An online store loses sales in ways that are hard to trace back to data. A customer searches for a product and doesn't find it — because the product's category tag was entered wrong. A order ships to the wrong address — because the customer's record had an outdated address. A discount email goes to the same customer twice — because they're in the database twice. Every one of these failures starts with a data quality problem.
The Two Biggest E-Commerce Data Quality Issues
Product data quality is the completeness, accuracy, and consistency of your product catalog. Missing sizes, wrong weights, duplicate SKUs, inconsistent category names, and incomplete descriptions all reduce discoverability and conversion.
Customer data quality is the accuracy and uniqueness of your customer records. Duplicate accounts, stale shipping addresses, invalid emails, and missing order history all affect the customer experience and your ability to market effectively.
Sohovi automatically finds every duplicate in your dataset — including near-matches — and shows you exactly which rows are affected.
Product Data Quality Checklist
- Complete required fields: Title, description, price, category, and primary image should be 100% complete for every active product
- Consistent category names: "Women's Clothing" and "Womens Clothes" and "women's" are three different categories to a search algorithm
- Accurate dimensions and weights: Wrong weights cause shipping calculation errors; wrong dimensions create fulfillment problems
- Unique SKUs: Duplicate SKUs cause inventory tracking failures and fulfillment errors
- Up-to-date availability status: Products showing "in stock" that are actually discontinued create abandoned carts and bad reviews
Customer Data Quality Checklist
- Valid email addresses: Run an email validation pass before every major campaign
- No duplicate accounts: A single customer with two accounts has split order history and no loyalty recognition
- Current shipping addresses: Stale addresses cause failed deliveries and returns
- Accurate contact preferences: Opt-out and suppression lists must be current and applied consistently
Sohovi lets you upload a CSV export of your product catalog or customer database and instantly see completeness rates, duplicate counts, and format issues for every column — helping you find problems before they cause lost sales.
See how Shopify sellers lose sales to product data problems for a specific e-commerce example.
E-commerce data quality isn't optional — it's directly connected to revenue. Every data problem you fix is a sales problem you prevent.
