📧 Email Engagement Scoring System
Marketing Analytics | Modeled with Anonymized Data
In this project, I recreated a simplified, anonymized version of an Email Engagement Scoring Model I originally developed in a professional marketing role. The goal? To better understand how users interact with email campaigns and to translate those behaviors into actionable insights for smarter targeting.
🔍 What I Built
I created a scoring system that evaluates user interactions based on email open and click behavior, then categorizes each user into engagement tiers from 0 to 5.
Here’s how it works:
- Open Rate = Emails Opened Ă· Emails Received
- Click Rate = Emails Clicked Ă· Emails Received
- Weighted Action Rate = (Open Rate + 3Ă—Click Rate) Ă· 2
(Because clicks signal stronger intent, they’re weighted 3x more.) - Score 0 = Received emails but never opened any
- Scores 1–5 = Assigned based on fixed percentiles of normalized scores, where Score 5 reflects top-tier engagement
đź’ˇ Why This Matters
This scoring model helps teams go beyond surface-level email metrics and actually segment users based on how they behave. That means better targeting, smarter campaign decisions, and ultimately stronger results.
Whether you’re in marketing, sales, or customer success, having a simple, data-backed way to measure engagement can unlock a lot of value.
🧪 This Demo Includes
- A dummy dataset modeled after real-world behavior
- Visual breakdowns
Examples of how this could be applied in campaign targeting or lead scoring
