Sentiment Analysis Case Study

The Background

CouchPotato Couriers, a unique delivery service known for its relaxed and humorous approach to deliveries, places a high priority on ensuring that customers can truly “sit back and relax.” As they continue to grow, they recognize the importance of understanding customer sentiments to enhance their service and maintain a lighthearted customer experience. To maintain their unique and fun approach while ensuring service excellence, they need to gauge customer sentiments accurately and act on feedback to address concerns. You are an experienced data analyst working for CouchPotato Couriers, so you enthusiastically volunteer to analyze customer feedback data. Unfortunately, the data is not labelled, but since you are an experienced data analyst, that should not be a problem.

The Data

Along with this write-up, you should have received one dataset:

1. cc_customer_feedback.csv

This dataset contains feedback from 674 customers from the month of October 2023. This dataset contains two columns, one column containing the feedback text and the other containing the date.

The Case Study

Your manager has given you the following task:

1. Perform exploratory analysis to provide insights into the data.

2. Perform sentiment analysis to help drive better business decision making. In particular, your manager wants

to know:

a. What is the overall sentiment for our organization?

b. How has the sentiment changed over time?

c. Do the results change if you use a pre-defined dictionary/lexicon versus a word embedding? (Note: to

use a word embedding, you will need to manually label some observations to build a predictive model.). Note: Undergraduate students only need to use a dictionary/lexicon. Graduate students must use a dictionary/lexicon and a word embedding.

3. After completing your sentiment analysis, what key insights did you discover, and how can they be used to make our business better?