- Used Python to perform the basic Exploratory Data Analysis
- Used Tableau to perform Descriptive and the Diagnostic Analysis.
- Prepared two different PPTs using the Pyramid Principle keeping in mind the type of audience involved
- For detailed methodology, refer to the attached document - Methodology.doc
For the past few months, Airbnb has seen a major decline in revenue. Now that the restrictions have started lifting and people have started to travel more, Airbnb wants to make sure that it is fully prepared for this change. The different leaders at Airbnb want to understand some important insights based on various attributes in the dataset so as to increase the revenue such as:
- Which type of hosts to acquire more and where?
- The categorisation of customers based on their preferences.
- What are the neighbourhoods they need to target?
- What is the pricing ranges preferred by customers?
- The various kinds of properties that exist w.r.t. customer preferences.
- Adjustments in the existing properties to make it more customer-oriented.
- What are the most popular localities and properties in New York currently?
- How to get unpopular properties more traction?
To prepare for the next best steps that Airbnb needs to take as a business,we were asked to analyse a dataset consisting of various Airbnb listings in New York. Based on this analysis, we prepared two presentations to the following groups:
- PPT-1 was prepared for audience having basic technical knowledge - Data Analysis Manager, Lead Data Analyst etc.
- PPT-2 was prepared for audience from non technical background - Head of Acquisitions and Operations , Head of User Experience