You will evaluate marketing channel performance using metrics such as cost per lead (CPL) and return on ad spend (ROAS). You’ll identify underperforming channels and recommend data-driven budget reallocations to optimize campaign impact.

You will apply AI-driven scheduling and optimization tools to plan and publish social media content that improves visibility and audience engagement. You’ll build structured calendars using AI-assisted platforms to support consistent performance

You will analyze content performance data to determine which formats, posting times, and messages drive the highest engagement. You’ll interpret analytics outputs to design improvement plans backed by measurable insights.

You will apply location-based optimization techniques to enhance Shopify product titles and descriptions. You’ll create AI-powered product content designed to increase discoverability and drive conversions.

You will analyze e-commerce data using Shopify and Google Analytics 4 to quantify revenue by referral source. You’ll interpret performance trends to make data-driven decisions that improve online sales outcomes.

You will apply co-marketing principles to plan and execute collaborative campaigns with shared goals and performance metrics. You’ll design structured initiatives that strengthen partnerships and extend campaign reach.

You will evaluate how AI assistants describe brands and competitors by analyzing sentiment patterns in responses. You’ll interpret AI-generated perceptions to refine messaging and strengthen brand positioning.

You will apply marketing automation tools to build structured email nurture sequences that guide leads toward conversion. You’ll design AI-enhanced workflows that improve efficiency and campaign performance.

You will analyze customer data to calculate Customer Lifetime Value (CLV) for defined segments. You’ll interpret revenue patterns to identify high-value audiences and inform retention strategies.

In this project, you will analyze multi-channel campaign performance and revenue signals to diagnose what is working, what is underperforming, and where optimization effort should be focused. Using AI-assisted analysis and structured reasoning, you will evaluate engagement, conversion, automation effectiveness, and customer lifetime value (CLV), then recommend clear, prioritized optimization actions. This project simulates a real-world analytics task commonly performed by growth analysts, performance marketers, and revenue teams. The emphasis is on diagnosis, trade-offs, and decision-making, not dashboard creation, data engineering, or tool configuration. The final deliverable is leadership-ready analytics brief that demonstrates your ability to turn performance data into actionable recommendations.