Job Description
We are seeking an Assistant Manager in Customer Experience - Loyalty to support and lead initiatives that increase owner engagement, strengthen customer relationships, and ultimately drive repurchase. This is not a rewards-based loyalty role ; it focuses on using behavioral data, predictive model outputs, loyalty indicators, and customer insights to shape activation across the enterprise.
This role is ideal for candidates who are strategic first , but who also bring enough analytical fluency to dive into data when needed . You will not serve as a sole developer or data engineer, but prior hands-on experience with query languages, data platforms, or BI tools enables you to collaborate effectively with analytics and convert insights into actionable loyalty strategies.
You will operate independently, exercise strong judgment, and solve non-standard problems. While working under guidance, you are expected to own outcomes , propose innovative solutions, and influence cross-functional teams without direct authority to improve loyalty and reduce defection.
Key Responsibilities:
Loyalty Strategy & Insight Translation
Develop and refine loyalty strategies using owner behavior trends, predictive model outputs (e.g., propensity scores), and engagement indicators that directly inform owner engagement, retention, and repurchase actions.
Independently analyze customer, digital, and service data to identify specific, actionable loyalty drivers, opportunity areas, and owner pain points.
Translate insights into clear tactical outputs including audiences, triggers, integrated journey improvements, targeted campaigns, or next-best-action logic to drive action.
Build customer lifecycle and loyalty activation frameworks, ensuring they are paired with practical action steps that guide cross-functional teams toward measurable outcomes.
Break down broad loyalty challenges into prioritized initiatives, using structured problem solving and data-driven reasoning to move concepts into execution.
Partner with analytics and marketing to validate insights through a test-and-learn approach, ensuring tactics are continually optimized based on results.
Analytics Partnership
Shape requirements for dashboards, predictive models (e.g., customer lifetime value, churn, etc.), and data assets by clearly defining business needs and articulating expected value.
Translate data, predictive model outputs, and insights into customer loyalty strategies
Manage and prioritize analytics backlog items tied to loyalty outcomes, using sound judgment in ambiguous data environments.
Partner with analytics teams to interpret complex data and propose alternative approaches when precedent is limited.
Balance independence with awareness of when to escalate or seek deeper technical expertise.
Activation & Cross-Functional Influence
Activate insights by developing audience definitions, targeting strategies, and next-best-action recommendations.
Partner closely across CRM, marketing, CX, and additional Enterprise functions to connect insights to activation pathways.
Use clear, data-backed storytelling to influence decisions and anticipate objections.
Serve as a connector across teams, driving alignment and supporting enterprise repurchase initiatives without direct authority.
Business Case & Operational Impact
Build data-driven business cases that quantify opportunity size and support prioritization decisions.
Recommend innovative enhancements to loyalty measurement, CX frameworks, or lifecycle processes.
Lead workstreams and deliver solutions with significant operational impact across the loyalty function.
Apply a test and learn approach & develop roadmaps to improve loyalty drivers and refine leading indicators of repurchase, defection, and engagement
Mentorship & Collaboration
Act as a resource for colleagues with less experience, offering clarity on insight interpretation and loyalty activation.
Model inclusive, collaborative behaviors that support cross-team problem solving.
Skills & Expertise:
Strategic Competencies
Independently assess loyalty challenges, evaluate options, and recommend innovative solutions.
Demonstrated business judgment in ambiguous environments; able to structure complex problems into clear, actionable pathways.
Skilled in influencing others using data-backed evidence when presenting recommendations or gaining alignment.
Technical / Data Fluency
Prior marketing analytics experience analyzing behavioral data, segmentation, funnel metrics, and engagement patterns.
Ability to interpret predictive model outputs (propensity, churn, segmentation scores) and activate them in CX or marketing workflows.
Familiarity with SQL/Python, Databricks, and BI tools (e.g., Power BI); comfortable querying and exploring data when needed.
Understanding customer data ecosystems and the ability to translate business needs into analytical requirements.
Familiarity with loyalty and CX KPIs such as repurchase rate, engagement scores, churn indicators, NPS, and digital engagement metrics .
Soft Skills
Excellent communication skills and ability to translate analytical findings into compelling business narratives.
Demonstrates urgency, focus, and accountability for outcomes.
Comfortable challenging assumptions and proposing new approaches.
Works respectfully and inclusively across diverse teams.
Deep understanding of owner needs, behaviors, and lifecycle pain points .
Requirements:
Bachelor's degree or equivalent experience required
5+ years of experience in marketing analytics, customer insights, CRM, CX, or loyalty strategy
Strategic Competencies
Strong strategic thinkers who can independently assess loyalty challenges, interpret trends, evaluate options, and translate into clear actionable strategies.
Demonstrated business judgment in ambiguous environments; able to structure complex problems into clear, actionable pathways.
Skilled in influencing others using data-backed evidence when presenting recommendations or gaining alignment.
Understanding of owner needs, behaviors, and lifecycle pain points .
Technical / Data Fluency
Prior marketing analytics experience analyzing behavioral data, segmentation, funnel metrics, and engagement patterns.
Ability to interpret predictive model outputs (propensity, churn, segmentation scores) and activate them in CX or marketing workflows.
Familiarity with SQL/Python, Databricks, and BI tools (e.g., Power BI); comfortable querying and exploring data when needed.
Understanding customer data ecosystems and the ability to translate business needs into analytical requirements.
Familiarity with loyalty and CX KPIs such as repurchase rate, engagement scores, churn indicators, NPS, and digital engagement metrics .
Soft Skills
Excellent communication skills, storytelling, and ability to translate analytical findings into compelling business narratives.
Demonstrates urgency, focus, and accountability for outcomes.
Highly organized, detail-oriented, and able to manage multiple priorities
Strong interpersonal skills; collaborative, inclusive, and comfortable challenging assumptions constructively
Preferred Background:
Career trajectory shows progression from hands-on analytics roles (e.g., marketing analytics, customer insights, BI) into broader CX, marketing or loyalty strategy responsibilities, demonstrating both depth and evolution.
Proven experience launching or operationalizing loyalty, retention, or owner engagement initiatives; not just analyzing data but driving real activation outcomes.
Advanced comfort working in complex customer data environments, including querying large datasets or exploring Databricks, with the abili
