Piyush Ajmeria

Senior Product Manager | IIM Ahmedabad MBA

I turn complex product problems into measurable growth across AI-enabled AdTech, recruitment and e-commerce. I build 0-to-1 products, improve monetization, and scale engagement through fast, data-led experimentation.

Portrait of Piyush Ajmeria
  • 3× ARRgrowth at MonetizeMore
  • 20M+users on the Naukri platform
  • 90M+monthly GenAI-powered communications
  • 9h → 1hfraud analysis time per domain

Work

Selected product impact

Four products, what problem each solved, and what changed. Open a card for the full case study.

AI product development

An AI agent that analyzes invalid traffic patterns and recommends domain-specific remediation for publishers.

Became sales' primary upsell demo
0-to-1 product launch

A website scanner with 78 AI-powered Google policy checks, a domain quality score and LLM-generated remediation steps.

8h → 1h compliance review · 1,200+ leads
Engagement at scale

Automated personalized push and email copy across Naukri's communications platform, for faster campaigns and systematic experimentation.

+30% CTR · 90% less campaign creation time
Growth & monetization

A referral acquisition channel built on personalized QR cards shipped with customer orders.

$1.9M revenue · +20% AOV · +13% retention

Experience

Professional experience

Senior Product Manager (Consultant)

MonetizeMore · Traffic Cop
Aug 2025 – May 2026AdTech · B2B SaaS

Led a fixed nine-month mandate to turn Traffic Cop from a support-heavy toolset into an AI-first, monetizable product line, protecting 550+ publishers and $156M in annual ad revenue.

  • Tripled ARR from $2M to $6M through end-to-end product strategy and execution, delivering the defined scope on schedule.
  • Cut fraud analysis from 9 hours to 1 hour per domain with an AI-powered IVT Explainer that became a primary sales demo for upsells.
  • Launched Ad Policy Grader 0-to-1, automating 78 Google policy checks and reducing compliance review time from 8 hours to 1 hour; deployed for 1,200+ leads.
  • Reduced churn by 30%, protecting about $900K in at-risk ARR through analysis of 200+ churn cases and a unified retention playbook.
More impact
  • Increased average deal ACV 2.4× through a premium and bundle pricing redesign.
  • Improved landing-page lead conversions by 60%.
  • Generated $55K from new revenue lines.

Product Manager II

Info Edge · Naukri.com
Dec 2023 – Jul 2025Recruitment technology · 20M+ users

Owned app engagement, retention, GenAI initiatives and communications for Naukri's jobseeker platform.

  • Built a GenAI communications engine powering 90M+ monthly messages, lifting CTR by 30% and reducing campaign creation time by 90%.
  • Generated ₹90L in revenue through a Women's Day career event that engaged 2M users and onboarded 300+ partner brands; partner diversity listings saw 8.3× applications.
  • Increased notification clicks by 65% through ML-based multi-arm bandit experimentation.
  • Won the Info Edge Merit Award for an iOS revamp that cut app load time by 50% and raised the App Store rating from 4.4 to 4.7.
More impact
  • Recovered 25% of opted-out users through re-permission flows on high-intent journeys, leading to a 28% increase in job applications.
  • Generated ₹2 Cr in incremental revenue and 90K+ registrations for Coding Ninjas Masterclass.

Senior Product Manager

eShakti.com
May 2021 – Dec 2023Custom fashion e-commerce

Owned the web and app product roadmap, growth and customer acquisition for a custom women's apparel brand serving customers across the US and Europe.

  • Grew app MAU by 63% YoY, installs by 38% and app revenue by 27%.
  • Improved conversion by 43% with swipeable custom-style recommendations and tailored imagery across 40+ collections.
  • Built a QR-card referral program shipped with orders that generated $1.9M in revenue.
  • Generated $2.2M in revenue at 22% higher ROI while managing a $5M advertising budget across 60+ campaigns.
More impact
  • Scaled Amazon US revenue 2.5×, from $180K to $450K.
  • Shipped an India-focused D2C app in 30 days, reaching ₹5 Cr ARR.

