ANL-301 Business Analytics Term Project (Spring 2023)
In the term project, you will work in teams of up to three students. The team members will be assigned by the instructor randomly. Please go to People page on Canvas to learn your group members.
This assignment will provide you a learning experience of working in a team with random people. This will be a real-life experience to be expected when you graduate and start working – you do not get to choose who you work with. Please keep your mind open, as you may also make new friends with this project.
Working as a team, please keep the following in mind:
• Team members should meet to make sure the project moves with progress. • Before your FIRST meeting, all team members are expected to read the assignment and look
through the dataset. • Upon completion, team members will evaluate the contributions of each member to the group effort. The evaluations will be confidential.
You will apply what you have learned in this course to a real-world data problem. All teams will work on the same business case. The goal is to understand the problem domain and the data available to provide insight on analytical results. You will explore how best to use business analytics methods to transform data into business decisions and communicate of the results and insights from the analysis. You will use the techniques you learn in the following sections in the textbook:
• Chapter 1: Introduction • Chapter 2: Descriptive Statistics • Chapter 3: Data Visualization • Section 8.4: Using Regression Analysis for Forecasting • Section 10.3: Some Useful Excel Functions for Modeling
Other supporting resources are listed and linked on Canvas in the module “Project”.
You will prepare a short report (2-3 pages) to present the findings of your data analysis process and the conclusion. The report will include the tables and/or charts that you created in Excel. You will also submit the Excel file which includes your calculations, tables and/or charts.
The project will be evaluated based on two things: (i) the technical quality and significance of the work and (ii) the clarity and the quality of the report. Details can be found in the Rubric section.
Page 2 of 3
THE BUSINESS CASE
Cross-buying refers to customers buying additional products from the same firm – for example, when a customer starts a relationship with a bank, opens a savings account, and one year later opens a checking account. Financy, one of Germany’s largest financial services providers, would like to run a cross-sell campaign and incentivize customers who do not yet have a checking account to open one. Thereby, the firm must concentrate its
marketing efforts on customers who are more likely to cross-buy and open a checking account. Also, the firm wants to better understand customer behavior (Balance, Number of Products, Complaints) across different customer segments based on socio-demographics.
The file Cross-Buy.xlsx contains data on 1,000 customers of Financy. The dataset contains 16 variables that describe customer demographics, transactions, activities, and the firm’s marketing efforts. The variables are defined below.
1 Cross-buy Customer opened a checking account: 1 (yes), 0 (no) 2 Age Customer’s age in years 3 Gender Customer’s gender: 1 (male), 0 (female) 4 Marital Status Customer marital status 5 Occupation
6 Giro Mailing Received an email about opening a checking account: 1 (yes), 0 (no) 7 Direct Mailing Total number of mailing in the last year 8 Complaints Number of complaints in last year 9 Customer Tenure Number of months since customer onboarding 10 Desktop Logins Number of logins in the last 180 days 11 Mobile Logins Number of mobile sessions in the last 180 days 12 Number of Products Total number of products (accounts) owned by the customer 13 Balance Total balances of all savings accounts (€) 14 House Size Average number of households per building in the residential block 15 Purchase Power Average purchase power in the residential block 16 Share of New Houses Share of new buildings in the residential block
1. Understand the data: What are the data types (Quantitative, Categorical or Other) of each variable in this dataset? Clean and prepare your data for analysis. Define new variables, if necessary.
Page 3 of 3
2. Define four specific objectives of your analysis. The objectives can be defined based on what you want to do with data and what sparks your interest. Some examples can be:
o a business question to answer o to explore a relationship between some variables o to examine a variable’s distribution among different groups o to identify some interesting values o …
3. Apply appropriate business analytics techniques (sort, filter, conditional formatting, numerical summaries, crosstabulations, charts, regression, etc.) to explore the dataset based on your objectives. You have a lot of freedom to choose what to do, as long as you reach your objectives and restrict yourselves to exploratory techniques (rather than forecasting, simulation, or optimization approaches).
4. Present your analysis and findings in a report. Also, provide business actions/decisions for Financy based on your findings.
5. Submit your Excel file and your report (pdf or Word) on Canvas.
(90-100 points) Very Good
(75-90 points) Adequate
(50-75 points) Unsatisfactory (0-50 points)
Well-motivated, interesting, and insightful objectives
Objectives have two of the three qualities: well-motivated, interesting, and insightful
Objectives have one of the three qualities: well-motivated, interesting, and insightful
Objectives are overly simplistic, unrelated, or unmotivated
Accurate, appropriate, and advanced analysis
Analysis has two of the three qualities: accurate, appropriate, and advanced
Analysis has one of the three qualities: accurate, appropriate, and advanced
Choice of analysis is overly simplistic or incomplete
Conclusions and Business
Relevant, insightful, and well-supported conclusions
Conclusions have two of the three qualities: relevant, insightful, and well-supported
Conclusions have one of the three qualities: relevant, insightful, and well-supported
Conclusions are overly simplistic or incomplete
Attractive, well- organized, well- written project report
The project report has two of the three qualities: attractive, well-organized, well-written
The project report has one of the three qualities: attractive, well-organized, well- written
The project report has none of the three qualities: attractive, well- organized, well- written