Telecom Churn Analysis

Here's a snapshot of the journey:

****Data Validation and Manipulation in Excel:** For the validation of the data, Excel served as my starting point. Ensured that the columns did not contain obscure data points and outliers. Some of the columns contained null values, hence used Excel's "find and replace" to substitute those values accordingly.

****Initial Analysis with Pivot Tables:** For the initial analysis, pivot tables assisted me in uncovering the trends, identifying major factors contributing to churn, and also highlighting the areas for improvement. Pivot charts also proved to be valuable in visualizing the insights.

****Visualization and Insights Presentation in Power BI:** I opted for Power BI to visualize the insights uncovered previously in Excel. Some of the highlights are mentioned below:

-Created calculated age category column using DAX to visualize the retention vs churned rate. -Visualized the KPIs using new card visual. -Visualized the churn breakdown in stacked bar chart. -Used numeric parameter and DAX measures to enable the end-user to view the top churn reasons dynamically. Used field parameter to dynamically switch the churn in either numeric format or as percentage. -Used DAX measure to maintain the sorting of top churn reasons.

****The results** -The insights uncovered the tail of churn being mostly due to competitor offering better services and customer's dissatisfaction with the product, customer service and price.

-The company lost approx. 26% of its customers in Q2-2022. Whereas only 6% accounted for new customers in the same time span.

-The elderly people had the highest churn rate due to the same churn reasons stated in the first point.

-Most of the churned customers were using fiber optic internet and were subscribed to monthly contract.

-San Diego faced the highest churn with 185 churned customers, followed by Los Angeles with 78.

****Recommendations:** The following recommendations are based on the above-stated insights:

-The company should review its services and data offers. And offer market-competitive data offers and services to compete in the market.

-There's a need to invest in high-availability of network. The company also need to invest in the training of their customer service department.

-The pricing should be reviewed, and they might need to explore the option of offering the discounted deals to its customers.