Sales-Call-Marketing-Center

Same data, different chart

Table of Contents

• Project brief
• Objective
• Questions to Answer
• Data source
• Tools
• Dashboard design charts
• Development
• Data processing / Transformation
• Findings
• Recommendations

Project brief

Sales call Marketing Center

Objective

To analyze agent performance using a sales call dashboard, identify key trends, improve customer experience, reduce call abandonment, and support data-driven decisions for better sales outcomes.

Questions to answer

1. How many total calls were received and how many were successful, failed, or abandoned?

2. What is the success rate of calls handled by each agent?

3. Why does Sarah Walter have a low success rate despite high call volume?

4. What are the average ratings and call duration for selected agents?

5. What time of day does Sarah Walter receive the most calls?

6. What are the top U.S. states where agents receives the most calls?

7. Are there specific times or months when call volume spikes?

8. Why are calls being abandoned frequently? Is it due to long wait times or other reasons?

9. What percentage of selected agent calls lead to follow-up interactions?

10. What products are most frequently discussed during calls handled by agents?

11. How does Sarah Walter’s performance compare with other agents?

12. Are male or female agents handling more calls, and are there any performance gaps?

Data source

Here are the Data needed to achieve project goal

1. Agents name
2. Product discussed on calls
3. Reason call was abandoned
4. Gender performance
5. Call Outcomes
6. Percentage of follow up calls
7. Minimum and Maximum Monthly call trend
8. States where most call came in from

Tools

Tools	Purpose
Excel ( Functions & Formulas )	Cleaning, Transformation, Processing.

Dashboard design

Here is a list of appropriate chart visuals used in answering key questions.

1. Score cards
2. Column chart
3. Donut chart
4. Area chart
5. Bar chart
6. Clustered bar chart
7. Stacked bar chart
8. Filter panel

Same data, different chart

Development

Here’s a step by step guide on how the data was approached

1. Get the data from source
2. Load Excel
3. Clean and transform with Excel
4. Visualizations using Excel customized charts
5. Generate Insights
6. Give recommendations

Data Processing / Transformation

The goal is to refine the dataset to ensure its clean and ready for analysis.

• Only relevant columns should be retained.
• All data types should be appropriate for the contents of each column.
• No column should contain null values, indicating complete data for all records

Processing

Findings

1. Male agents handled 70% of all calls, with female agents handling 30% of all calls.

2. Top 5 agents with highest call rate is at 69% more than other agents at 31%.

3. High abandonment rate due to long wait times.

4. Average rating of 4.3 indicates customer satisfaction despite low success rates.

5. Most calls came in during late hours of morning (11 AM) and early hours of afternoon (2 PM), with monthly spikes in June (364 calls).

6. Texas and California had the highest call volume.

7. Most discussed product: Loan, followed by Insurance.

Recommendations

1. Improve response time to reduce high abandonment due to wait time.

2. Consider training or workflow improvements to convert more calls to success.

3. Reallocate or increase manpower during peak hours Morning and Afernoon (11 AM – 2 PM).

4. Leverage strong customer satisfaction to improve sales conversion.

5. Focus marketing in high-volume states like Texas, California, Florida.