Marketing Analytics & Insights Manager

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Requirements:

• 3-6 years in marketing analytics, growth strategy, or data analysis within an agency, brand, or eCommerce setting.
• Deep understanding of performance marketing & digital advertising, including paid social (Meta, TikTok), search (Google Ads, Bing), email marketing, and retention campaigns.
• Strong knowledge of funnels, on-site conversion metrics, and customer journey analysis in eCommerce.
• Proficiency in Google Analytics (GA4 preferred), Looker, or similar analytics tools.
• Understanding of the Shopify/eCommerce ecosystem and key metrics like AOV, LTV, conversion rates, and retention trends.
• Strong skills in Excel/Google Sheets for data analysis and reporting.

Responsibilities:

• Analyze omnichannel marketing performance, including paid social, search (Google/Bing), email/retention, programmatic, and on-site conversion.
• Identify opportunities to improve ROAS, CAC, LTV, and funnel efficiency across channels.
• Partner with media teams to diagnose performance fluctuations and optimize spend allocation.
• Develop predictive models to forecast spend efficiency, revenue growth, and conversion trends.
• Provide data-backed recommendations for media mix adjustments across paid and owned channels.
• Evaluate incrementality testing, attribution models, and campaign lift studies to refine strategy.
• Conduct competitive benchmarking, market research, and customer segmentation analysis.
• Support A/B testing and experimentation, including landing page and audience insights.
• Stay ahead of emerging trends in digital marketing, AI-driven analytics, and eCommerce.
• Build and maintain dashboards and automated reports in Google Analytics, Looker, Power BI, Tableau, or Google Data Studio.
• Translate complex datasets into clear, actionable insights for internal teams and clients.
• Develop reporting frameworks to measure campaign performance, customer behavior, and marketing efficiency.
• Identify opportunities to leverage AI tools for marketing analytics, automation, and workflow optimization.
• Improve predictive modeling, anomaly detection, and real-time performance monitoring.
• Explore AI-driven insights for media buying, budget allocation, and performance forecasting.