I’m a product leader with 15+ years of experience building products at the intersection of AI/ML, personalization, marketplace platforms, and navigation systems. I’ve built 0-to-1 products at Amazon, scaled teams at Uber and GoDaddy, and led AI transformations that shifted how organizations operate.
I hold an MBA from Duke University’s Fuqua School of Business and a B.Tech in Electronics Engineering from the Indian Institute of Technology (IIT), Varanasi. Before product management, I was a software engineer — I’ve written production code, debugged ranking algorithms, and built browser extensions from scratch. That technical foundation shapes how I lead: I go deep on the problem before I go wide on the solution.
I’m currently based in San Francisco. You can find me on Twitter and LinkedIn, or reach me at pushkarprateek@gmail.com.
Experience
Intuit
Principal Product Manager — Digital Help Experience
San Francisco, CA · Jul 2025 – Present
At Intuit, I lead the AI-powered Agent Assist platform and self-serve AI support experiences — the systems that help millions of TurboTax, QuickBooks, and Mailchimp customers get answers faster, and help support agents resolve issues more accurately.
This role sits at the intersection of two things I care deeply about: using AI to transform how organizations operate, and building products that serve both the end customer and the internal operator simultaneously.
AI-Powered Agent Assist Platform
Intuit’s support agents handle some of the most complex product questions in consumer software — tax law, accounting workflows, marketing tools. I’m leading the platform that puts AI directly into their workflow, surfacing the right guidance at the right moment during live customer interactions. The goal isn’t to replace agents — it’s to make every agent perform like the best agent on the team.
AI Product Recommendation Engine
I shipped the company’s first AI-driven product recommendation engine for TurboTax support agents. Rather than relying on agents to remember the full product catalog and manually match solutions to customer needs, the system analyzes the customer’s context and recommends the right product in real time. This improved recommendation rates by 27% — meaning more customers are getting pointed toward the product that actually solves their problem.
The support experience I own has driven 225% year-over-year revenue growth — not by pushing harder on sales, but by making the support interaction itself more useful. When you help customers find the right answer faster, the commercial outcome follows naturally.
GoDaddy — Director of Product
Director of Product Management — Digital Care & Care Platform
San Francisco, CA · Oct 2022 – Jul 2025
I joined GoDaddy’s Care organization at a pivotal moment. Care was viewed as a cost center — leadership and Operations were optimized for weekly revenue and short-term efficiency. GenAI was emerging as a potentially transformative lever, but there was deep skepticism, limited technical fluency, and real change resistance across the organization.
My job was to change that. I led a 15-person product org across two teams — Digital Care and Care Platform — and drove the full AI transformation of how GoDaddy supports its customers.
The Care AI Vision
I didn’t walk in with a finished roadmap. I started with education — running targeted GenAI sessions tailored for highly non-technical stakeholders, using concrete, day-in-the-life use cases instead of abstract AI concepts. The goal was to shift the conversation from “AI as a risk” to “AI as an operator multiplier.”
Then I reframed the opportunity. While customer-facing chatbots were the obvious starting point, I identified that the real 0-to-1 unlock would come from empowering every Care agent with a role-specific AI assistant. That insight led to GABI — our Generative AI Agent Assist platform.
Critically, I built the vision jointly. Instead of presenting a fully formed strategy, I worked closely with Operations, Support leaders, and frontline teams to co-create use cases. By letting stakeholders extrapolate from simple examples to their own workflows, the Care AI vision became something they helped author — not something imposed on them.
The result: Care AI became one of GoDaddy’s top strategic bets — referenced in earnings calls. The platform consistently delivers multi-x ROI on invested dollars while materially improving agent efficiency and customer outcomes.
GABI: Building Trust in AI (The Hard Way)
GABI’s launch taught me one of the most important lessons of my career: in high-stakes AI systems, sophistication matters far less than trust.
We launched with strong initial excitement and early agent adoption. Then adoption dropped sharply. We tried the obvious fixes — training, reducing friction with a “one-click guidance” feature. Nothing worked.
The breakthrough came when I visited one of our offshore BPO centers and shadowed agents directly. The root cause was trust. Agents operated in a high-stakes environment where accuracy directly affected their performance metrics. Even occasional AI inaccuracies were enough for them to reject the tool entirely. I also uncovered a cultural barrier: agents felt uncomfortable giving direct negative feedback to product and engineering teams.
I rebuilt trust deliberately — through informal conversations, empathy, and consistent presence. We changed the entire roadmap away from impressive AI features and focused relentlessly on fundamentals: accuracy, latency, and confidence signaling. GABI’s adoption recovered from single digits to roughly 50%.
