were developed using measures of
dispersion as well as central tendency. A definition of RFM analysis is given, along with
information on how it may be used to determine which clients are the most valuable
based on their purchasing patterns. The RFM approach was used to analyze the
company's customer data, and the results are then presented in the report.
Understanding these distinct client categories' habits and dynamics will help Wirkkala
make data-driven decisions. The data was processed before analysis using adequate
data cleaning and converting procedures, all of which are described in this paper.
Insights from this dataset were gained using statistical and descriptive analytic
techniques. Examples of data visualization were also provided to help Wirkkala
managers; these examples included valuable data to support managerial business
choices on their business operations and addressed their main research questions. The
report makes suggestions based on the research and assessment, with a strong
emphasis on the age, gender, and geographical differences between the client
categories, for potentially improving the chance of responses as well as grade of leads
for focused marketing campaign.
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