🎬 OTT Subscription Forecasting and Market Insights

This Streamlit-based data science app analyzes and forecasts subscription growth for OTT platforms using time series forecasting ARIMA.
Dataset is mocked dataset of Netflix and UI is Inspired by Netflix’s aesthetics, it visualizes subscriber trends, forecasts future counts, and reveals actionable business insights for the OTT market.

---

📊 Project Overview

This project demonstrates how time series forecasting can be used to understand the growth potential of OTT platforms like Netflix.
It uses historical subscription data to forecast future subscribers, helping media and entertainment businesses with revenue planning, pricing strategies, and market insights.

Key Features:

• Upload or use sample OTT (Netflix-style) subscription data (2014–2024)
• Visualize historical subscriber growth trends
• Forecast future subscriptions using ARIMA
• Explore trend and seasonality components
• Netflix-themed red and black UI 🎨

---

🧠 Forecasting Workflow

1. Collect historical subscription growth data
2. Clean and preprocess for time series consistency
3. Explore and visualize trends over time
4. Select a forecasting model (ARIMA)
5. Train the model on historical data
6. Forecast future subscription counts for the next quarters

---

🖥️ App Preview

🎥 Netflix-inspired dashboard with an elegant dark theme

• Red and black color palette
• Card-style sections
• Interactive forecasting visualizations
• Sidebar with About and Data Source

---

🚀 Run Locally

1️⃣ Clone the repository

git clone https://github.com/<your-username>/OTT-Subscription-Forecasting-and-Market-Insights.git
cd OTT-Subscription-Forecasting-and-Market-Insights