Cloud-Based NVivo for Predictive Analysis in Movie Success and Audience Insights

Abstract

The global film industry faces ongoing challenges in predicting audience preferences, forecasting box office performance, and optimizing marketing strategies. Traditional approaches, reliant on historical data and generalized assumptions, often lack accuracy and adaptability. This study introduces a cloud-based NVivo framework for predictive analysis, integrating structured metrics such as box office data with unstructured sources including social media comments, reviews, and audience feedback. The methodology employs qualitative coding, sentiment analysis, and machine learning techniques to generate real-time insights into audience behavior and film performance. Results demonstrate that NVivo’s predictive analytics enhance the accuracy of success forecasting, provide demographic-specific insights, and support proactive risk assessment. The system further facilitates tailored marketing strategies and content recommendations, enabling studios and marketers to respond dynamically to evolving audience sentiments. This research highlights the transformative potential of cloud-based qualitative analytics in driving data-informed decision-making within the entertainment industry.