Analysis of Call Centre Data using Excel
Description: iVision is a well-known analytics firm. iVision does analytics on the data shared by their clients. Recently, iVision collaborated with Nile, an E-commerce company. Nile intends to improve their customer service, but before doing so, Nile wants to get some insights on their customer service request data. To help Nile make better business decisions and improve their services, iVision is engaged to provide Nile access to the analytics dashboard and report. Nile has shared its customer service data with iVision. As an employee of iVision, you are responsible for creating this analytics report.
Business Objective: The analysis aims to leverage data-driven approaches to optimize customer service processes, enhance customer experience, and drive overall business growth. By examining historical customer service data, the project seeks to identify patterns, trends, and opportunities for improvement, ultimately leading to enhanced customer loyalty and increased operational efficiency.
Project Goals:
Customer Sentiment Analysis:
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There are higher number of negative sentiments than neutral or positive ones.
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If we dive deep into that, then as per the comparison of Csat score & Response time, the negative sentiment is highest among people with Billing questions.
Root Cause Analysis:
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Common customer complaints is Billing related queries.
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The channel through which the most payment queries are handled are Call centre so more workload is shared for Billing & Payment followups hence the increased response time.
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Hence distribution of customer query through proper channel is something they can work upon
Service Response Time Analysis:
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LA team has response time within SLA which is highest amongst the dataset.
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Denver has lowest score for resp. time below SLA.
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So this builds up a picture that respective call centres will need to develop special case study wherein the efficiency of their service team can be improved & maintained in future.
Customer Segmentation:
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Based upon the dataset presented, the customers have been pragmatic about their approach in identifying the fastest means of resolution for their query which is call-centre, wherein most positive & very positive inputs have been resolved through.
Trends and Patterns Identification:
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To summarise, the trends & patterns within this dataset is something which I found to be of a research topic and honestly Nile needs to work upon their customer support services in a tech-savvy means such that their throughput can be improved & maintained.
