An end-to-end Microsoft Excel data analysis project focused on understanding subscription trends, revenue, user engagement, demographics, retention, loyalty, payment preferences and regional behaviour of users on a streaming service platform.
The project uses Excel-based data analysis techniques to transform user-level data into interactive analysis, dashboards and business insights.
The objective of this project is to analyse streaming service user data and identify meaningful patterns across:
- 💰 Subscription & Revenue Trends
- 📺 User Engagement Metrics
- 👥 Demographic & Behavioural Insights
- 🔄 Retention & Loyalty
- 💳 Payment Preferences & Regional Trends
The analysis is designed to support better understanding of user behaviour and identify potential business opportunities.
The dataset contains user-level streaming platform information including:
- Subscription details
- Monthly revenue
- Watch activity
- Viewing preferences
- Device usage
- Loyalty metrics
- Demographic attributes
- Payment preferences
- Regional information
The analysis was performed using the supplied Excel dataset.
- Data Cleaning
- Data Preparation
- Calculated Columns
- Excel Formulas
- Pivot Tables
- Pivot Charts
- Slicers
- Conditional Formatting
- Dashboard Design
- Interactive Reporting
- Data Visualisation
- Business Insight Generation
DATEDIFCOUNTASUMAVERAGECOUNTIFIFIFERRORGETPIVOTDATA
The project followed a structured analytical process:
Data Cleaning → Data Preparation → Calculations → Pivot Tables → Slicers → Charts → Dashboard → Insights → Recommendations
Additional analytical columns were created for:
- Total Revenue
- Subscription Duration in Months
- Login Frequency
- Login Status
- Region
Subscription duration was calculated using DATEDIF.
For users where the last login date preceded the join date, the last day of December 2024 was used as the last login date for analysis.
Login status was classified into:
- Highly Active — login frequency less than 7 days
- Moderately Active — login frequency up to 30 days
- Inactive — remaining users
The project includes an interactive Streaming Services Dashboard containing key performance indicators, Pivot Table-based analysis, charts and slicers.
| KPI | Value |
|---|---|
| Total Users | 1,000 |
| Total Revenue | 118,162 |
| Average Watch Hours | 255 |
| Active Users | 1,000 |
| Active Users % | 100% |
The project analyses:
- Plan-wise total revenue
- Plan-wise monthly revenue
- User distribution by plan
- Plan-wise and country-wise revenue
- Subscription trends by country
- The 15.99 Premium plan generates the highest total revenue among the existing plans.
- The Premium plan also generates the highest monthly revenue.
- The 11.99 Standard plan has the highest number of users among the three plans.
- The USA has the highest number of users and generates the highest total revenue.
- India has the highest average subscription revenue.
The analysis was performed using Pivot Tables, slicers and charts. GETPIVOTDATA and IFERROR were also used to connect Pivot Table results with dashboard visualisations.
The project examines user engagement through:
- Watch hours by subscription plan
- Movies and series watched
- Language preferences
- Favourite genres
- Watch-time patterns
- Device usage
- Peak viewing periods
- The 11.99 Standard plan has more users and higher average watch hours than the other plans.
- Smartphone and Smart TV are the most-used first devices.
- Average watch hours are higher for Smartphone users than Smart TV users.
- Viewing behaviour varies across languages, genres and watch times.
- The peak watch time identified in the analysis is Late Night.
- Drama is the most watched genre during Late Night, followed closely by Documentary.
The analysis examines user behaviour across:
- Age groups
- Devices
- Genres
- Languages
- Watch times
- Viewing preferences
- Active devices
- The 55+ age group has the highest number of active devices.
- The 35–44 age group has the highest loyalty points.
- Device usage shows Smartphone and Smart TV as important engagement channels.
- Language and genre preferences provide useful indicators of viewing behaviour.
- Viewing patterns vary across age groups and preferred content.
The project analyses:
- Membership status
- Age-group-wise loyalty points
- Subscription duration
- Login frequency
- Content downloads
- The dataset contains 1,000 users, and all users are active based on subscription status.
- The 35–44 age group has the highest loyalty points.
- The 25–34 age group has the highest total subscription duration.
- Inactive users account for the highest number of content downloads and non-downloads based on the login-frequency classification.
The project analyses:
- Preferred payment methods by region
- Payment methods by country
- Country-wise user distribution
- Country-wise revenue
- Average subscription revenue
- Language preferences and watch hours
- PayPal is the most-used payment method.
- Europe has the highest PayPal usage.
- The USA has the highest number of users.
- The USA generates the highest total revenue.
- India has the highest average subscription revenue.
- Regional language and genre preferences provide useful inputs for content localisation.
The dashboard was created using Pivot Tables, Pivot Charts and Slicers.
Slicers allow the analysis to dynamically change based on selected dimensions such as:
- Monthly Plan
- Country
- Age Group
- Favourite Genre
- Watch Time
- Device
- Payment Method
GETPIVOTDATA combined with IFERROR was used to connect Pivot Table results with dashboard visualisations.
This enables dashboard tables and charts to dynamically respond to slicer selections.
- Premium plan generates the highest total and monthly revenue.
- Standard plan has the highest number of users.
- USA contributes the highest total revenue.
- India has the highest average subscription revenue.
- Standard-plan users demonstrate higher average watch hours.
- Smartphone and Smart TV are important engagement devices.
- Late Night is identified as the peak watch-time period.
- Drama and Documentary are prominent genres during Late Night.
- 35–44 age group has the highest loyalty points.
- 25–34 age group has the highest total subscription duration.
- Login frequency can be used as an indicator of user engagement.
- Early identification of inactive users can support retention initiatives.
- PayPal is the most-used payment method.
- Europe has the highest PayPal usage.
- USA has the highest number of users and total revenue.
- Regional language and genre preferences can influence content strategy.
Based on the analysis, the following recommendations were identified:
-
Optimise the recommended-content interaction engine to improve watch hours and retention.
-
Increase investment in series content, particularly considering the longer engagement cycles observed among younger age groups.
-
Prioritise Smartphone and Smart TV users, as these devices drive significant user engagement.
-
Enhance loyalty programmes to help reduce user turnover.
-
Target users differently based on watch time, device usage and age group.
-
Localise content offerings based on regional language and genre preferences.
-
Identify inactive users at an early stage to support retention initiatives and improve potential customer lifetime value.
excel-streaming-service-analysis/
│
├── README.md
├── Streaming_Service_Data_Analysis.xlsx
├── Streaming_Service_Analysis_Documentation.docx
│
├── 01-dashboard-overview.jpg
├── 02-subscription-revenue-analysis.jpg
├── 03-user-engagement-metrics.jpg
└── 04-retention-and-loyalty.jpg