Orders Are Where Money Meets Data
Every order in your e-commerce system represents real money — either revenue received or revenue owed. When order data is wrong, financial consequences follow directly:
- Wrong shipping address → undelivered package → refund + reshipping cost
- Duplicate order record → overstated revenue → misleading reports → bad decisions
- Misattributed channel → marketing budget allocated to the wrong source
Order data quality isn't an analytics nice-to-have. It has a direct P&L impact.
The Most Common Order Data Errors
Duplicate orders: An order placed twice due to a double-click at checkout, a timeout, or a payment retry. The customer gets charged twice; you ship twice; you issue a refund once. Net result: you've eaten shipping and fulfillment costs.
Sohovi automatically finds every duplicate in your dataset — including near-matches — and shows you exactly which rows are affected.
Wrong or undeliverable addresses: Addresses with missing apartments, wrong zip codes, or incomplete street names. USPS and UPS will try to deliver, fail, and return — costing you the outbound and return shipping.
Payment status inconsistencies: An order marked "Paid" in your platform but pending in your payment gateway. These become reconciliation nightmares at month-end.
Channel misattribution: Orders tagged to the wrong marketing source because UTM parameters were stripped or a multi-touch journey was attributed to the last click incorrectly. Your marketing ROI reports are wrong.
Missing required fields: Orders without a valid email (no order confirmation), without a phone number (carrier can't reach customer), or without a tax ID for B2B orders.
Detecting Order Data Issues
Duplicate detection: Export orders and sort by customer email + amount + date. Orders from the same customer for the same amount within 30 minutes of each other are probable duplicates.
Address validation: Most shipping carriers offer address validation APIs. Run your order addresses through validation weekly and flag undeliverable ones before you pick and pack.
Payment reconciliation: Export orders from your platform and transactions from your payment gateway. Join them by order ID. Any order ID that appears in one but not the other is a gap.
Field completeness: For each required field, count nulls in your weekly order export. Any new nulls are a form or checkout bug.
Sohovi profiles every column in your dataset for completeness and flags the exact rows where values are missing — free to try.
Preventing Order Data Problems
Most order data problems start at checkout:
- Require address validation at checkout (many platforms offer this via extension)
- Require a valid email format (use HTML5 email input type minimum)
- Configure your fraud detection to flag suspicious duplicate orders before fulfillment
- Use consistent UTM parameter conventions for all campaigns and set up UTM validation in your analytics tool
