A Study on E Mail Intent Analysis at Zoho Corporation
KRITHIK S
ABSTRACT
In today’s fast-paced business environment, email continues to be an essential communication channel for a wide range of purposes, including customer interaction, internal collaboration, and service delivery. The sheer volume of emails, however, has made it increasingly difficult to manually process and interpret the intent behind each message, leading to inefficiencies and delays in response times. As a result, businesses are turning to Artificial Intelligence (AI) tools to automate and streamline email management. This study evaluates the Email Intent Analysis feature developed by Zoho Corporation, a renowned leader in Software as a Service (SaaS) solution, which leverages AI and machine learning models to automatically identify the intent of incoming emails. These intents can range from requests, complaints, and queries to purchases, allowing businesses to efficiently categorize and prioritize email responses. The primary objective of this research is to assess the accuracy, contextual relevance, and overall practical utility of this tool in real-world applications. Specifically, the study focuses on evaluating the feature's performance in diverse email scenarios, including the ability to handle multi-intent emails and its integration with various business workflows. Critical factors such as prediction confidence, grammar sensitivity, tone recognition, and emotion tagging are also examined, as they contribute significantly to the tool’s ability to accurately interpret the nuances of email content. Both qualitative and quantitative evaluations are conducted to gauge the effectiveness of Zoho’s solution in improving email management processes and enhancing customer support operations. Ultimately, the study aims to offer valuable insights into the practical implications of using AI-driven email intent analysis, shedding light on its potential to optimize business communication, streamline operational efficiency, and enhance customer satisfaction. Furthermore, the research will provide actionable recommendations for enhancing the feature’s performance and user experience, ensuring that the technology can meet the evolving demands of businesses in an increasingly digital world.
