Project Overview

This Airbnb Market Intelligence & Pricing Analytics project was developed as a complete data analytics solution to transform raw Airbnb listing data into actionable business insights. The project covers the entire analytics lifecycle, starting from data collection and ending with interactive business intelligence reporting.

The process began with web scraping Airbnb-related data from multiple sources, followed by extensive data cleaning, preprocessing, and exploratory data analysis (EDA) using Python. Statistical analysis was performed to understand pricing distributions, listing characteristics, guest satisfaction patterns, and market behavior across different European cities.

To support scalable analysis, a complete relational database was designed and implemented. The database development phase included requirement analysis, entity relationship diagram (ERD) design, schema creation, data loading, SQL querying, and query optimization techniques to ensure efficient data retrieval and analytical performance.

The analytical layer focuses on understanding Airbnb market performance through key metrics such as average nightly price, listing volume, guest satisfaction scores, room type distribution, and geographic market coverage. Additional analysis was conducted to compare pricing behavior across cities, countries, weekdays, weekends, and accommodation categories.

A dedicated pricing simulation module was also developed to evaluate the potential impact of price adjustments on market positioning and customer satisfaction. Using dynamic what-if parameters, users can test different pricing scenarios and immediately assess their influence on average prices and satisfaction indicators.

The final reporting solution was built in Power BI using a structured data model, DAX measures, interactive filters, geographic visualizations, and advanced analytical dashboards. The report enables users to explore market trends, identify pricing opportunities, compare city-level performance, and support data-driven business decisions.

Overall, this project demonstrates the complete journey from raw web data collection to database engineering and business intelligence, transforming large-scale Airbnb data into a comprehensive decision-support platform for pricing strategy and market analysis.