sql, python & power bi project
Website Analysis
ROLE
Data Analyst
OBJECTIVE
Improve Marketing Strategy
REQUEST
Comprehensive analysis
Online retail business, is aiming to address a decline in customer engagement and conversion rates despite increased marketing efforts. The goal of this project is to conduct a comprehensive analysis of the company’s marketing strategies and customer feedback to identify key areas for improvement. By analyzing the effectiveness of current campaigns, customer reviews, and social media comments, this project seeks to uncover insights that will guide optimization of marketing strategies and enhance customer satisfaction.
Key objectives include:
Identifying factors that negatively impact conversion rates and suggesting strategies to improve the conversion funnel.
Analyzing customer interactions with various marketing content to pinpoint the most effective content types and enhance engagement.
Examining customer feedback to uncover recurring themes, both positive and negative, that can inform improvements in product offerings and services.
This section outlines the step-by-step approach followed throughout the project, including data preparation, sentiment analysis, model building, and dashboard creation
1- Data Preparation and Cleaning (SQL):
Collected data from five datasets: Customers, Products, Customer Reviews, Customer Journey, and Engagement.
Utilized SQL to clean and preprocess the data, ensuring consistency and quality for further analysis.
SQL Scripts : View on GitHub🔗
2- Sentiment Analysis (Python):
Used Python to conduct sentiment analysis on customer reviews.
Leveraged libraries like Pandas, PyODBC, and NLTK to analyze text data.
Calculated the following sentiment attributes:
Sentiment Score: Numerical value representing the sentiment.
Sentiment Category: Classification into categories like positive, negative, or neutral.
Sentiment Bucket: Categorized sentiment score into defined buckets Range
Python Notebook : View on GitHub 🔗
3- Data Modeling and Dashboard Creation (Power BI):
Built the data model in Power BI by importing cleaned data and integrating it into a cohesive model.
Create a calendar table
Developed four interactive dashboards to visualize key metrics:
Overview Dashboard: High-level view of key performance indicators (KPIs).
Conversion Details Dashboard: Focus on conversion rates and analysis of customer journeys.
Social Media Details Dashboard: Insights from social media engagement.
Customer Reviews Details Dashboard: Sentiment analysis results and trends based on customer feedback.
Explore and Interact with the Dashboards and dive into it:
Explore Key Findings, Goals, and Actionable Insights for Optimizing Marketing Strategies