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Prevent data errors at the source

Userlane checks entries against your rules as people work and guides them through data entry correctly, preventing errors before they reach your systems.

See It in Action

Prevent data errors <span class="gradientWhite">at the source</span>
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The Data Quality Challenge

Data quality programs that focus on cleanup are fighting downstream. The cost of fixing a data error after entry is an order of magnitude higher than preventing it.

  • Forms are confusing, field requirements unclear, and processes differ across departments
  • Training happened weeks or months before the person encounters the actual form
  • System updates introduce new error patterns that previous training did not cover
  • No mechanism to enforce data standards at the point of entry across the entire organisation

How Userlane Ensures Data Quality

Catch errors before submission

Errors are caught before they enter your systems, not discovered weeks later in a data quality report. Validators check entries against your rules as people work, and can warn at the submit button listing every field that does not meet them.

  • Measure how often errors happen first, without interrupting anyone, so you have a real error rate before you change anything
  • Enforce correct formats and patterns at the field level, and flag out-of-range values before submission
  • Warn people at the submit button, listing the fields that do not meet the rules, and let them correct or proceed

Standardise data entry

Every person follows the same process, regardless of when they were trained. Guided workflows standardise data entry and eliminate the variation that causes inconsistency.

Without guidance at the point of entry, people fill in forms differently. Standardised workflows reduce the need for post-entry correction.

  • Auto-populate known fields to reduce manual entry and errors
  • Explain field requirements in context so people understand what is expected
  • Guide people through the correct sequence and format for each process
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Proven Impact

  • 70% higher process efficiency.
    A European bank combined in-app guidance with real-time validation. One digitalization lead reported: "Our employees complete complex processes smoothly now."
  • Standardised processes across sites.
    A global manufacturer improved data quality and reduced training efforts by 75% by enforcing consistent processes across its global operations.

70%

Higher process efficiency - European bank

91%

Better software usage - global manufacturer

Data Quality FAQs

Immediately. Validation rules are active as soon as they are deployed. Rules are created in a no-code editor and deployed via the browser extension. No backend integration or application modifications required. This means validation can be added to any browser-based application without involving the application vendor.

Userlane supports format checks, range validations, and conditional rules (for example, a field that requires different formats depending on the value in another field). Validation is configured per field and can vary by department, role, or process using segmentation.

No. Validation happens in real time as people complete fields. Errors are flagged inline before submission, not after. One European bank reported that process efficiency increased by 70% after deploying validation and guidance together. The time saved by preventing errors and rework more than offsets the validation step.

HEART analytics shows where people struggle, make errors, or abandon processes. This data identifies which fields and processes cause the most downstream problems. Prioritise validation for the fields that generate the most rework, support tickets, or compliance exposure.

Yes. Validation rules are configured by department, role, or process while maintaining enterprise-wide standards. Each team gets appropriate controls for their context. This is important for organisations where the same application (such as an ERP or CRM) serves different functions with different data requirements.
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