Solving Marketplace Cold Start at Scale as part of the ranking system

Theodore Meynard

Machine Learning & Deep Learning & Statistics
Python Skill None
Domain Expertise Advanced

Cold start cripples two‑sided marketplaces: new items lack behavioral signals and social proof, ranking models under‑expose them, which delays the very signals needed to rank them well. This talk shares our journey to break down this loop at GetYourGuide, a marketplace for travel experiences. We evolved our exploration/activation framework over the past three years with three complementary interventions: guaranteed exposure at strategic positions, a real‑time reranker to allocate that exposure efficiently under tight latency budgets, and guardrail boosting for unactivated items when primary assessment slots are empty.

The talk is a pragmatic case study: we’ll show how experiment‑led exploration shaped the system over the last 3 years. We will share what worked, what did not, and how we managed trade-offs between short-term revenue and long-term marketplace health. Attendees will leave with a blueprint for safely accelerating early traction in their own marketplaces, combining learning‑to‑rank with exposure guarantees without sacrificing overall business health.

Theodore Meynard

Theodore Meynard is a data science manager at GetYourGuide.He leads the evolution of their ranking algorithm, helping customers to find the best activities to book and locations to explore. Beyond work, he is one of the co-organizers of the Pydata Berlin meetup and the conference. When he is not programming, he loves riding his bike and looking for the best bakery-patisserie in town.