Recent Graduate 🎓 | Aspiring Data Analyst | Expertise in PowerBI, Tableau, SQL, and Excel 📊 | Skilled in Python Development 🐍 | Passionate About Machine Learning and Analytics 💡
Hi Connections , I am happy to share that I analyzed a fascinating dataset from an American customer support agency, which encompassed the operations of four call centers. Here are some of the key findings and recommendations: ✅ #kpi : . Total Calls: 32.94K . Total Call Duration (hours): 13.74K hours . Total Call Duration (minutes): 834.22K minutes . Average Call Duration: 25.02 minutes . Response Time: 75.26% . Analysis and Insights ✅Total Calls by Day: Thursdays and Fridays were the busiest days, with the highest call volumes. ✅Total Calls by Reason: Billing-related inquiries dominated, reflecting a common concern among customers. ✅Total Calls by Channel: Interestingly, the call center received the most calls, followed closely by chatbot interactions. Email and web inquiries also made a significant impact. ✅Total Calls by Sentiment: Negative sentiment calls were the most prevalent at 11.1K, emphasizing the need for effective issue resolution. ✅Total Calls by Call Center: The Los Angeles center took the lead with 14K calls, followed by Baltimore with 11K, Chicago with 5K, and Denver with 3K calls. ✅Total Calls by State: To visualize the data, I created a map chart showcasing the call distribution by state. It provides valuable geographic insights. 💡#Recommendations : To enhance customer experience and mitigate negative sentiment, the call center agency can consider the following steps: 🔹Implement proactive issue resolution techniques. 🔹Enhance training for customer service representatives to handle difficult inquiries effectively. 🔹Implement sentiment analysis tools to identify issues in real-time and address them promptly. 🔹Encourage customer #feedback and utilize it to improve services. These findings can help shape strategies to enhance customer support services, improve response times, and optimize resource allocation. Please #like and #share this #linkedinpost , and leave a #comment below with your thoughts on how this analysis can be improved. Follow me for more interesting dashboards and hashtag#reports . Thank You! Hashtags: #dataanalysis #analytics #Insights #businessintelligence #datavisualization #sql #excelskills #job #hiringmanager #DataTrends #mavenanalytics #DataInsights #DataAnalytics #DataScience #PowerBI hashtag #Dashboard #ai #hrmanager #hr #businessanalysis #powerbideveloper #powerbidesktop #powerbidashboard #freshersjobs
