Customer-Call-Analysis

An analysis of customers that needs to be contacted based on payment being made or not to the company.

Table of Contents

• Project Overview

• Data Sources

• Recommendations

• Project Overview

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Customer relationship management is a fundamental aspect of any successful business. To maintain and strengthen these relationships, it's essential to engage with customers proactively. This project focuses on managing a customer call list, with a mixture of paying and non-paying customers who have expressed a desire to be contacted. The goal is to enhance customer satisfaction, address inquiries, and potentially re-engage non-paying customers.

Data Sources

Customer database with contact information and payment status. Customer preferences and feedback collected through surveys in a company's spreadsheet file.

Tools

Excel for data collection and analysis.

• Data visualization libraries (e.g., Matplotlib) to create insightful chart.

• Jupyter Notebooks for documenting and sharing the analysis process.

• Statistical and data analysis packages (e.g., pandas) for data exploration.

  Data loading & Preparation

Gathered a list of customers who have indicated a preference for contact. This list will include both paying and non-paying customers.

Exploratory Data Analysis

EDA involves exploring the population data, to answer key questions. such as;

1. No of customer that were paying that need to be contacted.
2. No of customers that were not paying that also needed to be contacted.

Data Analysis

Include some intersting code/features worked with

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   Pandas

df = df.fillna('')

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Results/Findings

The analysis results are summarized as follows: 1. We had more paying customers than non-paying customers that needed us to contact them. 2. Most customer's contact begin with the code "123".

Recommendations

This analysis reveals an interesting insight into customer preferences for contact. The fact that more paying customers have expressed a desire for the company to contact them than non-paying customers is a positive indication of customer engagement. It also underscores the potential for strengthening relationships with paying customers, who are likely more committed to the brand.

To leverage this insight effectively, the company can consider the following recommendations:

• Prioritize Paying Customers: Given that paying customers have shown an active interest in further engagement, prioritize reaching out to them. This can include personalized communication, exclusive offers, or proactive support to enhance their customer experience. Strengthening these relationships can lead to increased loyalty and long-term revenue growth.

• Segmentation and Personalization: While paying customers are the primary focus, non-paying customers should not be overlooked. The company can further segment this group based on their previous interactions and preferences. Tailored strategies for re-engagement, such as targeted promotions or solutions to their concerns, can be developed to encourage them to become paying customers.

• Feedback and Continuous Improvement: Use this opportunity to collect feedback from both paying and non-paying customers during interactions. Their input can inform improvements in products, services, and overall customer experience. Implement a feedback loop to ensure that customer preferences are continually addressed.

• Track and Analyze Outcomes: Monitor the outcomes of these interactions closely. Measure conversion rates, customer satisfaction levels, and the impact on customer retention. Analyze which strategies are most effective in achieving the desired results and adjust the approach accordingly.

• Regular Communication: Maintain regular, consistent communication with customers, especially paying customers who have expressed interest in being contacted. This can help sustain their engagement and strengthen the company's relationship with them over time.

In conclusion, the analysis presents an opportunity for the company to capitalize on the willingness of paying customers to engage. By prioritizing paying customers, tailoring interactions, and actively seeking feedback, the company can enhance customer satisfaction, loyalty, and ultimately, its bottom line. Simultaneously, it should not neglect non-paying customers and implement strategies to re-engage them, with the goal of converting them into paying customers.

This recommendation aligns with a customer-centric approach, fostering positive relationships and ensuring that customer preferences are at the forefront of the company's strategies.

Contributions

This project encourages collaboration and expertise in customer relationship management. By actively engaging with both paying and non-paying customers, the company can strengthen its relationships and adapt its strategies to meet customer expectations. Effective call list management is essential for businesses looking to thrive in a competitive market by prioritizing customer satisfaction and loyalty.

Limitations

Cleaning the data using the strip method in pandas library was not an easy task, and also using the replace method. very tasking. Which i usrd to drop Na & nan values. df["Phone_Number"] = df["Phone_Number"].str.replace('nan--','') df["Phone_Number"] = df["Phone_Number"].str.replace('Na--','') df

References

Call centre software for custromer relationship management. Customers feedback through email platforms.