Building the Team
When I took over the Care PM team, most PMs had grown internally from customer support roles — deep customer empathy but limited product craft. I raised the baseline with templates and example docs, created coaching loops through weekly reviews and peer critiques, and paired PMs based on complementary strengths.
The result: We grew from 3 to 12 PMs managing $40M+ in annual impact. The team delivered GoDaddy’s first enterprise GenAI platform, led the Care AI transformation, and implemented a hybrid CRM strategy saving $10M annually. Two original PMs were promoted to Senior PM roles.
Uber
Product Lead — Maps, Routing & Navigation
San Francisco, CA · Jun 2020 – Oct 2022
I was the first dedicated Product Manager for Uber Navigation — the product that hundreds of thousands of drivers use for 80% of their working hours. Despite its critical role, Navigation was severely under-resourced when I arrived: 6 engineers, no dedicated design support, and no clear product vision.
I authored the 3-year Uber Maps Navigation vision, scaled the team from 6 to 22, and built what the CEO later described as one of Uber’s “secret sauces” for drivers.
Repositioning Navigation as a Strategic Asset
I assembled a cross-functional task force across engineering, design, research, and data science. We ran deep discovery — interviews, surveys, journey mapping, and large-scale analysis of open-ended feedback across markets. I tied every piece of the vision to concrete business outcomes and presented it across 10+ executive sessions.
The team grew from 6 to 22 engineers with dedicated designers. Navigation became a regular topic in CPO updates. My 2-PM team consistently exceeded half-yearly targets — crushing the H1 2021 org-wide target by 2.5x.
Driving Customer Obsession Across the Org
When I joined, the org was heavily engineering-driven. Customer research was sporadic. Every prioritization conversation turned into a standoff — people arguing from opinion, not evidence.
I reframed the problem to leadership: we’re not disagreeing on priorities — we’re disagreeing in the dark. I secured a researcher, led a multi-phase study across riders and earners, and my team and I went through over 1,000 raw responses ourselves.
The data dissolved the internal debate. We shaped the Maps roadmap for the next two years. I was named the org’s user research champion, secured two dedicated UXR roles, and set up always-on listening pipelines so the team would never go blind again.
Key Initiatives
Uber South Korea Launch (+$65M GB/year) — Volunteered to own the rider experience for a uniquely challenging market. Coordinated with product managers across the company to modify product funnels from onboarding to payment for a market where 90% of drivers were over 70 and credit card adoption was limited.
Intersection Safety Assistance (AI/ML) — 6% Reduction in Dangerous Driving — Partnered with the safety org to analyze hundreds of incidents, found a pattern at 2-way stop signs, and collaborated with UberAI to build an ML model alerting drivers about cross-traffic behavior. The CPO featured it in Uber’s global all-hands.
Side-of-Street Rendezvous — 4% Reduction in Cancellations — Improved marketplace coordination between riders and drivers at pickup.
Driver Off-Trip Map Experience — 0 to 30% Adoption — Built the between-trips map experience to improve marketplace dynamics.
GoDaddy — Senior Manager
Senior Manager, Product — Customer Experience
Kirkland, WA · Aug 2018 – Jun 2020
My first stint at GoDaddy — before I returned as Director to lead the Care AI transformation. I owned two of the company’s highest-leverage customer experience surfaces: the activation funnel (personalization) and site navigation. I also built the company’s experimentation practice from scratch.
ML-Driven Personalization (+30% Conversion, +$25M Revenue)
GoDaddy’s domain purchase path is the most trafficked funnel on the site, but customers faced decision paralysis choosing among multiple website-building and email products. I partnered with the experimentation engineering team to build an ML classification model that analyzed 200+ data signals per customer and predicted the product with the highest purchase propensity.
The ML-driven hero card saw a 60%+ lift in conversion. I was the first to implement propensity-based personalization at GoDaddy, leading to company-wide adoption of similar approaches.
Site Navigation Overhaul (+$10M Revenue)
I led a complete overhaul of GoDaddy’s site navigation during a major brand redesign. Rather than shipping everything at once, I broke the design into 6 sequential experiments with zero gaps between them — coordinating across 3 engineering teams, 3 design teams, 6 product marketing teams, and international stakeholders. We implemented the rebranded navigation without any negative impact to revenue metrics.
I was awarded the “Getting $hit Done” award — one of GoDaddy’s most prestigious employee honors — and named company-wide “Experimentation Ambassador.”
Amazon
Senior Product Manager — Last Mile Technology, Amazon Logistics
Seattle, WA · Feb 2017 – Aug 2018
At Amazon, I worked on the systems that power the last mile of delivery. I spent over a month physically inside delivery stations, observing operations and talking to the people who run them. What I found was that Amazon had not provided its station operators the right software to be successful — a typical station used more than 40 different tools throughout the day.
