OVERVIEW

AdvoCare is seeking a Senior Manager, Marketing Analytics & Insights to own and strengthen the analytics capability within Marketing. This role will combine hands-on technical expertise with strong business and marketing acumen to transform customer, eCommerce, retention, and retail data into actionable insights that improve performance and support profitable growth.

This is a hands-on role requiring strong SQL, Oracle, and Tableau capabilities. The individual will be able to independently access, extract, validate, segment, and analyze complex data rather than relying solely on centralized BI resources. Equally important, this person must be able to move beyond reporting to diagnose what is happening, understand why it is happening, identify opportunities and risks, and translate findings into clear recommendations for Marketing and executive leadership.

The ideal candidate has experience working across customer analytics, eCommerce, retention, CPG, and omnichannel businesses and is comfortable operating at the intersection of technical analytics and business insights.

Key Responsibilities

Marketing & Business Performance Analytics

• Own analysis of overall marketing, customer, and eCommerce performance, identifying the key drivers behind revenue growth, declines, customer behavior, and business trends.

• Analyze performance across the customer journey, including acquisition, conversion, repeat purchase, retention, churn, reactivation, purchase frequency, AOV, LTV, and customer profitability.

• Proactively identify emerging trends, performance gaps, risks, and opportunities and translate findings into actionable business recommendations.

• Analyze website and eCommerce performance, including traffic, conversion, funnel behavior, landing page performance, checkout behavior, product performance, and customer journeys.

• Evaluate retention and lifecycle performance across email, SMS, loyalty, subscription, promotional, and customer engagement programs.

• Partner with Marketing, eCommerce, Retention, Product, Sales, Retail, and Finance to answer critical business questions and improve decision making.

Customer Analytics & Segmentation

• Build and maintain customer segmentation and analytical frameworks including RFM, lifecycle segments, acquisition cohorts, behavioral segments, and value-based customer groups.

• Analyze customer cohorts to understand acquisition quality, repeat behavior, retention, purchase frequency, LTV, and profitability over time.

• Identify high-value, at-risk, lapsed, and growth-opportunity customer populations and provide actionable audiences and insights to functional teams.

• Support customer targeting and campaign development by translating business objectives into measurable customer populations and segments.

• Evaluate customer movement between lifecycle stages and identify opportunities to improve retention, reactivation, frequency, and customer value.

Data Extraction, Reporting & Business Intelligence

• Write advanced SQL to independently extract, join, transform, validate, and analyze data across Oracle and other relational data sources.

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• Build and maintain scalable Tableau dashboards, reporting datasets, KPI definitions, and self-service analytics for Marketing.

• Integrate and reconcile data across Oracle, Salesforce, GA4, eCommerce systems, retailer and marketplace feeds, APIs, and flat files.

• Establish and maintain trusted KPI definitions, business logic, documentation, and reporting methodologies to create consistent sources of truth.

• Identify data-quality issues, reporting discrepancies, tracking gaps, and anomalies; perform root-cause analysis and partner with appropriate teams to resolve issues.

• Reduce Marketing's dependency on centralized BI resources by creating the technical capability within the Marketing organization to independently access, analyze, and interpret customer and performance data.

eCommerce, Customer & Channel Analytics

• Analyze eCommerce performance across customer segments, channels, and marketplaces to identify key trends, opportunities, and risks.

• Analyze customer behavior across the eCommerce journey, including traffic, conversion, repeat purchase, purchase frequency, AOV, basket composition, cross-purchase behavior, and customer value.

• Evaluate DTC and marketplace performance, including Amazon and TikTok Shop, to understand channel contribution, customer behavior, and overall business performance.

• Connect customer, eCommerce, marketplace, and relevant retail data to provide a broader view of performance and emerging trends.

• Identify customer, channel, and eCommerce opportunities that can drive incremental revenue, retention, and profitable growth.

Promotions, Forecasting & Measurement

• Analyze promotional performance and determine baseline versus incremental impact on revenue, orders, customers, AOV, frequency, and profitability.

• Evaluate promotional lift, customer response, cannibalization, post-promotion behavior, and longer-term customer value.

• Develop forecasts and scenario models using historical trends, customer behavior, and business assumptions to support planning and decision making.

• Support A/B testing and structured experimentation by defining measurement approaches, evaluating results, and determining business impact.

• Partner with Finance and Marketing leadership to connect customer and marketing performance to revenue forecasts and business plans.

Insights & Executive Communication

• Translate complex analyses into clear, concise insights and recommendations for Marketing and executive leadership.

• Develop executive-ready reporting that focuses not simply on what happened, but why it happened and what it means for the business.

• Proactively surface significant changes in customer behavior, retention, conversion, product performance, and other key business drivers.

• Serve as an analytical thought partner to Marketing leadership, helping teams frame business questions, determine the appropriate analysis, and interpret results.

• Ensure functional teams have the data and insights necessary to make informed decisions while functional leaders retain ownership of strategy and execution.

Required Qualifications

• 7+ years of experience in marketing analytics, customer analytics, business intelligence, eCommerce analytics, or a related analytical discipline.

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• Advanced SQL proficiency, including complex joins, CTEs, window functions, aggregations, query optimization, and data validation.

• Hands-on experience working with Oracle or comparable enterprise relational databases, including schemas, tables, views, and data models.

• Advanced Tableau skills, including dashboard development, calculated fields, parameters, LOD expressions, data relationships, and performance optimization.

• Demonstrated ability to independently extract and analyze large, complex, multi-source datasets.

• Strong understanding of customer analytics including segmentation, cohorts, retention, churn, repeat purchase, purchase frequency, AOV, LTV, and customer profitability.

• Strong understanding of eCommerce performance including traffic, conversion, funnel performance, customer behavior, and product performance.

• Experience identifying data discrepancies and establishing trusted KPI definitions and reporting methodologies.

• Strong analytical and problem-solving skills with the ability to move from data to diagnosis to actionable business recommendations.

• Strong communication and presentation skills with the ability to explain methodology, assumptions, findings, and recommendations to both technical and nontechnical audiences.

• Advanced Excel skills.

Preferred Qualifications

• Experience in CPG, DTC, subscription, retail, or omnichannel businesses.

• Experience with syndicated, POS, retailer, or marketplace data such as Circana/IRI, NielsenIQ, SPINS, Amazon, Walmart, Target, or comparable platforms.

• Experience with Salesforce Commerce Cloud, Salesforce Marketing Cloud, GA4, Shopify, Amazon Seller Central, or comparable eCommerce platforms.

• Understanding of CPG metrics including net sales, units, velocity, distribution, market share, customer penetration, repeat purchase, promotional lift, trade spend, contribution margin, inventory, and out-of-stock impact.

• Working knowledge of Python or R for advanced analysis, automation, or statistical workflows.

• Experience with experimentation, forecasting, scenario modeling, and promotional incrementality analysis.