Abhishek Sharma

Developed and implemented an AI-driven competitor intelligence system using Gemini vector embeddings to automate pricing, assortment, and store-coverage comparison for Blinkit/Instamart products.

Constructed daily governance dashboards for CXO-level business reviews, providing critical KPIs to enhance strategic decision-making and operational oversight.

Identified and resolved key gaps in the adtech platform, successfully increasing search ad density by 5% while optimizing user experience.

Spearheaded a reduction framework for obsolete inventory, identifying ₹250 Cr worth of inventory and achieving ₹120 Cr in cost savings.

Defined and led the A/B experimentation charter across 500+ brands, driving measurable impact on brand conversion and retention, and increasing platform AOV by 500 bps.

Collaborated with Product Managers to design end-to-end instrumentation and funnel logic for high-impact Homepage "Big Events," contributing to 30% of total platform revenue.

Architected a loss tree model to precisely attribute marketing revenue drop-offs, enabling teams to reduce consumption (ad revenue) risk by over 50%.

Mentored and managed a team of 3 analysts, and guided 20+ junior analysts within the Center of Excellence, fostering a culture of analytical best practices and professional development.

Led product analytics for Groww's broking vertical, directly contributing to over 95% of the company's revenue through data-backed product and strategy decisions.

Defined core KPIs and built comprehensive dashboards to track trading behavior, retention, and conversion funnels, enhancing visibility into user journeys.

Created and implemented an end-to-end experimentation framework from scratch, conducting A/B tests to optimize product launches and user experiences.

Formulated and executed new product strategies in close collaboration with business teams, shaping the company's product portfolio and market positioning.

Successfully launched key products including the new Groww App, In-house Option Chain, Trading view charts, Quick Navigation, Most Bought, Market Trends, and Collections.

Implemented faster navigation options for regular traders, significantly improving the seamless trading experience on the platform.

Conducted in-depth segmentation analysis to understand distinct customer behaviors in stocks and FNO, facilitating targeted product development and feature prioritization.

Joined as one of the earliest employees (company size < 30) before Series A and seed funding, earning a high-impact award in OND quarter '21 for significant contributions.

Developed initial data infrastructure by creating multiple API integrations with Unicommerce, Razorpay, Flipkart, Amazon, and Google Analytics.

Drove the growth of the 'GreenSoul' brand, contributing to due diligence and a Value Creation Plan, and scaling its revenue by 3x.

Collaborated with the M&A team to create Value Creation Plans (VCP) for identifying potential in acquisition targets.

Provided data-driven marketing insights using Google Analytics and Mixpanel, significantly improving campaign performance and ROI.

Developed a pricing and product ranking intelligence model to track competitor movements across Amazon and Flipkart, informing strategic adjustments.

Led demand planning, pricing strategy, and marketing strategy, automating live reporting during major events like Prime Day and Diwali sales, achieving 5x growth on brands over BAU.

Created comprehensive dashboards to track customer shopping behavior, retention, payment gateway failures, and website performance, enhancing user acquisition across multiple brand websites.

Automated financial reports using R and Tableau, delivering daily financial numbers to Myntra and Flipkart Board members for informed decision-making.

Developed an automated FIFO query using SQL and R to analyze inventory data, improving tracking accuracy and efficiency.

Generated monthly KPI reports to track progress against targets and goals, directly contributing to improved company performance.

Led a project predicting hit and provision caused by aged inventory (360+ age), which optimized inventory management and reduced losses from bad inventory.

Forecasted net COGS burn value for upcoming months using Time Series Analysis, supporting strategic financial planning.

Managed PnL, pricing, and inventory for 'occasion wear' and 'essentials' categories, directly driving revenue generation.

Implemented day-to-day strategic pricing initiatives that resulted in a 30% increase in revenue for two key categories.

Created and automated a visibility dashboard to track important KPIs of all pricing actions, enhancing data-driven decision-making and transparency.