Homework: Marketing Analytics
Part 1: Google Analytics and Tableau report
Select your own live website and present a live report of Google Analytics and Tableau using the data of the live website:
Data analytics method: explaining the machine-learning models and/or Google Analytics Details on Real-time Monitoring Report, Audience Analysis Report, Acquisition Report. Consumer Behaviour Report;
The analytics problems which you are going to solve, include
o Customer Profiling/Classification
o Target customers? Example: Who will buy Life Insurance?
o Customer Avatar/Profile, Example: Age, Gender, Race, Ed
o Customer Behavior Prediction
o Loan or not? Example: Will he default on this car loan?
o Buy or Not Buy? Example: Will she watch this movie?
o How many units/sales? Example: How many shoes to stock?
o Next-time buy? Example: When will she buy this Fish Oil again?
o Chun Problem? Example: (Y/N) When will she switch to Bell?
o Customer Service (Chatbot)? Example: How serve online better?
Part 2: Python
The soruces of your datasets can come from:
o KAGGLE Website
o Google dataset search
o Dataverse
o Open Data Kit
o Ckan
o Open Data Monitor
o Plenar.io
o Open Data Impact Map
o Smart City Open Dataset, including IoTs, Traffic, Transportation, Housing, etc (get source here)
o Google Analytics Dashboard (tool screenshot) (github source here)
o Sharing-economy Airbnb (github source here)
o Travel Website Analytics (github source here)
o Sports Club Analytics (github source here)
o Twitter and Elections (github source here
What needs to be done on Python
Data cleaning, explorative data analysis, and data visualization
Data cleaning, explorative data analysis, and data visualization
Clustering (minimum 1 tool, e.g., K-mean, K-NN)
Data analytics: Classification (minimum 2 tools: e.g. Linear, LR, SVM, ANN)
Project presentation PPT format:
I. Business problem: a clear business data problem statement which your project addresses.
II. Motivation: why is this data problem interesting and challenging or innovative to solve?
III. Data Visualisation approach: show your visualization results here.
IV. Data Analytics approach: demonstrate your Machine-learning models and/or Google Analytics and results here.
V. Conclusion and Future work: summarize key achievements and identify future work here.
Project submission files over UCW course portal
I. Project files: code, dataset, key outputs, performance matrix, to be compressed to a ZIP file;
II. Project presentation PPT:
III. Project final report (MS Word): your final project report should follow the APA style, including
i. Introduction: describing the business problem and the motivation to solve it;
ii. Relevant work: describing 5+ peer-reviewed papers related to your project with reference;
iii. Data and visualization: describing your dataset and show the data using visualization tools;
iv. Data analytics method: explaining the machine-learning models (minimum 1 clustering and 2 classifications) and/or Google Analytics Details on Real-time Monitoring Report, Audience Analysis Report, Acquisition Report. Consumer Behaviour Report;
v. Results: demonstrating the results of your data analytics models and visualize the data output;
vi. Discussion, Conclusion, and Future work;
vii. Reference list.
Format your homework according to the following formatting requirements:
i) The answer should be typed, using Times New Roman font (size 12), double spaced, with one-inch margins on all sides.
ii) The response also includes a cover page containing the title of the homework, the student's name, the course title, and the date. The cover page is not included in the required page length.
iii) Also include a reference page. The Citations and references must follow APA format. The reference page is not included in the required page length.