Customer Insights & CDP Manager Lead

職務概要

We are hiring a Customer Data Platform (CDP) & Customer Insights Manager / Lead to build and lead our customer intelligence function (based in Vietnam, focused on the US market). This is a founding leadership role where you will: - Define how we understand our customers across a multi-brand portfolio using Customer Data Platform architecture - Build the strategy, team, and operating model for CDP and customer insights from the ground up - Partner directly with senior leadership (including ex-consultants from Bain, AC Nielsen, Google, Tiki, Trusting Social) to drive retention, loyalty, and customer lifetime value (LTV) You will sit at the intersection of strategy, analytics, and execution, working with a strong AI (LLM) and data engineering team that is building data → insights → action loops. What You'll Own - Set the vision & strategy: • Define the end-state vision for consumer insights, engagement, and retention across our retail and ecommerce portfolio • Translate business goals into a clear roadmap for customer understanding, segmentation, and lifecycle management - Build the function & team: • Design and build the CDP & Customer Insights function from 0 to 1 – including CDP infrastructure, processes, operating cadence, and best practices • Over time, hire, manage, and develop a small team of data analysts / customer insights specialists to scale the function • Establish ways of working with Product, Marketing, Operations, and the AI/Data teams - Design customer & retention programs: • Implement Customer Data Platform (CDP) to unify customer data across all touchpoints, brands, and channels • Build customer segmentation frameworks, cohort models, lifecycle stages, and behavioral triggers from the ground up • Design and test retention and loyalty programs, lifecycle campaigns, win-back strategies, and personalized engagement initiatives that drive measurable LTV and revenue uplift • Create customer health scoring, churn prediction models, and next-best-action recommendations - Lead through doing (player-coach): • Be a player-coach: comfortable both setting direction and being hands-on in the data • Build dashboards, design analyses, and structure A/B tests to identify what drives retention, purchase frequency, and ARPU • Use SQL, Python, and BI tools (Tableau, Looker, Power BI) to wrangle data and extract insights • Develop predictive models for customer lifetime value (CLV), churn risk, and expansion opportunities - Leverage AI and modern data tools: • Partner closely with our AI and data engineering teams to use LLMs and modern data stacks to analyze customer behavior at scale • Turn messy, complex data into clear, actionable narratives and recommendations - Own measurement & insight storytelling: • Define and track the KPIs that matter (customer health, cohort performance, retention rate, Net Revenue Retention (NRR), LTV, churn, etc.) • Build reporting and insight packs that help leadership make fast, data-backed decisions • Communicate insights in a structured, consulting-quality way (problem → approach → insight → recommendation → impact) • Establish attribution frameworks connecting CDP initiatives to revenue outcomes