Accountabilities

• Own the post-purchase customer journey, focusing on helping paying customers reach a quality match as quickly as possible.
• Optimize offer volume and presentation so customers receive an appropriate number of relevant options without being overwhelmed or underserved.
• Improve recommendation relevance and customer trust in the options presented throughout the experience.
• Increase the volume and quality of relevant invitations received by paying customers.
• Improve the likelihood that new customers form a quality match during their first week.
• Design engagement mechanics such as gamification, nudges, reminders, and conversation reactivation features that encourage customers to return.
• Analyze matching parameters across user segments and use segmentation, personalization, and data enrichment to improve discovery and matching outcomes.
• Identify bottlenecks and growth opportunities in the post-purchase journey using quantitative data, qualitative research, and product insight.
• Translate opportunities into clear, testable hypotheses with defined success metrics and requirements.
• Collaborate with engineers, designers, analysts, and data/ML specialists to deliver product improvements efficiently.
• Manage requirements, priorities, and timelines while maintaining predictable delivery.
• Run A/B tests and other experiments, analyze product metrics and outcomes, and scale improvements that demonstrate meaningful results.

Accountabilities

• Own the post-purchase customer journey, focusing on helping paying customers reach a quality match as quickly as possible.
• Optimize offer volume and presentation so customers receive an appropriate number of relevant options without being overwhelmed or underserved.
• Improve recommendation relevance and customer trust in the options presented throughout the experience.
• Increase the volume and quality of relevant invitations received by paying customers.
• Improve the likelihood that new customers form a quality match during their first week.
• Design engagement mechanics such as gamification, nudges, reminders, and conversation reactivation features that encourage customers to return.
• Analyze matching parameters across user segments and use segmentation, personalization, and data enrichment to improve discovery and matching outcomes.
• Identify bottlenecks and growth opportunities in the post-purchase journey using quantitative data, qualitative research, and product insight.
• Translate opportunities into clear, testable hypotheses with defined success metrics and requirements.
• Collaborate with engineers, designers, analysts, and data/ML specialists to deliver product improvements efficiently.
• Manage requirements, priorities, and timelines while maintaining predictable delivery.
• Run A/B tests and other experiments, analyze product metrics and outcomes, and scale improvements that demonstrate meaningful results.