Scaling Customer Experience using Generative AI Chatbot for Major Manufacturing Company
Business Problem/Scope of Work
Goal: To reduce the time and effort required for generating NQE reports while improving the accuracy and reliability of the data, thereby enabling the company to make more informed decisions based on the insights provided by the reports.
The Major Telecom Company's Network Quality Engineering team was facing a significant challenge in maintaining an efficient and effective platform to automate the testing of multiple telecommunications services. The testing process was complex, requiring the construction of intricate data extracting, transformation and loading(ETL) packages and the use of multiple data feeds. The team needed to evaluate the extracted information for discrepancies, make necessary modifications, and merge it into a structure suitable for reporting. Additionally, the team was struggling to respond to the demands of multiple subject matter experts as the services and tests touched on various aspects of the telecommunications industry.
To address this challenge, Pronix IT Solutions team was engaged to provide a solution that will streamline the testing process, improve the efficiency and effectiveness of the platform, and help the team to better respond to the demands of the subject matter experts.
Business Solution
To address the needs of the Network Quality Engineering team, Pronix Inc. developed a comprehensive business solution that involved several key steps.
First, the team worked closely with the Network Quality Engineering team to establish a system for monitoring and evaluating performance. This involved a deep dive into the key performance indicators (KPIs) that were most important to the team, as well as an analysis of the data related to test automation. By developing a clear understanding of the KPIs and how they relate to the overall business objectives, Pronix was able to develop a solution that was tailored to the unique needs of the organization.
Once the KPIs were established, Pronix Inc. was responsible for data cleaning and analysis. This involved a comprehensive process of data collection, cleaning, and analysis to ensure that the data was accurate and could be used to inform key business decisions. The team also connected other KPIs to provide a more holistic view of performance and to identify areas for improvement.
To optimize the performance of the test automation platform, Pronix Inc. provided insights that could be used to improve the overall performance of the system. By analyzing the data and identifying trends, Pronix Inc. was able to identify key areas for improvement and to recommend strategies for enhancing performance. The insights provided by Pronix were used to optimize the platform, ensuring that it met the needs of the business and supported its growth and success.
Overall, the business solution developed by Pronix Inc. was a comprehensive and tailored solution that met the unique needs of the Network Quality Engineering team. By working closely with the team to establish key performance indicators and to analyze data related to test automation, Pronix was able to provide insights that supported the growth and success of the business.
Technical Solution
To tackle the challenging data management project, Pronix Inc.'s team employed a range of cutting-edge technologies. They utilized Power BI, a powerful business analytics tool that provided custom visualizations, dashboards, and KPIs based on the organization's requirements. Additionally, the team implemented Windows Server to provide a secure and robust platform for the solution.
To develop the underlying database, the team employed MS SQL Server 2016/2014/2012 and T-SQL. They designed and deployed tables, ensuring optimal data management through normalization techniques. The team also established maintenance plans and stored procedures using T-SQL, thereby enhancing data manipulation processes.
For loading data from XML, Excel, and CSV files, the team utilized SSIS packages, which were also automated to ensure accurate and timely data loading. In addition to that, they implemented SSRS, a reporting tool used to create and deliver paginated and mobile reports.
To add an additional layer of insight and analysis, the team integrated Tableau 8 and Grafana into the solution. These tools provided powerful data visualization and analysis capabilities. MS Visual Studio 2017 was also utilized to create the solution, providing a user-friendly and intuitive interface for the team.
With the successful implementation of this range of technologies, the Pronix Inc. team delivered a comprehensive, efficient, and high-performing data management solution that met the organization's unique needs.
Overall, the Pronix Inc. team's technical solution for the data management system provided a comprehensive and high-performing solution that utilized a range of cutting-edge technologies. By following this step-by-step architecture, the team was able to create a robust and efficient data management system that met the organization's unique needs.
Technologies/Skills Used
The solution for this case study utilizes various technologies such as Power BI, Windows Server, MS SQL Server 2016/2014/2012, SSRS, SSIS, Grafana, MS Visual Studio 2017 and Tableau 8. Power BI will be used to create custom visualizations, dashboards, and KPIs.
Windows Server will be used as the operating system, MS SQL Server will be used as the database management system. SSRS and SSIS will be used to create reports and automate data loading, respectively.
Grafana will be used for monitoring and alerting, MS Visual Studio 2017 will be used to develop and manage the codebase and Tableau 8 will be used to create interactive dashboards to gain insights into the performance of the test automation platform.
These technologies will be used to support the test automation process and ensure data accuracy, reliability and timeliness.
Customer Success Outcomes
Improved Network Performance: The enhanced visibility and real-time access to the NQE data provided by the automation and reporting solution would have allowed the major telecom company to identify and address issues more quickly. This would have resulted in improved network performance and increased customer satisfaction. A 10% increase in network performance could result in a 5% increase in customer satisfaction.
Improved Customer Retention: The improved network performance resulting from the NQE automation and reporting solution would have helped improve customer satisfaction and retention. A 5% improvement in customer retention could result in a significant increase in revenue for the major telecom company.
Increased Revenue: The improved customer retention resulting from the NQE automation and reporting solution would have led to increased revenue for the major telecom company. A 10% increase in revenue could result from a combination of reduced customer churn and increased sales to existing customers.
Improved Data Analysis: The NQE automation and reporting solution allowed the major telecom company to generate reports on network quality evaluations more quickly and accurately. This improved data analysis capabilities, allowing the company to make more informed decisions to improve their network performance. An estimated 15% improvement in data analysis capabilities could result in a significant increase in the efficiency of decision-making processes.
Enhanced Data Management: The NQE automation and reporting solution helped the major telecom company to centralize and streamline their data management processes. This reduced the risk of data errors, improved the accuracy of the data, and increased the overall efficiency of the company's data management. An estimated 20% improvement in data management efficiency could result in significant cost savings and operational efficiencies for the company.
Improved Customer Experience: The improved network performance resulting from the NQE automation and reporting solution would have led to a better customer experience for the major telecom company's customers. This could result in a higher Net Promoter Score (NPS) for the company. An estimated 5% increase in NPS could result in a significant increase in customer loyalty and revenue.
Improved Operational Efficiency: The automation of the NQE reporting process would have improved the operational efficiency of the major telecom company. By streamlining processes and reducing manual effort, the company would have been able to reduce their overall operational costs. An estimated 10% improvement in operational efficiency could result in significant cost savings for the company.
Overall, the NQE automation and reporting solution had a positive impact on the major telecom company's operations, resulting in improved data analysis, enhanced data management, better customer experience, and increased operational efficiency.
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