• Built a Logistic Regression Model for a Technology client to find out the most likely customers to take the subscription • The project also helped the client understand the key drivers of subscription • Developed Propensity models using Logistic regression to predict prospective targets for marketing.• Using logistic model to Identify subscribers who are more likely to churn.• Measure the performance of campaigns for a major telecom firm based in the Norway using data analytics. • Provide recommendations to improve campaign success and drive higher sales among the loyalty members. Generate insights into customer behavior and spending in order to augment better targeting and boost sales.• Capture the response of customers on individual campaigns. Based on that inference on the customer responsiveness.• Conduct analysis on existing and past promotions/campaign that is conducted by the client in terms of their impact.• Test v/s Control study to measure the impact of campaign.• Predicting the performance of future campaign based on historical campaign analysis.• Customer behavior and value segmentation based on analysis of various parameters. Customer segmented in different groups whose behavior and needs are different from each other. • Recognize the preference of customer and then to effectively offer products and services that enhance customer loyalty.