Leveraging Predictive Sentiment Analytics and Reinforcement: Learning for Proactive Customer Experience in SaaS Companies.
Abstract
In a busy market, delivering a prepared and positive customer experience is important to supporting growth and building trust. This study examines how prediction combined with learning from trial and error can support SaaS companies to understand customer needs, notice warning signs, and improve customer service. We checked out other studies, suggested a suitable structure for SaaS companies, discussed practical issues, and made recommendations for useful applications. The goal is to provide a clear, accessible guide for SaaS executives and data teams to adopt these data insight tools for anticipating customers' needs. This study shows how Software as a Service companies can use predictive sentiment analytics and reinforcement learning to improve customer experience before problems occur. This study examines how emotional detection and machine learning can help companies know unhappy customers and take action early. The paper shows current study and explains important technologies, and provides useful suggestions for SaaS companies looking to apply these methods.
Citations
IRE Journals:
Hannah Bere "Leveraging Predictive Sentiment Analytics and Reinforcement: Learning for Proactive Customer Experience in SaaS Companies." Iconic Research And Engineering Journals Volume 9 Issue 5 2025 Page 2712-2716
IEEE:
Hannah Bere
"Leveraging Predictive Sentiment Analytics and Reinforcement: Learning for Proactive Customer Experience in SaaS Companies." Iconic Research And Engineering Journals, 9(5)
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