Product Marketing

Harini Mukesh  • Peerlist

Designed a 5-table relational database and conducted a 21-step exploratory analysis on synthetic SaaS customer data. Identified key pre-churn behavioral patterns using logistic regression; discovered 90-day support ticket drop as the strongest churn predictor — explained through Learned Helplessness theory. Built 5-dashboard Power BI report including a Customer Success Action Center, flagging 366 at-risk accounts with personalized intervention recommendations. Key insight: 85% of churn occurs in Year 1 — onboarding optimization is the highest-ROI intervention.

Behavioral Churn Analysis — RavenStack SaaS P

– Wrote complex SQL queries using joins, aggregations, and filtering. – Analyzed profitability trends, genre performance, and audience ratings. – Identified relationships between budget and commercial success indicators.

IMDB Movie Data Analysis | MySQL

– Built logistic regression model to identify high-conversion leads. – Performed feature engineering and evaluated performance using accuracy and ROC metrics. – Generated insights to optimize marketing lead prioritization.