Station Command Center: Replacing 40+ Tools with One (0→1)
I envisioned a single tool that would provide critical data points about the health of all station processes in real time. I built the 3-year product vision, the business case, and led the team through MVP to scale. The product hit its targeted adoption 6 months ahead of schedule with a savings impact exceeding $30M.
Streamlining Driver Return-to-Station (+$10M Savings)
I identified that operators were using 3 different tools and 7 browser tabs just to receive undelivered packages from drivers. I reframed the goal around reducing human judgment and cognitive load to zero. We expected to save 20% of operators’ time — we saved 53%, beating the target by 2.5x.
Learning to Disagree and Commit
A digital checklist project taught me a lasting lesson about principled disagreement. I believed the MVP should allow flexible (non-sequential) completion; leadership disagreed. I committed wholeheartedly but ensured the constraint was built as a reversible flag. Post-launch data proved users were gaming the sequential requirement. Leadership came around, and we reverted. Both sides learned — and I learned the value of building reversibility into decisions when you’re not aligned.
Sears
Senior Product Manager — Mobile, eCommerce Search Relevancy, Marketplace
Hoffman Estates, IL · Aug 2015 – Jan 2017
Sears was my first product management role after business school, and it was a crash course in resourcefulness. I won the “Rock Star Award” — the company’s most prestigious employee honor — recognized personally by the President and SVP.
Fixing Search: The Bug That Changed Everything (+4.6% Conversion Overnight)
I noticed search results on Sears.com were terrible — relevant products buried behind irrelevant ones. I volunteered to investigate even though I wasn’t on the Search team. I dove into software logs, rank calculations, and eventually the code itself. I found a piece of legacy code adding such a large number to the ranking total that it suppressed the entire keyword ranking algorithm. Millions of lines of sophisticated logic — rendered meaningless by one overlooked calculation that had been there for years.
We shipped the fix without the luxury of an A/B test, with holidays approaching. The result: 4.6% lift in conversion overnight. Year-over-year differential jumped 334%.
Sears Intelligence: The Chrome Extension That Went Viral
Sears.com was plagued with duplicate products, mispriced items, and miscategorized listings. No team could prioritize a fix. So I built the solution myself — spending two weeks of nights learning a new coding language to create a Chrome extension that let any Sears employee report bad listings with a right-click.
It spread like wildfire. 8,000 issues reported and resolved in the first week. Two existing projects were scrapped because my tool was better. The CEO backed it personally.
More at Sears
Marketplace Seller Central — Slashed listing friction with innovations like 1-click Amazon-to-Sears catalog import. Search Relevancy Overhaul — Drove a methodical algorithm rebuild that lifted conversion 3.4%. Mobile Notifications — Rallied 10+ teams to build push notifications from scratch, improving engagement metrics 2-5%.
Early Career & Ventures
Movik Networks — Senior Software Engineer
Bangalore, India · Apr 2010 – Jun 2013
At a startup bleeding money with no revenue, I took initiative to pursue a promising client in Japan that management had written off. I taught myself the technology, built the business case, assembled a cross-functional team, and led the execution. In 4 months we launched a new product line, earning the company its first revenue of ~$1M. The VP of Product called it the most beautiful execution he had seen in his lifetime.
Samsung India — Software Engineer
Bangalore, India · Jul 2007 – Mar 2010
Built voice, image, and video-sharing apps for 4 Samsung phone models. Introduced 2 process innovations that cut SDLC time by 25%. Beyond engineering, I led a CSR initiative building sustainable businesses for orphanages — including turning children’s paintings into premium greeting cards that funded an orphanage’s winter needs.
The Drapers (Founded 2005–2009)
Founded a startup delivering affordable, infant-safe garments to maternity clinics in one of India’s poorest states. Built the unit economics, set up manufacturing at home, and convinced clinics to distribute. The result: significantly fewer cases of infant infections and SIDS. It wasn’t a venture that made me rich — but it showed me that product thinking can solve problems that matter.
GustoRead (Founded 2011–2013)
Built a social networking platform for blog readers — from web crawler to ranking algorithm to community features. Page hits increased 200% after V2, but the platform never reached scale. My most valuable “failure” — it taught me the complexities of two-sided marketplaces and the importance of customer acquisition strategy.
Education
Duke University, The Fuqua School of Business — MBA, 2015. Concentration: Product Management and Decision Science.
Indian Institute of Technology (IIT), Varanasi — B.Tech, Electronics Engineering, 2007.