Netflix Content Strategy Analysis

Problem Statement

With intense competition in the streaming market, understanding user behavior and content performance is essential for data-driven decision-making. This project aims to analyze Netflix’s 2023 content data to uncover trends in user engagement, language preferences, seasonal patterns, and strategic release planning.

Project Goal

To conduct an in-depth analysis of Netflix content performance based on viewership hours, release timing, language, and content type. The objective is to derive actionable insights to inform content strategy and release decisions.

Key Features

• 📊 Exploratory Data Analysis (EDA):

  • Cleaned and processed viewership data for ~25,000 titles.

  • Removed duplicates and formatted time-based columns for analysis.

• 🔍 Key Insights Extracted:

  • Shows outperformed movies in terms of total viewership hours.

  • English and Korean content dominated global watch time.

  • Fall season (Sept–Nov) had the highest viewership, suggesting seasonal spikes.

  • Fridays were the most popular release days with the highest engagement.

  • Identified top 5 most viewed titles (e.g., The Night Agent, The Glory).

• 🗓️ Release Trends:

  • Analyzed monthly and weekly release timing vs viewership.

  • Found strategic alignment with holidays like New Year’s and Valentine’s Day to boost views.

• 📈 Visualizations:

  • Plotly-based interactive bar and line graphs for clarity.

  • Comparative views of content type trends, seasonal engagement, and top-performing titles.

Outcome

• Delivered a comprehensive strategic analysis of Netflix’s content performance.

• Identified content types, languages, seasons, and days that drive the most user engagement.

• Demonstrated how data analytics can shape content acquisition and release timing strategies.