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📊 Customer Journey Analytics Dashboard – Power BI Project

1. Project Overview

The Customer Journey Analytics Dashboard is designed to help businesses understand how customers interact across different touchpoints—from first contact to repeat purchase. The dashboard provides insights into customer behavior, conversion performance, churn patterns, and satisfaction levels. Using Power BI, this project transforms raw customer interaction data into a visual, interactive analytics tool for data-driven decision-making.

2. Project Objectives

Track and visualize the end-to-end customer journey.
Identify drop-off points and stages with low conversion.
Measure engagement and retention trends.
Analyze customer satisfaction through NPS, feedback, and CSAT scores.
Segment customers based on demographics, behavior, and spending.
Provide actionable insights for improving marketing, sales, and support processes.

3. Data Sources

Typical datasets used:
Customer Demographics
Customer ID, Age, Gender, Region, Membership Tier
Marketing Interactions
Campaign ID, Channel (Email, Social, Web), Clicks, Impressions
Website/App Behavior
Page Views, Session Duration, Repeat Visits
Sales Transactions
Order ID, Items, Amount, Purchase Frequency, Date
Customer Support Data
Tickets, Resolution Time, Issue Type, Satisfaction Rating
Feedback/NPS Surveys

4. Data Preparation in Power BI

Data cleaning: handling missing values, removing duplicates
Data transformation using Power Query
Date table creation with DAX
Relationship modeling:

1-to-many relationships between Customer → Orders, Customer → Support Tickets, etc.

DAX Measures:
Total Revenue
Funnel Conversion %
Customer Lifetime Value (CLV)
Customer Retention Rate
Average Resolution Time
NPS Score

5. Key Dashboard Features

A. Customer Journey Funnel
Awareness → Engagement → Consideration → Purchase → Retention
Conversion % at each stage
Drop-off rate between stages

B. Customer Segmentation

Demographics (Age, Gender, City)
Behavioral (Engaged, At-risk, New, Loyal)
Purchase value segments (Low, Medium, High spenders)

C. Sales & Revenue Insights

Monthly revenue trend
Repeat vs first-time buyers
CLV distribution

D. Engagement Analytics

Website session trends
Campaign performance
Response rate by channel

E. Support & Satisfaction

Ticket volumes
Average resolution time
Customer satisfaction (CSAT)
NPS and feedback text analysis

6. Dashboard Pages (Recommended Layout)

Overview
High-level KPIs, customer funnel summary
Customer Insights
Segments, demographics, behavior patterns
Sales & CLV Dashboard
Revenue, lifetime value, repeat purchase trends
Engagement & Marketing
Campaign performance, website behavior
Support & Satisfaction
Tickets, CSAT, NPS, sentiment analysis

7. Tools & Technologies

Power BI Desktop
Power Query
DAX
Excel / SQL Server (if needed for data source)
Power BI Service (for publishing and sharing)

8. Business Impact

Improved targeting of marketing campaigns
Reduced customer churn
Enhanced customer experience
Better sales forecasting
Data-backed decision-making for customer success teams