ANSHUMAN PANDA

Customer Next Best Action

• Analyzed transaction and survey data to segment customers based on visit frequency and transaction values, uncovering key behavioral patterns
• Conducted past and post survey transaction analysis across customer segments to evaluate the impact of feedback on sales performance over varying time windows
• Identified the effect of negative reviews on sales, enabling the development of strategies to address customer concerns and improve retention
• Built and implemented a regression model with model accuracy of 83% quantify the influence of survey categories on customer ratings, driving data-informed business decisions.
• Delivered actionable insights that enhanced customer engagement strategies and optimized business outcomes.

• Conducted exploratory data analysis – EDA to uncover patterns, trends, and anomalies within datasets, utilizing various statistical techniques, including hypothesis testing, and visualization tools to derive actionable insights
• Employed preprocessing techniques such as data cleaning, feature engineering, and normalization to ensure high data quality and suitability for further analysis and modeling
• Developed and implemented machine learning models, including Lasso regression and Bayesian regression, to predict outcomes with a model accuracy of 85%, optimize processes, and drive decision-making
• Designed and deployed production-grade, scalable code for Market Mix Modeling, ensuring robust and efficient implementation in real-world business environments
• Led efforts in promotion optimization, developing models to identify optimal budget allocation strategies for advertising campaigns, driving improved marketing effectiveness and maximizing ROI