Airbnb CRM Data Case

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.

Executive Summary

Exploratory Data Analysis

The number of listings rose rapidly before dropping gradually from 2016.

Most popular and expensive listings are located near the beach.

Psycho-Linguistic Analysis Measured by LIWC

There is a positive correlation between scores and tone. However, the correlation coefficient is 0.36 (not strong).

The original rating tends to be higher than the tone, indicating that the validity of the model is not very reliable.

The reviews tend to be positive, more analytical and confident. However, they are likely to be guarded.

Cleanliness and Value are the most influential variables for the overall rating.

Overall, these metrics are gradually increasing since 2015. Most listings excel in Check-in and Communication and need to work on Cleanliness and Value.

Anger and Anxiety tend to be low (below 0.5 out of 1), with the average score of anxiety generally being higher than anger.