Marketing_Analytics_Internship

🥈Silver

This repository features my project as a Business Analytics Intern at Limitless Marketing, a Canadian digital marketing agency. To solve the challenge of fragmented data, I built an end-to-end analytics solution with a unified data warehouse, ETL pipelines, and real-time dashboards, driving impactful, data-driven insights for the agency’s clients.

400Updated Today

Intermediate30min to implementmarketing

Saves ~150 min per use

Quick InstallView Source

git clone https://github.com/Grisales1803/Marketing_Analytics_Internship.git

Works with:

Claude

Overview

About This Skill

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/Grisales1803/Marketing_Analytics_Internship

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

I'm a marketing analytics intern at [COMPANY], a [INDUSTRY] agency. I need to build an end-to-end analytics solution to unify fragmented data. Create a plan for a unified data warehouse, ETL pipelines, and real-time dashboards. Include key metrics and KPIs relevant to our clients' needs.

Example Output

# Marketing Analytics Internship Project Plan

## Objective
Create an end-to-end analytics solution to unify fragmented data for Limitless Marketing's clients.

## Proposed Solution
1. **Unified Data Warehouse**: Implement a cloud-based data warehouse (e.g., Google BigQuery) to consolidate data from multiple sources.
2. **ETL Pipelines**: Develop ETL pipelines using tools like Apache Airflow or Talend to extract, transform, and load data from various marketing platforms (e.g., Google Ads, Facebook Ads, SEO tools).
3. **Real-Time Dashboards**: Build real-time dashboards using Looker or Tableau to visualize key metrics and KPIs.

## Key Metrics and KPIs
- **Customer Acquisition Cost (CAC)**
- **Return on Ad Spend (ROAS)**
- **Click-Through Rate (CTR)**
- **Conversion Rate**
- **Customer Lifetime Value (CLV)**

## Implementation Timeline
- **Week 1-2**: Set up the data warehouse and ETL pipelines.
- **Week 3-4**: Develop and test the dashboards.
- **Week 5-6**: Deploy the solution and train the marketing team.