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Conducted extensive analysis of WeTalk's 2020 Q1 dataset using Google Sheets. Leveraged pivot charts to extract actionable insights, meticulously crafting a comprehensive dashboard for detailed evaluation of agent performance and operational trends in the support center.

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Screenshot 2024-03-10 at 15 00 19 Screenshot 2024-03-10 at 15 01 51 Screenshot 2024-03-10 at 15 02 09

WE TALK COMMUNICATIONS TASK TRACKER ANALYSIS

Welcome to the WeTalk Communications Task Tracker Analysis project repository! This project focuses on analyzing the 2020 first-quarter data from the WeTalk Communications Support Center. The dataset provides insights into call handling performance, call types, and call volumes, which are crucial for optimizing operations and enhancing customer satisfaction. Utilizing Google Sheets, we've employed data validation tools to ensure data security, conducted in-depth analysis using pivot charts, and created a comprehensive dashboard to visualize agent-wise performance breakdowns.

OBJECTIVE:

Our objective is to analyze the first-quarter data from 2020 to uncover trends and patterns within the WeTalk Communications Support Center. By examining call handling performance, call types, and call volumes, we aim to identify opportunities for optimizing operations and improving customer service efficiency.

METHODOLOGY:

The dataset comprises 2020 first-quarter data from the WeTalk Communications Support Center. We utilized Google Sheets for data analysis and visualization. During the data cleaning phase, we focused on ensuring data accuracy and consistency by checking for duplicate entries and handling missing values. Data validation tools were applied to enhance data integrity. Pivot charts were then leveraged to extract meaningful insights from the dataset, and a user-friendly dashboard was created to visualize agent-wise performance breakdowns.

KEY QUESTIONS ANSWERED:

  • Which month had the highest number of calls, and in which city was this observed?
  • What were the predominant types of calls across the three months?
  • How did the average call time vary across the three months?
  • Which city received the highest number of calls, and which received the least?
  • Which agent handled the maximum number of calls, and which handled the minimum?
  • Did agents show improvement in call duration over the three months?

SUMMARY OF FINDINGS:

  • January witnessed the highest number of calls, primarily in Chicago.
  • Usability Feedback was the most frequent call type, followed by Software Update.
  • Average call time peaked in Month 1 and decreased in Month 3. Chicago received the highest number of calls, while New York City and Phoenix received the least.
  • Agent 5 handled the maximum number of calls, while Agent 3 handled the minimum.
  • Three out of five agents showed improvement in call duration over the three months.

RECOMMENDATIONS:

Based on the analysis, we recommend:

  • Targeting marketing efforts during peak call months to maximize customer engagement.
  • Exploring expansion or intensified marketing efforts in high-volume call cities like in Chicago & Houston
  • Monitoring agent performance trends to identify areas for improvement and training opportunities.

CONCLUSION

In conclusion, the WeTalk Communications Task Tracker Analysis project provides insights into call handling performance and customer interaction trends. This analysis serves as a foundation for WeTalk Communications to optimize operations, enhance customer satisfaction, and drive overall business success.

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Conducted extensive analysis of WeTalk's 2020 Q1 dataset using Google Sheets. Leveraged pivot charts to extract actionable insights, meticulously crafting a comprehensive dashboard for detailed evaluation of agent performance and operational trends in the support center.

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