Analysis of Adaptation Strategies and Optimization of Airbnb Listings in Bangkok: The Impact of COVID-19 on Ratings, Host Services, and Pricing

Developed by: Nabila Lailinajma

Overview

This project examines the impact of COVID-19 on Airbnb listings in Bangkok, focusing on guest ratings, host strategies, and pricing optimization. By analyzing property characteristics, traveler preferences, and seasonal trends, the study provides insights into how hosts can adapt to market shifts and enhance listing performance.

Background

Bussiness Understanding

The Airbnb marketplace in Bangkok, one of Southeast Asia’s most visited cities, has undergone significant changes due to shifting traveler preferences and external disruptions like the COVID-19 pandemic. While Airbnb provides opportunities for property owners to reach a global audience, hosts face challenges in maintaining high ratings, attracting guests, and optimizing pricing strategies.

One key issue is the variation in guest ratings across different areas of Bangkok, which raises questions about the influence of property characteristics and host performance. Additionally, the pandemic has led to shifts in traveler preferences, impacting the demand for certain types of accommodations and locations. Lastly, seasonal patterns play a critical role in shaping occupancy rates and revenue, requiring hosts to continuously adapt their marketing and pricing strategies.

This study aims to analyze these factors to provide insights into how Airbnb hosts in Bangkok can adapt and optimize their listings for better performance in a rapidly evolving market.

Problem Statement

1. Regional Rating Differences: How do property characteristics and host performance explain variations in ratings across different areas of Bangkok?

2. Changes in Guest Location Preferences: How has the COVID-19 pandemic influenced guests' choices of properties?

3. Shifts in Seasonal Trends: How have seasonal trends impacted Airbnb property marketing strategies in Bangkok before and after the COVID-19 pandemic?

Project Organization

├── readme.md                            <- The top-level README for developers using this project
|
├── data
│   ├── Airbnb Listings Bangkok.csv      <- The original, immutable data dump
│   ├── airbnb_cleaned.csv               <- The final, canonical data sets for analysis
│   └── data_additional.csv              <- The additional data sets for analysis
│
└── notebooks   
    └── 1.0-preprocessing.ipynb          <- Cleaning process before analysis
    └── 2.0-exploratory.ipynb            <- Additional, exploratory data sets before analysis
    └── 3.0-analysis.ipynb               <- Data sets analysis

Tableau Dashboard

https://s.id/Airbnb-Bangkok-COVID-Impact_Analysis-tableau

Powerpoint

https://s.id/Airbnb-Bangkok-COVID-Impact_Analysis-ppt

Contribution

Contributions are welcome! Feel free to suggest improvements, report issues, or submit pull requests on GitHub.