AI-Driven Personalized Content Recommendation System for Streaming Platforms

Medium Priority
AI & Machine Learning
Streaming Platforms
👁️17055 views
💬1119 quotes
$25k - $75k
Timeline: 12-16 weeks

Develop a cutting-edge, AI-powered personalized content recommendation system to increase user engagement and retention on our streaming platform. By leveraging advanced machine learning models, we aim to enhance user experience by delivering tailored content suggestions based on user behavior, preferences, and real-time data.

📋Project Details

Our SME streaming platform is seeking to implement an AI-driven personalized content recommendation system. The goal is to significantly improve user engagement and retention by offering highly tailored content suggestions. We aim to utilize the latest in AI & Machine Learning technologies, including LLMs and NLP models, to analyze user behavior, preferences, and real-time data. The project requires the development of sophisticated algorithms capable of processing large datasets to produce accurate recommendations. Technologies such as OpenAI API, TensorFlow, and PyTorch will be integral to this development. This system will not only provide personalized content recommendations but also leverage predictive analytics to anticipate user preferences and trends. By integrating AutoML and Hugging Face models, we plan to streamline the model training process and improve the accuracy of predictions. The project also includes deploying the solution on Edge AI to ensure low latency and high availability. With a medium level of urgency, we aim to complete this project within 12-16 weeks.

Requirements

  • Experience with recommendation systems
  • Proficiency in machine learning frameworks
  • Strong understanding of NLP
  • Ability to work with large datasets
  • Experience with streaming platforms

🛠️Skills Required

Machine Learning
Python
TensorFlow
Data Analysis
NLP

📊Business Analysis

🎯Target Audience

Our target users are streaming platform subscribers who seek personalized content experiences. They are tech-savvy individuals who enjoy discovering new shows and movies that align with their preferences.

⚠️Problem Statement

As the streaming industry becomes increasingly competitive, users are overwhelmed with content options and often struggle to find shows that match their interests. This results in lower user engagement and higher churn rates.

💰Payment Readiness

The market is ripe for solutions that enhance user experience and retention due to the competitive streaming landscape. Companies are willing to invest in technologies that provide a distinct advantage in user satisfaction and engagement.

🚨Consequences

Failing to address the demand for personalized content experiences could result in decreased user engagement, increased churn rates, and a competitive disadvantage in the streaming market.

🔍Market Alternatives

Current alternatives include generic recommendation systems that lack the precision and personalization offered by advanced AI models. Other competitors may use basic collaborative filtering methods which do not fully leverage the potential of AI & Machine Learning.

Unique Selling Proposition

Our system's unique selling proposition lies in its integration of cutting-edge NLP and predictive analytics to deliver highly personalized and accurate content recommendations, thereby boosting user satisfaction and retention.

📈Customer Acquisition Strategy

Our go-to-market strategy involves promoting the enhanced user experience and retention benefits through targeted digital marketing campaigns. We will leverage social media and influencer partnerships to reach potential subscribers and highlight our platform's unique features.

Project Stats

Posted:July 21, 2025
Budget:$25,000 - $75,000
Timeline:12-16 weeks
Priority:Medium Priority
👁️Views:17055
💬Quotes:1119

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