This project focuses on analyzing Netflix user data to uncover demographic and usage patterns, calculate key metrics such as Lifetime Value (LTV), and provide actionable insights based on various attributes, including age, country, device usage, and subscription types. The analysis offers recommendations for targeted marketing, user retention, and platform optimization.
- Understand Demographics: Analyze user distribution across various countries, genders, and age groups.
- Device Usage Insights: Examine how users access Netflix (Laptop, Tablet, Smartphone, Smart TV).
- Subscription Patterns: Break down subscription types and identify opportunities for plan upgrades.
- Calculate Lifetime Value (LTV): Determine the LTV per user and country to inform strategic decisions.
- Provide Recommendations: Offer insights on marketing, user retention, and product optimization based on the analysis.
The dataset contains the following columns:
User ID
: Unique identifier for each user.Subscription Type
: Type of subscription plan (Basic, Standard, Premium).Monthly Revenue
: Monthly revenue generated by each user.Join Date
: Date the user joined Netflix.Last Payment Date
: Date of the last payment made by the user.Country
: User's country of residence.Age
: Age of the user.Gender
: Gender of the user.Device
: Primary device used (Smartphone, Tablet, Smart TV, Laptop).Plan Duration
: Duration of the subscription plan.
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Number of Users per Country:
- United States and Spain have the highest user counts, with 451 users each.
- Other significant countries include Canada, the UK, Australia, Germany, France, Brazil, Mexico, and Italy.
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Gender Distribution:
- Gender distribution is nearly equal, with 50.28% female users and 49.72% male users.
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Device Usage:
- Laptops, Tablets, Smartphones, and Smart TVs show a relatively even distribution of use.
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Subscription Types:
- Basic: 39.96% of users
- Standard: 30.72% of users
- Premium: 29.32% of users
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Age Distribution:
- Mean Age: 38.8 years, Median Age: 39.0 years
- Most common ages: 30 and 39 years old
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Lifetime Value (LTV):
- The highest total LTV is in the United States, followed by Spain, Canada, and France.
- France and the UK have the highest average LTV per user, making them key regions for premium offerings.
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Focus on High-LTV Countries:
- Target marketing and retention strategies in the US, Spain, France, and the UK.
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Gender-Specific Campaigns:
- Create inclusive content to appeal to both male and female users equally.
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Device Optimization:
- Ensure the platform is optimized for all devices (Laptops, Tablets, Smartphones, Smart TVs).
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Subscription Upgrades:
- Encourage Basic users to upgrade to Standard or Premium plans through targeted promotions.
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Future Analysis:
- Perform deeper analyses on user behavior, content preferences, and regional trends.
- Python: Data analysis and visualization
- Jupyter Notebook: Execution environment
- Pandas: Data manipulation and analysis
- Matplotlib/Seaborn: Data visualization
This project provides valuable insights into Netflix's user base, helping identify opportunities for growth through targeted marketing, device optimization, and subscription plan promotions. By leveraging these insights, Netflix can further enhance user satisfaction and maximize revenue.
- Clone this repository to your local machine.
- Install the required dependencies:
pip install -r requirements.txt
- Open the Jupyter Notebook and run the analysis.