Data Analysis Case Study

During my data analysis training, I analyzed an Airbnb Bangkok dataset from Kaggle to generate actionable business recommendations. Airbnb is an online rental platform connecting hosts with travelers seeking vacation accommodations. As of 2022, Bangkok was a top tourist destination globally, attracting 18.8 million visitors, compared to Paris (11 million) and Dubai (6 million). Additionally, Airbnb ranked among the top 5 travel applications used in Bangkok, suggesting a strong market position.

My task was to analyze the dataset and identify areas for improvement through comprehensive exploratory data analysis (EDA). Despite Airbnb's strong market position, Ansoff's marketing theory suggests that companies can use market penetration strategies for existing products in existing markets. Therefore, the problem statement focused on optimizing Airbnb's attributes to capitalize on Bangkok's growing tourism industry. This included improving product features, pricing strategies, and locations offered.

The first step in my analysis involved data cleaning, which included handling missing values, removing irrelevant features, and addressing outliers. Next, I utilized Python libraries like Pandas and Tableau to conduct initial analysis and identify potential trends. I also created visualizations to communicate findings and business patterns relevant to improvement opportunities.

Product analysis revealed that entire homes and private rooms were the most popular types, while shared rooms were rarely booked. Based on these insights, I recommended focusing marketing efforts on promoting entire homes and private rooms while enhancing the amenities offered in shared rooms to attract more guests.

Price analysis revealed significant inconsistencies. Listings within the same district often had similar amenities but varied greatly in price, with some being overpriced and others underpriced. This suggests that many hosts may be unaware of the appropriate pricing strategy for their rentals. To address this, I recommend encouraging or training hosts to utilize Airbnb Plus. Airbnb Plus provides valuable data and insights that can help hosts set competitive and accurate pricing for their listings.

To analyze location data, I identified several travel websites listing "places to visit in Bangkok." Combining and filtering their mentioned locations revealed the most popular tourist destinations. Further filtering by district identified four districts with high tourist appeal but limited Airbnb presence. These districts present significant potential for Airbnb expansion.

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