Project Experience

Based on the data analysis result to provide marketing strategies for Airbnb. Responsible for building the Airbnb brand and getting, keeping, and developing customers by creating social media content. You’re using your expertise in social media. This includes everything from understanding the voice of customers and creating content relevant to the company brand to promote in the digital space and create a better customer experience. Analytical tools being used are LIWC, sentiment analysis and topic modelling.

The goal of this business case is to develop a digital waste retribution application called SampahID (WasteID) to address the problem of waste management in Indonesia.

This project received the top 5% score of The University of Sydney Business School Creative and Analytical course (BUSS5221) and was invited to join the MARD Competition.

Supported Screen Australia to analyse their data and provide strategies to improve revenues based on model training results.

Marketing analysis through Twitter and TV Viewership data to explore insight. Methods being used: Feature Engineering, Sentiment Analysis, and Topic Modelling. At the end of the report, it provided recommendations based on the result.

Model training to explore why the audience was interested in Sydney Swans and AFL. Analysed the members’ connection with AFL and Sydney Swans.

According to the Exploratory Data Analysis to decide how to do data processing and feature engineering. The data spreadsheet was mainly a classification data type. This report used different model training methods, for example, LINEAR, TREE-BASED and STACK models. Based on the model with the best performance, providing a recommendation for those two companies.