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Error handling

Operations and workflow managementIntermediate Level

Error handling is how a system detects, reports and recovers from problems such as invalid data, failed imports or rejected channel updates, so one error does not stop the whole process.

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What is Error handling?

Error handling means detecting, reporting and recovering from problems when a system runs a process: a product import with a broken row, a price update a marketplace rejects, or a timeout from a webshop API. Good error handling keeps the rest of the job running, tells you exactly what failed and why, and makes a retry or a fix easy. In ecommerce, most system errors are product data errors: a missing required attribute, a value in the wrong format, a duplicate SKU or an unknown category. Error handling differs from data validation, which tries to stop bad data before it is used; error handling deals with what still goes wrong. Both work best together, with clear rules up front and readable error logs afterward. Our guide to data validation covers the rules side.

Why Error handling matters for e-commerce

Ecommerce runs on many small automated jobs: imports from suppliers, updates to webshops, feeds to marketplaces. When one of them fails silently, products go missing from a channel, prices drift apart or stock is wrong, and nobody notices until a customer does. Clear error handling turns those silent failures into a list of fixable items: which product, which field, which channel and what the channel said. That saves support time and keeps listings live.

Examples of Error handling

  • 1Process: CSV import, Error: row 412 has text in the price column, Handling: row skipped, other rows imported, error listed with row number.
  • 2Process: Channel update, Error: marketplace rejects a product without a GTIN, Handling: product flagged with the channel's message, others sent.
  • 3Process: API sync, Error: webshop returns a timeout, Handling: request retried later instead of failing the batch.
  • 4Process: Bulk edit, Error: wrong value applied to 300 products, Handling: the change is undone from the operation history.
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How WISEPIM Helps

  • Rules before errors: Quality Guard rules flag missing or invalid product data before it is sent, so fewer updates fail at the channel.
  • Channel checks: Channel Readiness shows which products meet a channel's requirements and which fields block them.
  • Readable import results: product import reports which rows failed and why, and Rollback Import undoes an import that went wrong.
  • Undo on paid plans: Operation history lets you reverse a bulk change instead of fixing products one by one.

Common mistakes with Error handling

  • Stopping a whole import because of one bad row.
  • Error messages that say something failed but not which product or field.
  • Retrying the same invalid data again and again instead of fixing it.
  • No owner for the error list, so failures pile up unread.

Tips for Error handling

  • Let jobs continue past single failures and collect the errors in one list.
  • Log the product, the field, the channel and the exact message for every error.
  • Separate temporary errors (timeouts) that can be retried from data errors that need a fix.
  • Turn errors that keep coming back into validation rules.

Trends around Error handling

  • More validation at import time, so errors are caught at the source.
  • Channel APIs return more detailed error codes per item, which makes automatic flagging easier.
  • AI suggestions for fixing common data errors, such as missing attributes or wrong units.

Tools for Error handling

  • Error monitoring tools: collect and group application errors for developers.
  • Integration platforms and middleware: offer retries and dead-letter queues for failed messages.
  • Marketplace and Merchant Center diagnostics: show item-level errors per channel.
  • WISEPIM: Quality Guard rules, Channel Readiness and import error reports for product data.

Related Terms

API (Application Programming Interface)Batch processingBOPIS (Buy Online, Pick Up in Store) DataBusiness rulesChannel ReadinessCross-functional Collaboration

Also Known As

Exception handlingError managementError recoveryFault handling

Frequently Asked Questions

Error handling is how a system responds when something goes wrong: it detects the problem, reports it clearly and recovers, for example by skipping a bad record or retrying later. The goal is that one failure does not break the whole process.

Typical ones are failed product imports, updates a channel rejects because of missing or invalid fields, API timeouts, duplicate SKUs and price or stock values that do not sync. Most trace back to product data.

Data validation checks data against rules before it is used and blocks what does not pass. Error handling deals with failures during processing, including ones validation could not predict, such as a channel outage.

A useful error names the product, the field, the channel and the exact message, and says whether a retry can help. That lets someone fix it without digging through logs.

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