• Created a Google Form to collect feedback and ratings from customers and store in Google Sheets • Developed a Python code to fetch feedback and perform sentiment analysis using NLTK in Python and push data to AWS RDS MySQL • Designed a Dashboard using Power BI that fetches data from AWS RDS MySQL to monitor sales, ratings, sentiment scores, perform sales forecasts of various products and product categories with drill down features

1. Product Rating Monitoring System
1
Collect
•Collect Feedback from Customers on
Various Products
2
Process
•Process the collected information and
Perform Sentiment Analysis
3
Present
•Present the feedback on a Dashboard
which gives a high-level overview to
Managers

2. Concept
• A Product Feedback Monitoring system that
continuously keeps track of the ratings &
reviews for every product from every category.
• The system is designed in such a way that it is
easy to collect feedback from customers and
the whole process of managing data to pushing
data to the dashboard is totally automated.
• Feedback is collected by Google forms and the
data is stored in Google sheets.
• Python fetches new feedback, performs data
pre-processing, sentiment analysis and pushes
data to AWS RDS MySQL server.
• Power BI fetches data from MySQL server and
displays data on a dashboard. The Python Code
and Power BI are scheduled to run and fetch
new feedback once everyday.

3. Initial Technology End
Data Collection
Use Google Forms to Collect Data in the form of
Surveys from Customers and Store in Google Sheets
Data Processing, Storage and
Management
Python Fetches data from Google Sheets to a pandas
dataframe and performs sentiment analysis using
nltk
The data with sentiment analysis is pushed to AWS
RDS MySQL Database
Data Visualization
The dashboard is created using Power BI and new
data is automatically fetched with scheduled refresh.
The processed data is presented on Power BI
Dashboard which can be viewed anywhere across
the globe on Desktops, Laptops and Mobiles.

4. Workflow

5. Manager’s
View

6. Manager’s
View

7. Manager’s
View

8. Manager’s
View
• The Manager can quickly get to know the
average rating of the product and the number
of ratings.
• The dashboard has KPI’s for Average Rating for
every product category.
• The Average Rating and the number of reviews
for every product are provided in the table. The
dashboard provides slicers to drill into the
timeline or specific product/product category.
• The forecast of sales, average rating of
products.
• The sentiment score of products, word cloud,
comments to understand the product’s
performance in market.