Sanghmitra Singh

My work at Saras Analytics involved managing advertising sources, building data connectors, and leading significant client projects to enhance business efficiency and resolve complex issues to deliver data-driven solutions that align with strategic business goals.

• Spearheaded management of diverse advertising data sources, ensuring meticulous data verification and analysis to support strategic marketing decisions.
• Impact: Significantly reduced client and consulting issues by 63% through prompt and accurate data analysis.
• Pioneered development of the first logistic data connector using Daton, Postman, SQL, and Excel, streamlining data accessibility for logistics customers.
• Impact: Facilitated a 21% increase in customer engagement by providing easy access to logistic data.
• Orchestrated creation and management of Amazon Selling Partner and Vendor Central connectors, automating UI processes and minimizing monthly bugs from 150 to 40.
• Impact: Enhanced operational efficiency and data integrity, leading to the successful deployment of new features and reduction in system bugs

• Coupon Distribution Analysis: Analyzed user ride behavior with the help of fare and number of rides taken in one month using SQL.
• Conducted A/B testing by segmenting users into distinct categories according to ride frequency and fare, enabling targeted analysis and personalized strategy development.
• Designed different coupons and rate cards to optimize overall pricing and handled these campaigns on Moengage and Webengage
• Impact: The number of rides in subsequent months increased by 4% - decreased overall spending on cashback by 1%.
• Fraud Analysis: Creating Logic to detect various types of fraud that exist in cab booking models.
• Identified key fraud types and crafted strategic business rules to mitigate them, safeguarding the integrity of our platform's transactions and user experience.
• Impact: Fake rides decreased by 5% in the subsequent month because of the business rules.

• Led project to address rising product returns by tracking and categorizing sales data using Google Data Studio, enabling targeted analysis and strategic response.
• Developed data mining algorithms to identify and classify patterns in data.
• Performed Cohort Analysis to identify daily level trends in return in different categories
• Lead Analysis: Performed an analysis to identify factors providing better leads through Facebook campaigns.
• Tracked leads to conversion ratio to identify ways through which conversions can be increased.