Integrating Shopify with your ERP system ensures that data flows seamlessly between your online store and your back office. This means orders, products, inventory, and customers stay synchronized, reducing manual entry and preventing costly mistakes.
A proven way to achieve this is with an ETL (Extract, Transform, Load) process.
How this works
The ETL pipeline can be fully modular:
- Extract from Shopify using:
- Shopify REST or GraphQL APIs (orders, products, customers, inventory)
- Webhooks for real-time triggers (new orders, stock changes)
- Transform into your ERP’s expected format:
- Normalize field names (shopify_order_id -> erp_order_number)
- Convert data types (e.g., dates, currencies, quantities)
- Apply business logic (map Shopify payment status to ERP financial codes)
- Filter or enrich records before pushing
- Load into your ERP:
- Push via ERP APIs or middleware connectors (e.g., Odoo, NetSuite, SAP, Dynamics)
- Directly insert into ERP database tables (more rare)
- Schedule & Sync:
- Run in real time (webhooks)
- Batch sync at intervals (hourly, nightly, or custom)
Typical Data Flows
- Orders: Shopify orders -> ERP sales orders/invoices
- Products & Inventory: ERP is the source of truth -> sync stock levels and pricing to Shopify
- Customers: Sync customer profiles so support and accounting teams always have up-to-date data
Example: Sync Orders from Shopify to ERP
./shopify_to_erp.py
import requests
import pandas as pd
SHOPIFY_API_KEY = "your_api_key"
SHOPIFY_STORE = "yourstore.myshopify.com"
ERP_API_URL = "https://your-erp/api/orders"
def extract_shopify_orders():
url = f"https://{SHOPIFY_STORE}/admin/api/2025-01/orders.json"
headers = {"X-Shopify-Access-Token": SHOPIFY_API_KEY}
response = requests.get(url, headers=headers)
response.raise_for_status()
return pd.json_normalize(response.json()["orders"])
def transform_orders(df: pd.DataFrame) -> pd.DataFrame:
return df.rename(columns={
"id": "shopify_order_id",
"created_at": "order_date",
"total_price": "order_total"
})[["shopify_order_id", "order_date", "order_total"]]
def load_into_erp(df: pd.DataFrame):
for _, row in df.iterrows():
payload = row.to_dict()
requests.post(ERP_API_URL, json=payload)
if __name__ == "__main__":
shopify_orders = extract_shopify_orders()
transformed = transform_orders(shopify_orders)
load_into_erp(transformed)