The E-commerce Customer Lifecycle & Merchandising Strategist will own day-to-day site operations and assist in the implementation of AI-powered engagement strategies across Positive Grid's digital touchpoints.
This role focuses on orchestrating personalized customer journeys that prioritize meaningful engagement over traditional transactions. The specialist will leverage AI tools to automate processes, analyze customer behavior patterns, and implement ecosystem-based merchandising strategies that connect customers with the right products at the right moments in their musical journey.
This position requires a balance of attention to detail, analytical thinking, creative problem-solving, and a deep understanding of how AI can enhance the customer experience. The role collaborates extensively across departments to ensure a unified approach to customer engagement through our digital platforms
【Your Team】
This position will report directly to the Sr. Manager of Ecommerce Merchandising & Operations.
【What We Offer】
-Opportunity to collaborate with talented international teams.
-Inclusive and diverse work environment.
【Typical Accountabilities】
-Own the development of site merchandising strategies and their day-to-day execution.
-Develop and implement AI-powered personalization strategies that prioritize customer engagement and journey optimization over traditional transaction metrics.
-Configure, optimize, and evaluate AI algorithms that dynamically personalize product recommendations, content delivery, and on-site experiences based on customer behavior patterns.
-Lead the implementation of ecosystem-based merchandising strategies that showcase product interconnections and create seamless cross-product customer journeys.
-Design and optimize engagement-focused metrics and KPIs to replace traditional conversion-centric measurements, ensuring alignment with company's strategic shift.
-Automate routine merchandising tasks through AI tools, workflow improvements, and process optimization to increase team productivity and operational efficiency.
-Collaborate with data science team to develop, train, and refine machine learning models that predict customer preferences and optimize merchandising strategies.
-Implement and manage A/B testing protocols that evaluate engagement quality over simple conversion rates.
-Work cross-functionally to integrate AI-driven insights into merchandising strategies across all customer touchpoints (website, email, app, User Center).
-Build and optimize dynamic customer journey maps that adapt based on real-time engagement signals and behavioral patterns.
- Translate complex AI capabilities and engagement data into actionable merchandising strategies and clear communication for cross-functional teams.
-Maintain and evolve the digital product ecosystem visualization to ensure customers understand the interconnections between Positive Grid products.
-Assist in the implementation of innovative digital merchandising technologies with a focus on engagement enhancement and journey personalization.
-Ensure all AI implementations adhere to privacy standards, ethical guidelines, and transparency best practices.
【Essential】
3+ years of experience in an e-commerce role with focus on digital merchandising,personalization, or customer experience optimization
Strong attention to detail in site merchandising and performing site QA.
Flexible and adaptive to changing priorities;able to organize, multi-task and prioritize workload to meet deadlines.
Demonstrates strong logical, quantitative analysis and problem-solving skills
-Demonstrated collaborative skills and ability to work well within a cross-functional team.
-Demonstrated experience implementing or working with AI-powered personalization
【Desirable】
Experience in the music technology industry or passion for music production
Advanced certification in e-commerce platforms, personalization tools, or AI applications
Knowledge of HTML/CSS, Photoshop and other design or web development tools is beneficial.
Degree in marketing, communications,business or related course of study.
Knowledge of ecosystem-based merchandising approaches and cross-product customer journeys
Experience with machine learning model