Adecco is looking for Global Lifecycle Marketing Analytics in New York, NY. This local job opportunity with ID 3700171759 is live since 2026-06-03 17:51:29.

Adecco Creative is partnering with a luxury fashion house to recruit for a Global Lifecycle Marketing Analytics role. This position will be temp to perm and a hybrid schedule in Midtown Manhattan. Proficiency in SQL is a must.

Key Responsibilities:

• Own the measurement framework for global email and SMS, aligned to brand's intent-led lifecycle model (See / Think / Do / Care)
• Define and operationalize KPIs by lifecycle stage and customer intent (e.g., engagement, conversion, repeat purchase, reactivation)
• Measure performance of triggered, behavior-based programs (browse, cart, post-purchase, win-back) and identify opportunities to improve results
• Analyze customer movement across lifecycle stages and quantify drivers of acquisition, engagement, retention, and reactivation
• Build reporting that tracks both campaign performance and list health (growth, engagement, churn, reactivation)
• Partner with Lifecycle Marketing to prioritize and evaluate tests (targeting, timing, content, channel) and scale what works
• Quantify the impact of lifecycle marketing on revenue and efficiency, including its role in reducing reliance on paid media
• Apply advanced analytics and AI (e.g., propensity models, recommendations, send-time optimization) and measure their incremental impact
• Partner with Data Science, Martech, and Engineering to ensure accurate tracking, clean data, and scalable measurement solutions
• Communicate insights clearly and tie findings directly to actions and business outcomes

Qualifications:

• 5+ years of experience in lifecycle marketing analytics, CRM analytics, or a related field
• Deep experience measuring and optimizing email and/or SMS programs at scale
• Strong proficiency in SQL and experience working with large, complex datasets
• Experience building dashboards and reporting in tools such as Tableau or Looker
• Proven experience designing and analyzing experiments (A/B testing, holdouts, incrementality)
• Strong understanding of lifecycle metrics (engagement, conversion, retention, churn, LTV)
• Experience using AI-powered tools to improve analytical efficiency, insight generation, or decision-making
• Experience applying or evaluating AI/ML in marketing (e.g., propensity models, recommendations, send-time optimization)
• Ability to translate analysis into clear actions and business impact
• Experience partnering cross-functionally with marketing, data science, and engineering teams
• Strong communication skills with the ability to influence non-technical stakeholder