Match Group (MTCH) Investor update summary

Product evolution and user outcomes

• Major improvements across nearly every aspect of the product, including trust and safety, recommendations, and new social features like Double Date and Events.

• Prevalence of bots and bad actors reduced by over 60%, enhancing user safety.

• Product and engineering teams restructured into smaller, more autonomous units, enabling faster decision-making and execution.

• Unified focus on a single North Star metric, Sparks, aligning teams around high-quality user conversations.

• Regular assessment and removal of underperforming features to ensure all product elements address clear user needs.

Engineering transformation and AI integration

• Engineering velocity has doubled year-over-year due to fewer handoffs, tighter collaboration, and rapid experimentation.

• Significant investments in rearchitecting core systems, such as chat, and upgrading infrastructure to support faster development.

• Over 90% of new code is AI-generated, with AI agents assisting in coding, testing, and bug fixing under human oversight.

• AI accelerates the product development lifecycle, compressing months of work into weeks or days.

• AI is used both to enhance user-facing features (onboarding, recommendations, safety) and to streamline internal processes.

Recommendation system advancements

• Transitioned from multiple independent recommendation decks to a unified system optimizing for Sparks, leading to significant improvements in user engagement.

• Real-time adaptive recommendations, set to launch in late Q4, will allow the system to respond to user behavior changes within seconds.

• Continuous major updates to recommendations indicate the system is still in early stages of optimization.

• Increased transparency and user control over recommendations, allowing users to provide feedback and adjust preferences.