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An Analysis of the First Time Booking Patterns
- 1. An Analysis ofthe First Time Bookings of Airbnb Users Brian O Conghaile 11311151 Patrick Leddy 08370231 Niamh Ryan 11307801
- 2. Airbnb • Founded in2008 • Major Growth • Market Leader • Both a Platform and a Service • Over 2 million listings worldwide
- 3. Objectives 1. Main Objective:Location of Booking 2. Social Media Trends 3. Seasonal Trends
- 4. Our Data • 5original datasets: • Training Set (213451x16) • Test Set (62096 x 15) • Sessions (10,567,737 x 6) • Age Brackets • Countries
- 5. Data Cleansing andDummy Variables • Merging of sessions dataset with training set and with test set • Dealing with the missing data • Creation of the dummy variables
- 6. Initial Understanding ofData • Social Media Trends : 0 Google 1 Facebook 2 Basic 3 Weibo
- 7. Initial Understanding ofData • Seasonal Trends • Time Series Analysis of 2014 Bookings
- 8. Tools and Techniques •Excel and XLMiner: • Creation of Dummy Variables • Nested IF Statements • MLR • Neural Networks • ArcGIS Maps • MiniTab: • Time Series Analysis Plot
- 9. 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)
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- 11. Earlier Models • DecisionTree : • Party package • RPart package
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- 13. Findings Country Expected UserBookings 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
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- 15. Conclusion • Limitations ofData Available • Our Result vs Competition Winner (87.248%) (88.697%)