eCommerce

Forecasting swimsuit sales for the next month to assist in inventory management for Heatwave

Application Area: 

Project Details

Term: 

Fall 2018

Students: 

Jheng Kai-Ru, Adam Yu, Silvia Yang, Zoly Chang

University: 

NTHU

Presentation: 

Report: 

VIDEO

Heatwave is a swimsuit e-commerce seller on the Tmall.com. They designed and manufactured their swimsuits and sell them on the Tmall platform. In this project, our team collaborated with Heatwave to work on the forecasting job of predicting swimsuit sales for the next month to assist in inventory management.

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: 

Report: 

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

Forecasting AsiaYo’s One Month Ahead Daily Room Occupancy in Different Cities for Supply Preparation

Application Area: 

Project Details

Term: 

Fall 2018

Students: 

Sz Wei Wu (Sandy), Cheng Che Liao (John), Min Sheng Wu (Akira), Kai Wei Pai (Kelvin)

University: 

NTHU

Presentation: 

Report: 

VIDEO

In this project, we collaborate with AsiaYo, an online B&B booking platform company headquartered in Taiwan, to work together on solving their business problem by using forecasting methods. One challenge facing AsiaYo is the revenue lost when they are lack of available rooms on holidays or special peak periods. Considering the enterprise level and resource, we find that it will be more affordable and understandable to focus our solution of this business problem on certain popular areas.

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: 

Report: 

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

Predicting PicCollage users’ first purchase for targeted promotions

Application Area: 

Project Details

Term: 

Fall 2017

Students: 

Reggie Escobar . Eduardo Salazar Uni Ang . Lynn Pan

University: 

NTHU

Presentation: 

Report: 

PicCollage is an app to create amazing photo collages with custom stickers, fonts, background that makes creating collages a creative experience. It’s biggest revenue streams comes from In-app purchase where users could pay to remove watermark, add custom stickers, and backgrounds. Also the have popup ads; but because ads strategy is implemented different for Android and IOS users in this project the model is not using features extracted from ads behavior and the scope of the model proposed is directly extracted from the behavior when users create their first collage.

Identifying bookings with a high-risk of host rejection to improve customer service and customer satisfaction

Application Area: 

Project Details

Term: 

Fall 2017

Students: 

Arturo Heyner Cano Bejar, Tonny Kuo, Nick Danks, Kellan Nguyen

University: 

NTHU

Presentation: 

Report: 

AsiaYo! operates in a highly competitive industry serving as intermediary and agent between accommodation providers (hosts) and accommodation seekers (guests). High customer service is a critical business goal for AsiaYo!. Rejection of bookings by hosts can cause customer dissatisfaction and potentially loss of customers. Currently, AsiaYo! experiences a host rejection rate of 15% of orders. Rejection of a booking by the host triggers a reaction from the AsiaYo!

Forecasting ATM/CARD/CASH revenues for EZTABLE to identify potential and actual revenue

Application Area: 

Project Details

Term: 

Fall 2014

Students: 

ean Xie, Sam Wang, Lydia Jiang, Suneel Chatla

University: 

NTHU

Presentation: 

Report: 

The primary stakeholder is EZTABLE, an ecommerce based platform for reservations for different restaurants in Taiwan. Currently, there is a mismatch between the number of bookings and the amount of revenue generated by the bookings. The problem is the current booking system which enable the user to book reservations even without prior payment. Hence the actual revenue falls short of the potential revenue due to the existing system. The business goal of our project is to let our client realize the potential revenue and the need for changing the strategies.

Forecasting Daily Sales of Perishable Foods to reduce spoilage

Application Area: 

Project Details

Term: 

2012 (Dec)

Students: 

Akshat Chowdhary, Anushree Gandhi, Kashish Goyal, Ravdeep Chawla, Vaibhav Tripathi

University: 

ISB

Presentation: 

Report: 

Problem Description - Representing the hypermarket, the objective of our forecasting is to reduce the spoilage of vegetables in the hypermarket by accurately forecasting sales on a daily basis. By using historical data of the last year we plan to forecast daily demand for two SKU's 'Exotic Vegetables' and 'Beans' under the vegetable sub-class.

Determining optimum insurance product portfolio through predictive analytics

Application Area: 

Project Details

Term: 

2012 (Dec)

Students: 

Dinesh Ganti, Gauri Singh, Ravi Shankar, Shouri Kamtala, Supreet Kaur, Vinayak Palankar

University: 

ISB

Presentation: 

Report: 

Business Problem – An entrepreneur has an idea for a new business venture, which, in a nutshell, is to
offer insurance to customers on price drops of certain products. Registered customers get a certain
multiple of the insurance fee or a certain percentage of the drop provided that the drop happens within

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