Sri Harshini Gosangi

Performed Customer Segmentation using Clustering methods and RFM analysis to identify customers with similar purchase behavior and provided insights to marketing team which helped them in designing better ad campaigns, offers to its target customers which resulted in 4% increase in retention rate. Built model to predict whether the order will get cancelled or not, if the prediction is true then the cod option gets blocked for the transaction. Resulted in 11% of reduction in customer driven cancellations without effecting the conversion rate. Retrained the model that was built to predict the post-delivery issues raised are genuine or fraudulent. Retrained model additionally saved around 0.13 million USD per month. Developed a framework to identify and penalize the customers with high return % resulted in 1.8% impact on platform returns, thus resulting in estimated net savings of 8.65 million USD per annum. Analyzed repeat rate behavior of customers based on order delivery speed and recommended Supply Chain logistics team to improve SDD and NDD which have potential to improve platform revenue by 3.15%.

Performed AB test analysis to see if the new feature implemented led to increase in RPU, conversion, CTR. As a result of testing the hypotheses, if a significant difference is found between the control and test groups, such experiments are considered successful and are rolled out in the app. Worked on Notifications CTR driving 10% traffic & 8% GMV for Myntra Fashion across email, push notifications and in-app notification channels via cohort strategy, data-backed improvement of content, engagement and conversion metrics. Identified pain points, areas of improvement in the app by understanding new user journey from installation to acquisition, which have potential to improve customer base by 17% and revenue of the platform by 4.58%. Performed analysis to understand app logins from various channels and identified that logins have a failure rate of 60% which compelled to rolling out Mobile Number only login which has driven more traffic to the platform and increased successful login rate by 9.05%. Extracted, interpreted and analyzed data to understand trends for key metrics and transform raw data using SQL for designing and creating dashboards. Performed automation of multiple dashboards and trackers.