How to Build an Automated Email Performance Dashboard

I built this automated email marketing dashboard to stop pulling reports manually every Monday. It tracks open rates, clicks, and revenue from email in a live view that updates itself.

The numbers that matter, updated automatically, in one place.

What You Need Before Starting

• Python 3.8+ with Flask
• ESP API key (Mailchimp, ConvertKit, or similar)
• SQLite for data storage

Step 1: Pull Campaign Data

import requests
from datetime import datetime

def pull_campaign_data(api_key, server):
    url = f"https://{server}.api.mailchimp.com/3.0/campaigns"
    response = requests.get(url, auth=("x", api_key), params={"count": 50, "status": "sent"})
    results = []
    for c in response.json().get("campaigns", []):
        report = requests.get(f"https://{server}.api.mailchimp.com/3.0/reports/{c['id']}", auth=("x", api_key)).json()
        results.append({
            "id": c["id"], "subject": c["settings"]["subject_line"],
            "sent": report.get("emails_sent", 0),
            "opens": report.get("opens", {}).get("unique_opens", 0),
            "clicks": report.get("clicks", {}).get("unique_clicks", 0),
        })
    return results

Step 2: Store in Database

import sqlite3

db = sqlite3.connect("email_dashboard.db")
db.execute('''CREATE TABLE IF NOT EXISTS campaigns (
    id TEXT PRIMARY KEY, subject TEXT, sent INTEGER,
    opens INTEGER, clicks INTEGER, fetched_at TEXT
)''')

def save(campaigns):
    for c in campaigns:
        db.execute("INSERT OR REPLACE INTO campaigns VALUES (?,?,?,?,?,?)",
            (c["id"], c["subject"], c["sent"], c["opens"], c["clicks"], datetime.now().isoformat()))
    db.commit()

Step 3: Build the Dashboard

from flask import Flask, render_template_string

app = Flask(__name__)

@app.route("/")
def dashboard():
    rows = db.execute("SELECT * FROM campaigns ORDER BY fetched_at DESC LIMIT 20").fetchall()
    html = "<h1>Email Dashboard</h1><table border=1>"
    html += "<tr><th>Subject</th><th>Sent</th><th>Opens</th><th>Rate</th><th>Clicks</th></tr>"
    for r in rows:
        rate = f"{r[3]/r[2]*100:.1f}%" if r[2] else "0%"
        html += f"<tr><td>{r[1]}</td><td>{r[2]}</td><td>{r[3]}</td><td>{rate}</td><td>{r[4]}</td></tr>"
    return html + "</table>"

Step 4: Schedule Updates

# Cron: pull fresh data every morning
0 6 * * * cd /app && python pull_data.py

What to Build Next

Add revenue attribution by connecting your payment processor. Knowing which emails drive sales changes your entire strategy.

Related Reading

• AI for Email Marketing Automation - how AI transforms email marketing operations
• Building a Reporting Dashboard from Scratch - making AI reports that drive real action
• Creating Automated Email Sequences That Convert - how AI transforms email marketing operations