Ahmed Hassan
Senior Product Manager | Consumer Growth & AI | Builder
Career
I’m a Growth Product Manager and builder with 6 years of experience building and growing consumer products at Coinbase, Gemini, and Morgan Stanley.More recently, I’ve been building Yigri, an AI-powered running platform for iOS and web. I work across product, design, and engineering, using Swift, TypeScript, SQL, APIs, data pipelines, and AI tools to turn ideas into products people can actually use.I enjoy starting from zero, talking directly with users, and figuring out what to build when there isn’t a roadmap yet. Check out some highlights below.
Things I've Built
I’ve been building things since I was a teenager, from starting a photography business and mentorship programs to experimenting with consumer products. Most recently, I’ve been building Yigri, an AI-powered running platform for iOS and web. Click below to see some magic.
Things I enjoy as well
Fashion design
Long distance running
Landscape photography
Let's Connect
Enjoyed reading through this? Feel free to reach out and connect with me on LinkedIn
Highlight Reel
Some products that I'm exceptionally proud of. These products have driven large-scale impact and were all 0--> 1 efforts.
Yigri: AI-Powered Running Insights Platform
Coinbase: Building & Scaling Referrals
Gemini: Increasing Activation & Engagement
© 2026 Watch Ahmed
Gemini (2025-2026)
Senior Growth PM
OverviewAt Gemini, I own global activation and early lifecycle strategy (First 30 days) across core trading and the credit card product.My focus is on helping new users understand value quickly, reducing friction to first trade, and increasing long-term retention through product-led growth systems.
HighlightsActivation & First Trade
Improved onboarding and first-trade flows, increasing conversion ~20%.Retention Growth
Built activation paths into staking, credit card ownership, and recurring buys, driving 1,000%+ retained user growth.Referral Growth
Expanded referral discovery, growing referring MTUs from 7% to 18% and increasing referral-sourced first traders by 55%.Experimentation Framework
Build out product experimentation framework for the Growth orgIn-Product Education
Launched contextual prompts and notifications to drive adoption of staking and recurring buys.
New User Activation
We identified that fewer than 15% of new users completed a first trade within their first 7 days, creating a major activation drop-off.Through UX audits and user research, we found that many users were unsure how to fund their wallet and execute their first transaction.To address this, we launched a guided onboarding activation checklist that:- Clearly outlined the steps required to start trading
- Surfaced relevant new-user offers at the right moment
- Reduced decision paralysis by deep-linking users into a preset BTC purchase flowFollowing launch, we drove an approximately 20% increase in 7-day activation rates.
Increasing Discovery
Fewer than 5% of new users engaged in any actions beyond basic crypto trading, limiting early activation and long-term LTV.To address this, we embedded contextual educational content directly into the product experience, highlighting the value of higher-retention actions such as staking and setting up recurring buys.Through a combination of in-app education and GTM support, we increased the number of new users completing a “sticky” action within their first 30 days by 50%.
Incentives & Sweepstakes
As Gemini’s new user growth accelerated in 2025, we identified that ~40% of users churned within 2–3 months of signup, limiting long-term LTV.To address this, I designed and launched targeted incentives that nudged users toward high-retention behaviors such as setting up recurring buys, staking, and credit card adoption, leveraging proven incentive design patterns from prior growth systems.Within four months, these incentives (alongside educational content) drove a 1,000%+ increase in retained MTUs, defined as users with at least one durable retention behavior.
Coinbase (2024)
Consumer Growth PM
OverviewOwned 0→1 growth products across referrals, incentives, and lifecycle surfaces to drive trader acquisition, activation, and revenue at global scale.
HighlightsGlobal Referrals
Launched and scaled referrals to drive $40.2M in revenue and capture 11.4% of all new traders on Coinbase.Incentives Platform
Built a self-serve rewards system enabling global marketing experimentation and faster campaign launches.In-App Rewards Hub
Unified all offers into a single discovery surface, increasing offer conversion by 42%.Growth Experimentation
Led cross-team experimentation to improve visibility, conversion, and user lifetime value across offers.
Referrals
With paid acquisition channels averaging >$400 CAC, there was an opportunity to leverage Coinbase’s existing user base to drive more efficient, product-led growth.We launched an initial referrals MVP using trading-fee reductions as the incentive, which generated moderate lift in new users and revenue. Based on early learnings and user research, we iterated to a monetary incentive model, unlocking significantly higher acquisition and trading revenue.After proving ROI-positive unit economics, we expanded the program globally across LATAM, APAC, and EMEA, driving hockey-stick growth. We continued to scale impact by improving referral discoverability across the product, gamifying the referral experience, and strengthening go-to-market execution.By the end of 2024, referrals accounted for >10% of all first-time traders at Coinbase and became the company’s most efficient acquisition channel, outperforming paid marketing.
Rewards Hub
Coinbase offered 7+ ways for users to earn rewards across multiple app and web surfaces. Because discovery was fragmented, most offers saw <10% CTR, leading to underutilization and lower-than-expected user LTV.To address this, we partnered and aligned with marketing and product teams to design a unified Rewards Hub that centralized all incentives and offers into a single discovery surface.During experimentation, we faced a key trade-off: while overall consumer revenue increased, learning reward revenue declined after removing its dedicated surface. However, users engaging through the Rewards Hub generated higher trading revenue and higher LTV compared to users interacting only with learning rewards.Based on these outcomes, we rolled out the Rewards Hub, prioritizing long-term user value and overall monetization over optimizing a single reward category.
Growth Marketing / Acquisition
As Coinbase scaled global growth marketing and partnerships in 2024, marketing and product teams needed customizable, easy-to-deploy incentives across a wide range of use cases, from paid campaigns to in-product promotions.To meet this demand, I partnered with engineering to build a self-serve Rewards Platform that enabled product and marketing teams to create, configure, and launch incentives in minutes rather than months.The platform was tightly integrated with our experimentation infrastructure, allowing teams to easily A/B test incentive types, values, and placements across marketing and product surfaces.As a result, we increased experimentation velocity by 70% for marketing partners and drove approximately $7M in platform-attributed revenue.
Morgan Stanley (2020-2023)
Client Experience PM
OverviewLed client-facing and internal platform products across wealth management and payments, focusing on operational efficiency, client experience, and streamlined workflow management.
HighlightsDigital Advisor Platform
Shipped online scheduling with a virtual advisor to 150k+ wealth clients, increasing advisor interactions by 34% and assets under management (AUM) by 4% in Q2 2021.Fully Paid Lending
Launched a stock lending product for HNW clients, achieving 40% enrollment and reducing institutional borrowing costs by 18% within 5 months.Ops Workflow Platform
Unified and automated Morgan Stanley and E*TRADE operations workflows via REST APIs, increasing daily output by 34% and reducing per-workflow time by 26%.CRM Consolidation Strategy
Led Buy vs. Build CRM decision, saving $200k+ annually in contract costs.
Yigri
(2026)
AI-powered Running Insights Platform
OverviewYigri started with a problem I kept running into as a runner: I had more training data than ever, but very little understanding of whether my training was actually working.Most running apps either tell you what to do or show you what you did. Yigri closes the loop between the two. It brings together your training plan, completed workouts, health data, and other context to understand how you're training and whether you're improving.Yigri then turns that data into simple, personalized insights that explain what’s changing, why it’s happening, and what you should pay attention to next.
How Yigri works
Yigri brings together fragmented training data and turns it into one structured view of how a runner is actually progressing. From there, it combines deterministic scoring with AI-powered interpretation to generate clear, personalized feedback instead of another dashboard full of raw metrics.
What I Built
I built Yigri from the ground up across product, design, data, and engineering. That includes the iOS and web experiences, data models and pipelines, third-party integrations, scoring systems, and the AI layer that turns training data into useful feedback.I’m still hands-on in the codebase today, working across Swift, TypeScript, SQL, APIs, and production debugging as the product evolves.
How I Build with AI
AI is part of how I build, not just a feature inside Yigri. I use it throughout the development loop, from exploring a user problem and prototyping solutions to implementation, debugging, testing, and iteration.The goal is to compress the distance between “this should exist” and “this is working in production” as much as possible.
This is the kind of workflow I aim for: listen closely to users, investigate deeply, fix the root cause, validate the outcome, and use the learnings to make the system more resilient going forward.
Where is Yigri today
Yigri is still early, but it has already gone from a personal idea to a working product processing real training data and generating ongoing insights for runners.
HiLo
(2025-2026)
AI-powered fashion discovery and recommendations
OverviewHiLo started with a simple problem: discovering new clothing brands that match your personal style is surprisingly difficult.I built an AI-powered discovery experience that let shoppers use outfits and products they already liked to find new brands and pieces that matched their preferences across fit, style, and price.Over time, I experimented with multimodal search, product recommendations, and AI-native discovery. The product began getting organic discovery through AI assistants, which led me to explore how shopping products could increasingly be built for both people and agents.
Sparrow Running
(2023-2024)
Personalized Running Coach
OverviewSparrow Running was created to remove the confusion and intimidation from training for your first race.Many new runners struggle with inconsistent plans, information overload, and a lack of confidence in how to structure their training.Sparrow simplifies the process by generating goal-based, personalized weekly running plans so users can focus on showing up and enjoying the journey.The goal is to make endurance training feel approachable, motivating, and achievable.
The Minority Network
(2019-2022)
Connecting underrepresented students with career opportunities and mentors
Overview
The Minority Network was built to close the information and access gap between underrepresented students and career opportunities.While many organizations aim to diversify their workforce, underrepresented students often lack clear pathways to mentors, programs, and resources.The platform connects students with mentors, opportunities, and diversity initiatives in one accessible hub.The mission is to make career exploration and advancement more equitable, visible, and attainable.
Fashion Design
Sample of a cropped trouser with a pleated reveal panel
Long Distance Running
New York City Marathon
Time: 3:16
Landscape Photography
Images from Portugal, Iceland, and Columbia
