Aditya Patil

Product Manager

India5 yrs 3 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Increased customer reactivation rates by 15%.
Elevated customer retention through strategic bundling.
Developed data-driven insights for product evolution.

Stackforce AI infers this person is a Product Analyst with expertise in SaaS and data-driven decision making.

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Skills

Core Skills

Customer InsightProduct StrategyData Analysis

Other Skills

A/B TestingA/B testingAnalytic Problem SolvingAnalytical SkillsArtificial Intelligence (AI)B2CBusiness AnalysisBusiness InsightsBusiness Intelligence (BI)Business RequirementsC (Programming Language)C++Cohort AnalysisCritical ThinkingCross-functional Partnerships

About

As a product analyst, I collaborate with cross-functional teams to identify customer needs, define product features, and test hypotheses. I use customer analysis, reporting and analysis, and data-driven testing skills to drive product evolution and enhance the user experience. Previously, I was a trainee decision scientist at Mu Sigma, a global data analytics firm, where I delivered data-driven solutions for various clients across industries. I increased revenue, reduced costs, and improved user retention and engagement for multiple projects, applying analytical and problem-solving skills. I hold a Bachelor of Engineering in Information Technology from the MIT College of Engineering. I am passionate about creating products that solve real-world problems and make a positive impact. I am always eager to learn new skills, tools, and technologies to enhance my product analysis capabilities. I value teamwork, innovation, and customer satisfaction.

Experience

5 yrs 3 mos

Total Experience

2 yrs

Average Tenure

1 yr 3 mos

Current Experience

Tide

Product analyst 3

Mar 2025 – Present · 1 yr 3 mos · Remote

Ketto

2 roles

Senior Product Analyst

Promoted

Feb 2024 – Mar 2025 · 1 yr 1 mo

· Developed a lead qualification pipeline integrating RFM scoring and customer segmentation to align high-potential leads
with relevant business units, optimizing lead allocation and sales process efficiency.
· Pioneered customer lifecycle analysis through advanced segmentation models, categorizing users into different cohorts,
resulting in targeted engagement strategies and a 15% increase in customer reactivation rates.
· Increased user connectivity by 8% by designing a personalized outreach time window, leveraging data on user activity,
previous touchpoints, and successful transactions to optimize timing for telesales communications.
· Identified target user segments for new verticals like insurance by analyzing user behavior and historical data, collaborating
with stakeholders to build a scalable, data-driven process for geographic segmentation and channel optimization, enhancing
ROI above 2 across diverse markets and segments.
· Advanced the algorithm in the second phase by applying XGBoost machine learning techniques to refine lead scoring.
This approach prioritized features based on importance, achieving 75% precision and 68% recall, contributing to
a significant 19% relative improvement in conversion rates during initial testing phases.
· Elevated customer retention by 2.3% through strategic cross-product analysis and implementation of personalized subscription bundling, identifying high-affinity product combinations and user engagement patterns.

RFM scoringcustomer segmentationcustomer lifecycle analysisdata-driven processXGBoostlead scoring+4

Product Analyst

May 2022 – Jan 2024 · 1 yr 8 mos

Implemented a multi-dimensional lead scoring algorithm utilizing weighted cohort analysis and normalization techniques
across diverse user segments, resulting in a 7% relative improvement in conversion rates through the strategic prioritization of
high-propensity leads for telesales operations.
· Spearheaded A/B testing initiatives on payment gateway optimization and user behavior analysis, resulting in a 4% increase
in conversion rate through the implementation of data-driven payment preference algorithms.
· Developed comprehensive dashboards and reporting frameworks with North Star, leading, and lagging metrics, providing
data-driven insights across product segments to support strategic goals and continuous improvement.
· Engineered an intelligent payment date selection system based on comprehensive user research and behavioral analysis,
identifying that 20% of subscription failures stemmed from insufficient funds, leading to strategic implementation of mid-month payment scheduling.
· Leveraged strong communication and presentation skills to effectively convey data-driven insights and root cause analysis
(RCA) to stakeholders.