Platform Integrations
ecommerce
How to Create Automated Stripe Revenue Reports
Generate automated revenue and subscription reports from Stripe data.
Jay Banlasan
The AI Systems Guy
I build automate stripe revenue reporting dashboard systems that give store owners automated MRR, churn, and revenue trend reports. This automation runs in the background so you can focus on growth instead of operational tasks.
What You Need
- Python 3.9+ or Node.js 18+
- Stripe API credentials
- A notification channel (Slack, email, or SMS)
Step 1: Connect to the Stripe API
import requests
import os
from dotenv import load_dotenv
load_dotenv()
API_KEY = os.getenv("STRIPE_API_KEY")
API_URL = os.getenv('STRIPE_API_URL')
headers = {
'Authorization': f'Bearer {API_KEY}',
"Content-Type": "application/json"
}
def fetch_data(endpoint, params=None):
url = f'{API_URL}/{endpoint}'
response = requests.get(url, headers=headers, params=params or {})
return response.json()
Step 2: Build the Processing Logic
from datetime import datetime
import json
def process_items(items):
results = []
for item in items:
processed = {
"id": item.get("id"),
"name": item.get("name", item.get("title", "")),
"status": item.get("status", ""),
"amount": item.get("total_price", item.get("amount", 0)),
"processed_at": datetime.now().isoformat()
}
results.append(processed)
return results
Step 3: Set Up Notifications
def send_notification(message):
slack_token = os.getenv("SLACK_BOT_TOKEN")
channel = os.getenv("ECOM_CHANNEL")
requests.post("https://slack.com/api/chat.postMessage",
headers={"Authorization": f"Bearer {slack_token}"},
json={"channel": channel, "text": message})
def notify_batch(processed_items):
for item in processed_items:
msg = f"*{item['name']}* | Status: {item['status']} | ${item['amount']}"
send_notification(msg)
print(f"Sent {len(processed_items)} notifications")
Step 4: Add Webhook Handler
from flask import Flask, request
app = Flask(__name__)
@app.route("/webhook/stripe", methods=["POST"])
def handle_webhook():
data = request.json
processed = process_items([data])
notify_batch(processed)
return "OK", 200
Step 5: Run on Schedule
import sqlite3
def log_run(action, count):
conn = sqlite3.connect("ecom_automation.db")
conn.execute("""CREATE TABLE IF NOT EXISTS runs (
action TEXT, count INTEGER, ran_at TEXT
)""")
conn.execute("INSERT INTO runs VALUES (?, ?, ?)",
(action, count, datetime.now().isoformat()))
conn.commit()
def main():
data = fetch_data("orders", {"status": "any", "limit": 50})
items = data.get("orders", data.get("data", []))
processed = process_items(items)
notify_batch(processed)
log_run("Stripe revenue reporting", len(processed))
main()
What to Build Next
Add a dashboard in Google Sheets that shows Stripe revenue reporting trends over time. Connect it to the webhook handler so data flows in real time, not just on schedule.
Related Reading
- Creating Automated Client Reports - reports that build themselves from live data
- Setting Up Google Analytics Automated Reports - getting more from Google Workspace with automation
- Creating Automated Performance Reports - reports that build themselves from live data
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