About

How I work

I combine customer research, funnel data and rapid prototyping to solve the right problem before scaling a solution. I connect product decisions to revenue, retention and efficiency, and use experiments to validate assumptions before committing significant engineering effort.

Skills

AI product & automation
GenAI product development · LLMs and agentic AI · n8n and workflow automation
Growth & monetization
Product-led growth · Pricing and monetization · Acquisition and retention · Funnel optimization
Data & experimentation
SQL and Python · A/B testing and experimentation · Analytics and product metrics

Tools: Firebase, Mixpanel, Jira, Tableau, Salesforce

Education

  • MBA, IIM Ahmedabad2019 – 2021
  • B.Tech., DA-IICT2015 – 2019

Earlier experience

  • Futures First · Financial Market Analyst2019

    Selected as 1 of 4 analysts from 500+ applicants. Traded sugar futures and options, intraday and algorithmic, for $20K in trading profit.

  • FinIQ Consulting · Product Design Intern2020

    Led a team of 5 interns on BFSI products; won the ₹10K prize for the best investment-dashboard UI.

  • Teach for India · Project Consultant2021

    Developed the marketing strategy, business model and investor pitch.

Outside work

State-level volleyball player and former captain of the IIM Ahmedabad and DA-IICT teams; recently picked up badminton & acing it! Also adventure sports, bike riding and fiction.

Contact

Let's talk

Open to Senior PM and AI product roles. The quickest way to reach me is email or LinkedIn.

Email
piyushajmeria1@gmail.com
Phone
+91 81097 15078
LinkedIn
in/piyush-ajmeria ↗
Résumé
View on Google Drive ↗
AI product development · MonetizeMore

IVT Explainer & Recommendation Agent

Problem and context

Traffic Cop protects 550+ publishers from invalid traffic (IVT). When a domain was flagged, explaining why and what to do about it was manual analysis work that took about 9 hours per domain.

Goal

Automate domain-level behavioral analysis and give each publisher specific remediation steps, without an analyst working through every flagged domain.

My role and ownership

Product owner. I co-shipped the agent with the ML team as part of the mandate to make Traffic Cop AI-first and monetizable.

Key product decisions

Execution and collaboration

Built with the ML team alongside a revamp of the IVT dashboard, which added metric baselines, risk-level thresholds and the value of impressions Traffic Cop prevented.

Results and business impact

0-to-1 product launch · MonetizeMore

Ad Policy Grader

Problem and context

Publishers risk losing ad revenue when their sites break Google ad policies. Checking a site for compliance was manual and took about 8 hours.

Goal and success metrics

Automate the compliance review, score domain quality, and test whether the grader could stand on its own commercially, with a clear go or no-go within a single quarter.

My role and ownership

Owned the product end to end, from 0-to-1 build to pricing, report delivery and the commercial experiment.

Key product decisions and trade-offs

Execution and collaboration

Replaced manual report creation with a Python-to-HTML pipeline that turns raw scan output into audit reports, delivered by email. To test a B2C self-scan version, I built a freemium agent on my own in n8n: scan ingestion, an LLM-gated teaser PDF with an embedded payment link, and the full report unlocking on payment.

Results and business impact

Learnings

The freemium experiment gave a clear answer at low engineering cost: the data did not support the B2C self-serve direction, so I made the call to stop it.

Engagement at scale · Naukri.com

GenAI Communications Engine

Problem and context

Naukri sends push notifications and emails to a 20M+ user base. Writing copy by hand slowed campaigns down, and copy that ran unchanged for a long time lost engagement.

Goal

Generate personalized copy at scale so the team could launch campaigns faster and experiment continuously.

My role and ownership

I owned the communications charter and built the tool.

Key product decisions

Results and business impact

Growth & monetization · eShakti

QR-card Referral Program

Problem and context

eShakti sells custom women's apparel to 1M+ customers in the US and Europe.

Goal

Turn existing customers into an acquisition channel for new customers.

My role and ownership

Owned the program as part of the web and app growth roadmap.

Key product decisions

Results and business impact