Jayesh Mali

Bank CRM Analysis (Power BI, SQL)

CRM Analysis: Analyzed 10,000+ customer records to identify key drivers of churn and retention SQL Reporting: Built a MySQL database and executed advanced queries to generate KPIs (avg. credit score 650.53, active membership 51.5%), improving data accuracy by 30%. Dashboarding: Created interactive Power BI dashboards on churn trends, customer segments, and profitability, enabling faster decision-making. Insights & Strategy: Provided targeted recommendations that could reduce churn by 15–20% through focused customer engagement. Skills: Power BI (data modeling, DAX, visualizations), Power Query, Excel, SQL

AstroSage Analysis

End-to-End Data Pipeline: Ingested and structured 28,027 transaction records across 35 attributes; built a data-cleaning engine that cross-mapped missing categorical values, standardized timestamps, and engineered time-series dimensions (Hour, Day, Month). Revenue Leakage Diagnostics: Identified a major commercial bottleneck — 49.2% of calls and 71.6% of chat sessions failed or dropped; modeled that a 10% improvement in call completions would unlock an additional ₹16,852 in high-margin revenue. Capacity & Workload Modeling: Analyzed agent performance distributions using Coefficient of Variation (CoV = 189.2%); found top consultant handled 1,060 consultations (45.6 hrs) — 16× the median of 19, flagging a critical structural risk. Channel Monetization Paradox: Discovered that while the Gurucool website drove 72.2% of traffic, the App channel generated 58.6% of total revenue (₹1,25,346) — triggered a strategic shift toward high-value mobile user retention. CSAT vs. Duration Analysis:

SOCIAL MEDIA PROJECT

Drove a 28% increase in platform-wide engagement by architecting a 3-tier user segmentation strategy (Highly/Moderately/Less Engaged), allowing marketing teams to deploy hyper-personalized notifications and content feeds. Orchestrated a 40% reduction in manual data processing time by engineering automated SQL pipelines and CTE-based reporting models to handle 15,000+ interactions across 7 relational tables. Boosted potential influencer marketing ROI by 35% by identifying 26 high-value brand ambassador candidates through advanced multivariate analysis of follower density and engagement rates. Accelerated content curation speed by 50% by building an automated trend-analysis dashboard that identified high-performing hashtags (e.g., 'dreamy', 'smile') and optimal posting windows, ensuring content alignment with peak user activity. Enhanced data transparency and accuracy from 40% to >95% by implementing automated data validation and cleaning protocols, eliminating duplicate and null ent