Product & Business Analyst
Aayush
Yadav
Former national-level squash player turned product thinker. I find user problems, validate them with data, and build solutions that move metrics.
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Former national-level squash player turned product thinker. I find user problems, validate them with data, and build solutions that move metrics.
IIT Delhi graduate with a knack for translating messy business problems into clean, measurable solutions. I blend analytical rigor with product intuition — using SQL, analytics, and AI tools to ship things that matter.
V2L Conversion Lift
Training Time Reduced
Agents Impacted
B.Tech, Textile Technology
Indian Institute of Technology Delhi
2021 — 2025
Business/Product Analyst — Health Insurance
Policybazaar · May 2025 – Present
Captain, IIT Delhi Squash Team
National Rank #34 · 8 Gold Medals
Best Sportsperson of the Year — IIT Delhi
A Chrome extension that prompts users to declare their purpose before visiting distracting sites and sets a countdown timer — enforcing accountability and cutting mindless browsing.
An AI-powered tool that analyzes every sales call transcript against the ideal pitch framework, generating scores across multiple parameters and actionable improvement suggestions for 300+ agents.
A comprehensive knowledge base of 100+ database tables and business logic, paired with a Custom GPT that lets anyone describe desired output and get recommended tables, columns, and joins.
An MVP displaying existing customer density by pincode to build trust in Tier 2/3 cities — addressing the key drop-off driver identified through user behavior analysis. Resulted in 10% conversion improvement.
Awarded by the IIT Delhi Director for an undefeated season across all tournaments.
Across inter-college and interstate level squash tournaments. National Rank #34.
Led the IIT Delhi squash team to victory at Inter-IIT Sports Meet 2023 and 2024.
Received a Pre-Placement Offer after internship for outstanding contributions to product and data initiatives.
Aayush joined Policybazaar as a Product cum Business Analyst and quickly stood out for his fast learning and strong ownership. He brings a rare ability to think from both product and business perspectives, ensuring practical and impactful solutions. He is also highly proficient in data analytics, using data effectively to drive insights and decisions. Aayush is a well-rounded professional and a valuable asset to any team.
Mindlessly is a Chrome extension built to solve a personal pain point — mindless scrolling. It forces you to declare your intention before visiting distracting sites like YouTube, Instagram, or Twitter, then sets a countdown timer. If you can't state why you're there, you probably shouldn't be.
Kept the UX deliberately minimal — a single input prompt and a timer. No dashboards, no settings overload. The friction of typing your purpose is the product. Built as a popup with a content script that intercepts navigation on blocked domains.
An AI-powered sales coaching tool built at Policybazaar to replace manual QA for sales calls. Every call transcript is automatically scored against the ideal pitch across multiple parameters — opening, needs discovery, objection handling, closing — and personalised improvement suggestions are generated for each agent.
Integrated NotebookLM as the intelligence layer, trained on the ideal pitch playbook. Transcription API converts raw call audio to text, which is then passed through the scoring pipeline. Output is structured feedback per parameter — actionable, not just a number.
A company-wide data intelligence knowledge base built during my internship at Policybazaar. Documented 100+ database tables, columns, KPIs, join relationships, and business logic — then trained a Custom GPT on it so anyone in the company could describe their desired output and get recommended tables, columns, and joins without needing SQL expertise.
Structured the documentation in a GPT-parseable format — each table entry includes purpose, key columns, common joins, and example use cases. The Custom GPT was prompted to think like a data analyst, asking clarifying questions before recommending a query structure.
An MVP built to address trust as the primary drop-off driver in Tier 2 and Tier 3 cities on Policybazaar's health insurance funnel. The feature displays the number of existing customers in the user's pincode area — showing "X people in your area are covered" — to reduce purchase hesitation through social proof.
Identified trust as the key issue through user interviews and funnel drop-off analysis. Designed the feature to be non-intrusive — a subtle callout on the policy detail page. Used Claude Code to rapidly prototype the MVP, which was then validated with a small user cohort before broader rollout.