An Analysis of the First Time Booking Patterns

An Analysis of the First Time Bookings of Airbnb

UsersBrian O Conghaile 11311151Patrick Leddy 08370231Niamh Ryan 11307801

Airbnb• Founded in 2008

• Major Growth

• Market Leader

• Both a Platform and a Service

• Over 2 million listings worldwide

Objectives1. Main Objective: Location of Booking

2. Social Media Trends

3. Seasonal Trends

Our Data• 5 original datasets:• Training Set (213451x16)

• Test Set (62096 x 15)

• Sessions (10,567,737 x 6)

• Age Brackets

• Countries

Data Cleansing and Dummy Variables

• Merging of sessions dataset with training set and with test set

• Dealing with the missing data

• Creation of the dummy variables

Initial Understanding of Data• Social Media Trends :

0 Google

1 Facebook

2 Basic

3 Weibo

Initial Understanding of Data• Seasonal Trends• Time Series Analysis of 2014 Bookings

Tools and Techniques• Excel and XLMiner:• Creation of Dummy Variables• Nested IF Statements• MLR• Neural Networks• ArcGIS Maps

• MiniTab:• Time Series Analysis Plot

Tools and Techniques• RStudio• Decision Trees• XGBoost• randomForest• SVM (Support Vector Machine)• Dimensionality Reduction Algorithms• Naïve Bayes• KNN (K Nearset Neighbour)• K Means• MLR (Multiple Linear Regression)

Association Between Variables

Earlier Models• Decision Tree :• Party package

• RPart package

XGBoost

FindingsCountry Expected User Bookings

Australia 552

Canada 802

Germany 662

Spain 883

France 1359

Great Britain 951

Italy 1041

Netherlands 723

Portugal 514

United States of America 13885

Other 3008

No Booking 37716

Findings

Conclusion• Limitations of Data Available

• Our Result vs Competition Winner (87.248%) (88.697%)