Predicting customer churn for targeting promotions for a traditional taxi company in Vietnam

Application Area:

Project Details

Term:

Fall 2019

Students:

Meng-Hen Huang, Sammi Yien Lu, Viet-Cuong Trieu (Daniel), Xin Wang

University:

NTHU

Presentation:

Team 8 Slides Mai Lingh Vietnam Taxi Customer Churn.pdf

Report:

Team 8 Report Mai Lingh Vietnam Taxi Customer Churn.pdf

Predicting Customers' Purchase Tendency for Precision Marketing to Increase Migo’s Revenue

Application Area:

Project Details

Term:

Fall 2019

Students:

Shao-En Lin, Hsuan-Yu Chen, Tzu-Hung Lin, Wan-jung Tsai

University:

NTHU

Presentation:

Team 7 Slides Migo Precision Marketing.pdf

Report:

Team 7 Report Migo Precision Marketing.pdf

Finding the most likely repurchasing customers next month: For targeted promotions

Application Area:

Project Details

Term:

Fall 2019

Students:

Rona Lu-Lai, Vivian Lu, Joanne Hsueh, David Hung

University:

NTHU

Presentation:

Team 6 Slides MeCome Targeted Promotions.pdf

Report:

Team 6 Report MeCome Targeted Promotions.pdf

Business Problem

Predicting customers' health supplement purchase propensities for precision marketing at MeCome pharmacy

Application Area:

Project Details

Term:

Fall 2019

Students:

William Feng, Silvia Yang, Vivian Lee, Thompson Lin

University:

NTHU

Presentation:

Team 5 Report MeCome Health Supplement Purchase.pdf

Report:

Team 5 Report MeCome Health Supplement Purchase.pdf

Predicting second trip from new registered user of WeMo to increase marketing effectiveness

Application Area:

Project Details

Term:

Fall 2019

Students:

Young He, Kai Ru Cheng, Ting Wei Chen, Ni Wei Jin

University:

NTHU

Predicting Conversion of Free Trial Users to Paying Customers to Increase Sales by Developing an Effective Free Trial Program

Application Area:

Project Details

Term:

Fall 2019

Students:

Chawisa Mahajindaplan, Thuc Han Bui, Jariya Tienmongkol, Ryjill Roa

University:

NTHU

Presentation:

Team 3 Slides Migo Conversion.pdf

Report:

Team 3 Report Migo Conversion.pdf

Migo is a digital company that utilizes satellite technology to serve digital contents to consumers who live in urban areas that have limited data connection due to high internet prices and find it too expensive to subscribe to the existing streaming services in the market.

Capturing High Value Customers among Migo’s Newly Registered Users for Conducting Precision Marketing

Application Area:

Project Details

Term:

Fall 2019

Students:

Bill Bennett, Wen‐Teng Chang, Yu‐Ting Lin, Tzu‐Lun Lin

University:

NTHU

Presentation:

Team 2 Slides Migo Precision Marketing.pdf

Report:

Team 2 Report Migo Precision Marketing V2.pdf

Predict last-minute give-up rentals to reduce operating loss for WeMo Scooter

Application Area:

Project Details

Term:

Fall 2019

Students:

Will Kuan, Beverly Lin, Adam Yu, PeiPei Chen

University:

NTHU

WeMo Scooter is an e-scooter sharing company that provides urban transportation solutions by convenient, economic, free and interesting riding experiences. WeMo offers an app as an interface for users to find, reserve, rent, and turn on/off an e-scooter easily.

Forecasting the daily traffic from Facebook fan page to content website for TC Incubator

Application Area:

Project Details

Term:

Fall 2018

Students:

Sam Kuo, Astro Yan, Serina Hung, Jay Lee

University:

NTHU

Presentation:

Slides.pdf

Report:

FInal Project Report.pdf

TC Incubator is dedicated to strengthening youth innovation, focusing on helping entrepreneurs by providing consultants. TC also operates an official information website
called "Jinrih Deliver", which promotes and attracts users to the official website by managing

Predicting Loyal Customers for Sellers on Tmall to Increase Return on Promoting Cost

Application Area:

Project Details

Term:

Fall 2017

Students:

Wendy Huang, Yu-Chih Shih, Jessy Yang, Zoe Cheng

University:

NTHU

Presentation:

Team 9 Presentation Tmall Loyal Customers.pdf

Report:

Team 9 Tmall Loyal Customers.pdf

Sellers on E-commerce platform sometimes run big promotions (e.g., discounts or cash
coupons) on particular dates (e.g., Boxing-day Sales, "Black Friday" or "Double 11 (Nov 11th)”, in
order to attract a large number of new buyers. Unfortunately, many of the attracted buyers are
one-time deal hunters, and these promotions may have little long lasting impact on sales. To
alleviate this problem, it is important for sellers to identify who can be converted into repeated

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