Instagram Chat Analysis
Syed Fatik Islam
Data Scientist
Data Analyst
Product Data Analyst
Microsoft Power BI
pandas
Python
Project Description
This project involves the Instagram Chat Analysis for Star Fabrics, aimed at identifying key factors influencing customer engagement and sales conversions. The analysis reveals that Late Response and Pricing Issues are the primary reasons affecting customer satisfaction, accounting for a significant portion of interactions. Despite these challenges, the conversion rate from chats to sales is just 4.71%, and 71.09% of customers fall into the Low Engagement category.
By addressing these insights, the project provides actionable recommendations to improve response times, refine pricing strategies, and enhance overall customer engagement, driving better conversion rates and satisfaction levels.
Power BI Insights: 71% Low Engagement, 4.71% Conversion, Key Issues: Late Responses & Pricing
Key Deliverables
Insightful Visualizations:
Interactive dashboards highlighting reasons for non-conversion (e.g., Late Response, Pricing Issues).
Breakdown of customer engagement levels and their impact on conversion rates.
Data-Driven Insights:
Analysis of the root causes of poor engagement and low conversion rates.
Categorization of customers by engagement level (Low, Medium, High).
Actionable Recommendations:
Strategies to reduce response times and address pricing concerns.
Tactics to improve engagement for the 71.09% Low Engagement customers.
Scalable Data Pipeline:
An automated, Python-based data pipeline for processing chat data efficiently.
