The Real-Time Data Accuracy as a Driver of Customer Satisfaction in Telecom Services

Аннотация

The telecom sector now prioritizes real-time data accuracy because of increased consumer demand for top-notch customer experiences. The study investigates the connection between real-time data accuracy and customer satisfaction in telecom services. Accurate real-time information becomes essential for shaping customer experiences throughout service delivery and support functions as businesses increasingly depend on data-driven decision-making. This research demonstrates the connection between data inconsistencies and problems that include billing errors along with service interruptions which result in customer dissatisfaction. The study employed a mixed-method approach with qualitative interviews and quantitative surveys among telecom customers and service providers to examine the relationship between data accuracy and customer satisfaction. Real-time data accuracy builds customer trust while reducing resolution time for service problems and increasing customer loyalty. The research emphasizes that inaccurate data erodes customer trust leading to service churn which negatively impacts telecom companies' reputation. The research explores how technology such as AI and machine learning helps maintain real-time data accuracy while automation presents opportunities to reduce human errors. The study proposes several strategies for telecom companies to utilize precise real-time data to boost service quality while enhancing operational efficiency and achieving greater customer satisfaction. The research enhances comprehension of how data precision interacts with customer-focused business tactics in the telecommunications sector. Key words: Real-Time Data Accuracy, Telecom Services, Network Downtime, Quality of Service (QoS), Predictive Analytics, Machine Learning, Big Data in Telecom, Artificial Intelligence (AI), Data Integrity, Customer Retention, Service Quality Metrics, Sentiment Analysis, Data-Driven Decision Making, Error Detection Algorithms, Telecom Fraud Detection. 1. Introduction Telecom services function as indispensable daily tools that connect billions of individuals worldwide with communication and data in our digital age. Accurate real-time data becomes critical for delivering positive user experiences as customer requirements grow. Telecom networks function better and provide correct bills and reliable services through accurate data which leads to higher customer satisfaction and loyalty. Telecom providers confront substantial hurdles in maintaining real-time data accuracy because of the growing implementation of AI analytics and data-driven decision-making processes. Network congestion and faulty data collection systems along https://www.academicpublishers.org/journals/index.php/ijdsml 87 AMERICAN ACADEMIC PUBLISHER with integration challenges prevent telecom service providers from creating accurate real-time data despite technological advancements. Data inaccuracies lead to billing problems and dropped calls while creating inconsistent service quality both of which harm customer trust and satisfaction levels. Addressing these challenges requires extensive understanding of real-time data systems and their effect on customer service results. Research Objectives: This study seeks to deliver an extensive examination of how data precision during real-time telecom operations affects customer satisfaction. The research will reveal valuable insights into telecommunications operational inefficiencies by examining the primary factors that lead to data inaccuracies. The research identifies the direct link between accurate information and customer loyalty over time and assists telecom providers in pinpointing improvement areas while helping them to allocate resources to achieve better data accuracy. By examining both mobile and broadband services this study offers a complete industry perspective which allows researchers to understand how data accuracy affects different operational functions and customer service areas from multiple angles. By taking this wide-ranging approach researchers can pinpoint shared obstacles and optimal methods across multiple service domains which may result in solutions with universal application. The study will investigate technical aspects that impact data accuracy to identify opportunities for system enhancements or technological advancements. The examination process will play a key role in discovering precise technological solutions that improve data precision during live operational activities. This research will examine multiple elements of data management systems such as methods for data collection together with storage protocols and transmission processes as well as real-time processing algorithms. The research intends to examine these technical components to discover vulnerabilities and inefficiencies that result in data inaccuracies. The study will explore user experience outcomes from inaccurate data to help telecom companies achieve better customer perspective understandi