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This document summarizes an exploratory analysis of a utility company's customer data. Key findings include: - Residential and small commercial customers greatly outnumber large commercial customers. - Median billed amounts are higher for large and small commercial than residential customers. - Total estimated revenue is higher for large and small commercial than residential customers. - There is a strong positive correlation between total estimated revenue and customer lifetime value.
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- 1. Exploratory analysis On Utility Company’s Data INTERNSHIP ASSIGNMENT RABIN S.K
- 2. Barplot Of the Customers As it is evident the Residential and Small commercial customers are much more than the Large commercial customers.
- 3. As Expected the median average billed amount is on the higher side for the large commercial and small commercial compared to the Residential And the median values of Large and Small commercial are almost the same which is interesting. Comparison of average billed amount
- 4. Comparison of Total estimated Revenue The median of Total estimated revenue was high for large commercial and small commercial compared to the Residential.
- 5. Scatterplot between Total Estimated revenue and customer lifetime value Running through the correlation analysis for total estimated revenue with all the factors ,it was found that correlation between total estimated revenue and customer lifetime value was the highest and this is a scatterplot of the relationship between them.
- 6. The Loyalty index was the highest for small commercial and large commercial had the lowest loyalty index Usually a higher loyalty index means good profit for the company but surprisingly the price realization which is the degree of company’s performance is higher for large commercial effectively telling that the loyalty index has no say in company's performance and higher loyalty index doesn’t mean a better market performance for the company .
- 7. Now comes the interesting part , comparing the correlation of total revenue with average monthly amount and customer lifetime value,it was found that the correlation decreased from large commercials to Residentials While the correlation between Total estimated revenue and contract lifetime,requested lifetime,residual lifetime increased from large commercials to residentials Comparing the correlation between large commercials,small and Residential
- 8. Inference from the Data Total estimated revenue is usually a good category to measure the companys performance and so I did analysis of it against all the available factors Factors affecting the total estimated revenue differed from Large commercials and small commercials to the Residential While contract lifetime and requested lifetime affects the total estimated revenues of the large and small commercials very minimally ,the Residential gets impacted it by a lot . So the total revenue of the Residential which accounts of almost 50%of the customers depends on contract lifetime,requested lifetime and the residual lifetime while the total revenues from large and small commercial doesn’t depend on it.