Maximizing Lifecycle Profitability in Technology Products Through Enhanced Sentiment Analysis and Dynamic Pricing

Abstract

In the highly competitive landscape of technology products, maximizing lifecycle profitability is crucial for sustaining growth and achieving market dominance. This study explores the integration of enhanced sentiment analysis and dynamic pricing strategies to optimize profitability across the product lifecycle. By leveraging advanced natural language processing (NLP) techniques, we analyze consumer sentiment from various digital platforms to gain insights into market trends, consumer preferences, and product perception. Coupled with real-time dynamic pricing models that adjust prices based on demand, competition, and market sentiment, our approach aims to enhance revenue generation and customer satisfaction. The findings demonstrate that integrating sentiment analysis with dynamic pricing not only improves profit margins but also enables technology companies to respond proactively to market changes, thus maintaining a competitive edge.