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AI Product Manager

Groupon Prague, Tschechien
Hybride Arbeit

Veröffentlichungsdatum: 29.08.2026

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. 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.

Responsibilities

Owning the complete post-purchase journey from voucher delivery through redemption and repeat engagement, with every metric in that funnel yours to move; Building AI-driven features — 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; 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; Designing and running A/B tests with documented hypotheses and instrumentation confirmed before launch, so every experiment produces a learning, not just a result; Defining and tracking repeat purchase rate, time-to-next-buy, redemption success, and refund costs, and building the roadmap that moves them; Maintaining consistency across web and mobile so the post-purchase experience doesn't fragment by platform

Requirements

Daily, hands-on use of AI tools in product work: you can walk through a real example from the past week — what you built, what tool you used, and what it produced; Production experience shipping AI or automation features: you understand the gap between a working demo and a live system, and you have closed it; Hands-on A/B testing, funnel optimisation, and cohort analysis — you have designed the experiments and instrumented them yourself, not reviewed someone else's reports; Consumer lifecycle economics: you speak the language of repeat rate, LTV, redemption drop-off, and refund cost, not just feature outcomes; The ability to defend a commercially ambiguous prioritisation call to engineering, design, and commercial leadership with data and a clear point of view
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