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Top1. Introduction
All companies depend on stakeholders, human resources, and customers as their backbone especially the telecom companies, that more interested to proactively interact with its customers on the significant increase in the number of telecom companies, that leads to customer migration from one company to another and create continuous warfare between companies. So, all these companies try not only to retain their current customers but also to increase them (Marchand et al., 2017). Prediction tasks have many useful applications ranging from tracking opinions about service to identifying the best and bad service and predicting of the telecom customer satisfaction, this prediction is based set of statistical studies.
Telecom companies may get a bad rap when it comes to customer experience. All too mostly customers feel that service inappropriate with their expectations, but those complaints useless as if it falls on deaf ears (Kasemsap, 2017; Aikhuele & Turan, 2018). Over the past years, there were trials for finding a solution to retain the telecom customer loyalty by found a positive correlation between service recovery and customer satisfaction (Ibrahim et al. 2018). A lot of companies are suffering from problems with integrating strategic planning into their daily works and promotional campaigns. There are many needs to suggest how strategic planning can solve these problems (Galli, 2018). But despite the poverty of the telecom companies in detecting customer sentiment, few companies have made the customer care as the first target and empirically test and evaluate the direct and indirect effects of service encounter constructs of service quality (Gera et al., 2017).
Hence, The proposed work tries to show how the use of customer textual data that come from an AI chatbot helps to determine if the telecom customers are willing or not with the new service, if not, how can we help them?, and helps to find a solution for a set of issues like what is the percent of success and acceptance of the new service? What are the services that a telecom customer does not need? And what the services that win the satisfaction of the customers? The proposed system can help the telecom companies to live day per day with its customers from the behavioral side; If it can predict and know the sentiment and behavioral meaning in each response. A question like what is the emotional affection that the change in a service lave? or do they really love the new feature added? Can be answered based on the proposed work in this paper.
The problem entities are how to understand and use the agreeableness and emotional range personality traits and its sub-traits with the sentiment analysis, emotional values of the telecom customer’s conversations as shown in Figure 1, and how the use of this traits help for reaching to a detailed report about customer feel towards the telecom company.
Figure 1. The cooperation between customer traits (agreeableness and Emotional range) and sentiment analysis in tracking telecom customer feel