Customer Insights Analyst — Apple Retail Online

Apple • Cupertino, CA

17h

About The Position

The Customer Insights and Lifecycle Marketing (CLM) Analyst supports analysis for Apple’s marketing organization, translating customer journey and campaign performance data into insights that inform CLM strategy. The role partners with Marketing, Decision Automation, Database Marketing, Product Marketing, and other teams to improve targeting, creative, and timing decisions across the customer lifecycle.

The analyst brings together campaign performance, customer behavior, and experimentation data to understand customer engagement and lifetime value. Responsibilities include supporting day-to-day customer insights and CLM performance analysis, contributing to A/B test design and measurement, and turning data from multiple sources into clear recommendations. The role also develops and iterates on lightweight applications and AI-assisted workflows, such as automated reporting, LLM-powered summaries, dashboards, and anomaly detection. As the analyst ramps up, they will take increasing ownership of specific CLM analyses and reporting.

Requirements

• Four years of experience in marketing analytics, customer insights, CLM, or a related data or analytics role, with demonstrated exposure to campaign or lifecycle marketing data.
• Working proficiency in SQL and Python for querying, cleaning, and analyzing large datasets and translating business questions into repeatable analytical workflows.
• Proficiency applying machine-learning techniques to marketing and customer datasets, including customer segmentation and churn or retention prediction.
• Practical experience building dashboards and reports in Tableau or similar business intelligence tools.
• Foundational understanding of A/B testing and statistical concepts, including sample size, significance, and variance, with hands-on experience supporting or analyzing test results.
• Ability to synthesize data from multiple sources, evaluate marketing performance, and communicate actionable recommendations.
• Strong written and verbal communication skills, including the ability to translate technical findings into business-relevant insights for cross-functional partners.
• Comfort working collaboratively with Marketing, Analytics, and Engineering teams in a fast-paced, evolving environment.
• A degree or substantial coursework in a quantitative field such as Statistics, Economics, Data Science, or a related discipline, with demonstrated application to real-world analysis.

Nice To Haves

• Hands-on exposure to Snowflake for querying and organizing large marketing or customer datasets, and Tableau for building dashboards that make CLM performance trends easy to interpret.
• Familiarity with AI or LLM-based tools for accelerating query writing, data exploration, or reporting workflows, and interest in expanding into more advanced tool-building.
• Prior experience related to customer lifecycle marketing, customer segmentation, or journey analysis.
• Exposure to designing or analyzing marketing experiments involving audience targeting, creative variation, or send timing.
• Prior experience working with or presenting to non-technical stakeholders and translating data findings into clear, actionable recommendations.

Responsibilities

• Support day-to-day customer insights and CLM performance analysis for marketing stakeholders, surfacing trends in customer journey and lifecycle engagement.
• Support the design and measurement of A/B tests across audience segmentation, creative, and timing; help define hypotheses, success metrics, and readouts.
• Combine data from marketing, analytics, and engineering sources into unified, digestible insights for the CLM team.
• Develop and iterate on applications and AI-assisted solutions, including dashboards, automated summaries, and lightweight models, to improve visibility into CLM performance and customer journey health.
• Partner with Marketing, Decision Automation, and Product Marketing teams to understand business questions and translate them into analysis plans.
• Present findings and recommendations clearly and concisely so non-technical stakeholders can act on them.
• Use data to identify patterns, evaluate marketing performance, and surface actionable recommendations.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed