VP, Customer Strategy, Analytics & Measurement

Macy's•New York, NY

About The Position

The Vice President, Customer Strategy, Analytics & Measurement is a senior, enterprise-wide leader responsible for defining and activating the company’s customer intelligence, analytics, and measurement strategy — and serving as the lead strategist and enterprise voice of the customer. This role oversees analytics, data science, research, marketing measurement, and customer strategy, translating customer signals into insight, insight into action, and action into measurable growth. With a deep focus on digital, customer, and behavioral data, this leader ensures the organization has a shared point of view on who the customer is, how they are segmented and studied, and how customer insight informs planning, prioritization, and execution. Operating at the intersection of customer strategy, AI-powered analytics, and enterprise execution, this role partners closely with Product, Digital, Marketing, Technology, Merchandising, and Finance to connect customer experience to business outcomes.

Requirements

15+ years of experience in analytics, data science, customer intelligence, marketing analytics, or strategy roles.
Proven success leading advanced marketing measurement (MMM, MTA, incrementality).
Deep expertise in machine learning, AI, and personalization at scale.
Strong command of digital analytics, experimentation, and instrumentation in omnichannel environments.
Experience translating customer insight into business strategy and experience design.
Exceptional executive communication and influence skills.
Builder mindset with a track record of scaling modern analytics organizations.

Responsibilities

Define and lead the end-to-end customer analytics, measurement, and customer strategy vision, spanning insight, modeling, experimentation, attribution, and optimization.
Establish a clear Signals → Insight → Priority → Action loop, ensuring customer data directly informs prioritization, sequencing, experience design, and investment decisions.
Elevate customer intelligence from reporting to a decision-making and optimization engine embedded into enterprise operating rhythms.
Serve as the lead strategist and voice of the customer, defining how the organization segments, studies, and plans around customers.
Own and evolve the enterprise customer segmentation strategy, including attitudinal, value, spend, lifecycle, luxury, and behavioral segments.
Establish a common customer language and strategic frameworks used consistently across marketing, digital, stores, product, and leadership.
Define the enterprise customer learning agenda, aligning research, analytics, and measurement to the most critical strategic questions.
Design how the organization studies customers holistically, integrating experience, behavioral, brand, market, and financial signals.
Translate customer insight into credible, directional business cases that inform initiative prioritization, sequencing, and investment.
Shape customer reporting, scorecards, and executive narratives to ensure leaders have a clear, shared view of customer health, momentum, and risk.
Own advanced contact strategy uplift modeling, including incrementality testing, holdout design, response curves, and frequency optimization.
Lead audience strategy and targeting analytics, including segmentation activation, propensity modeling, suppression logic, and next-best-action frameworks.
Oversee Marketing Mix Models (MMM) and modern hybrid approaches that combine MMM, experimentation, and multi-touch attribution.
Drive multi-touch attribution (MTA) and causal inference approaches across paid, owned, earned, and retail media.
Partner with Marketing and Finance to optimize budget allocation, channel mix, ROI, and customer outcomes.
Establish a rigorous test-and-learn culture grounded in incrementality-based measurement.
Oversee customer analytics across acquisition, engagement, retention, loyalty, lifetime value, and spend behavior.
Lead digital analytics and instrumentation, ensuring best-in-class event design, tagging, identity resolution, and behavioral tracking.
Partner with Product and Engineering to embed analytics into feature development, experimentation, personalization, and roadmap decisions.
Ensure analytics supports both growth and experience quality, not just performance reporting.
Lead a high-impact data science organization spanning predictive modeling, machine learning, optimization, and real-time decisioning.
Drive application of machine learning and LLMs across personalization, intent detection, insight generation, and experience optimization.
Oversee customer spend index models, lifetime value frameworks, churn and growth predictors, and forward-looking demand signals.
Apply advanced optimization techniques (uplift modeling, bandits, reinforcement learning) across marketing, digital, and store experiences.
Own enterprise Voice of Customer programs, integrating qualitative feedback, behavioral signals, and operational data.
Lead customer and area research, blending market, geographic, demographic, and behavioral insight.
Develop and maintain a scalable customer journey framework, mapping end-to-end experiences.
Build customer defect detection and early-warning systems to proactively identify friction and experience breakdowns.
Translate journey insights into prioritized experience improvements.
Define enterprise standards for measurement, experimentation, and causal inference.
Establish frameworks that connect customer actions to incremental business impact, not just correlation.
Lead experimentation strategies across marketing, digital, and store experiences (A/B, multivariate, geo-tests).
Partner with Finance and Strategy to align analytics with forecasting, investment decisions, and performance management.
Ensure insights are decision-ready, timely, and actionable.
Build, lead, and scale a high-performing team across analytics, data science, research, marketing analytics, and measurement.
Establish modern operating models with clear prioritization, reusable assets, and platform-driven analytics.
Own the strategy, selection, and evolution of the analytics, measurement, and insight tool ecosystem, including data platforms, experimentation, attribution, visualization, AI, and decisioning tools.
Design and deploy self-service analytics and insight products that democratize access to trusted customer and performance insights.
Partner closely with Technology to balance speed, scalability, governance, and data quality.
Establish enterprise standards for metrics, definitions, and measurement consistency.
Act as a trusted thought partner to senior leadership, shaping strategy through customer-led insight.
Elevate data, experimentation, and measurement literacy across the organization.