AI Product Manager

<div class="content-intro"><p data-pm-slice="1 1 []">Groupon connects 42 million customers with local experiences - restaurants, events, wellness and travel - and the million-plus merchants who deliver them. Our mission is to get people offline and into the real world at prices that make it possible. We're an AI-native company in the middle of a platform transformation, moving from a deals marketplace to an experience discovery platform that works for customers and merchants at the same time.</p> <p> </p></div><p>Groupon's post-purchase funnel — voucher delivery, redemption, repeat engagement — is a direct lever on repeat purchase rate, lifetime value, and refund costs. This role owns that entire funnel with a mandate to move those numbers, using AI as the primary method of doing so. When this hire is working well, the metrics shift in a way the business can measure quarter over quarter.</p> <h4><strong>Who you'll work with</strong></h4> <p>Report to Jason Wong, Group Product Manager, Customer Experience & Trust. You'll work directly with engineers and designers across web and mobile. <strong>One honest signal: this is a high-ownership, low-handholding role</strong>. You define the metrics, run the experiments, and make the calls. If you need consensus before moving, the pace here will be uncomfortable.</p> <h4><strong>What you'll be doing</strong></h4> <ul> <li>Owning the complete post-purchase journey from voucher delivery through redemption and repeat engagement, with every metric in that funnel yours to move</li> <li><strong>Building AI-driven features </strong>— personalised post-purchase communications, automated refund prevention, predictive churn signals — and taking them from concept to live production yourself, not handing off to a separate AI team</li> <li>Using AI tools in your daily product work: research synthesis, prototype generation, experiment design, data analysis — applied before engineering is involved, not as a finishing touch</li> <li>Designing and running A/B tests with documented hypotheses and instrumentation confirmed before launch, so every experiment produces a learning, not just a result</li> <li>Defining and tracking repeat purchase rate, time-to-next-buy, redemption success, and refund costs, and building the roadmap that moves them</li> <li>Maintaining consistency across web and mobile so the post-purchase experience doesn't fragment by platform</li> </ul> <h4><strong>What success looks like</strong></h4> <p>Day 30: Post-purchase funnel fully audited. Top three metric levers identified with supporting data. You can name the biggest AI leverage point in the funnel that nobody has acted on yet.</p> <p>D