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Data Privacy

Manage the privacy of your customer's data and safeguard their sensitive information


About Data Redact

Our Data Redact feature allows you to redact sensitive information from your data sets in our systems securely. With this feature, you can easily remove personal identifying information (PII) such as names, addresses, email ids, and mobile numbers from your data, while preserving the integrity of the remaining information.

This feature is essential for ensuring compliance with data protection regulations such as GDPR. With Data Redact, you can rest assured that your data is protected and that you are taking all necessary steps to safeguard the privacy of your customers.

We provide two solutions to cover your compliance and privacy needs:
1. Customer Redact
2. Auto Redact (Paid Service)


Customer Redact:
Under GDPR (and other privacy laws and regulations), individuals have the right to have their personal data erased. Your users may ask you to remove any personal data being held about them. This could typically happen when someone terminates their relationship with an enterprise, for example, the user who no longer needs the service, and asks the enterprise to delete their account and all the information it holds about them.

If your customer sends you a request to have personal data erased, you can use the Customer Redact to immediately remove personal identifying information (PII) such as names, addresses, email ids, and mobile numbers from your data, while preserving the integrity of the remaining information.


Auto Redact (Paid Service):
The auto-redact feature will automatically run on a daily basis and redacts personal identifying information (PII) such as names, addresses, email ids, and mobile numbers from our systems without any intervention from your side. Our Auto-redact feature allows you to define the time frame of redaction based on the user's inactive status of 30 days, 60 days, or 90 days.

To use the auto-redact feature, simply select the time frame related to the user's inactive status of 30 days, 60 days, or 90 days and our system will automatically scan your data sets and redact the personal identifying information (PII) such as names, addresses, email ids, and mobile numbers from inactive user accounts, leaving the remaining data intact.


Please note: The scope of redaction is not configurable and includes the following personal identifying information (PII) such as names, addresses, email ids, and mobile numbers.

The data redact process typically takes 2 hours to complete, as the service needs to thoroughly scan and redact all instances of sensitive information. We recommend not running or scheduling the broadcast during the data redaction window.

The Auto-Redact will run daily between 12:00am to 2:00am Central European Time (CET) for the EU Instance.

Please be advised that we are legally required or entitled to retain some types of data, such as order history as we are a commerce platform. We do this in line with applicable laws including for tax and accounting and fraud prevention purposes.

The EU instance employs a system where Server and Application log data are gradually replaced to retain only the most recent 30 days of logs. Redacting data will not affect the logs, as they are automatically overwritten every 30 days.

Jobs / history

Note: Jobs / history is currently only available for "Customer Redact" operation mode


No open jobs or history to show at the moment

All open jobs and history will show up here!

Customer Redact

Customer Redact allows you to promptly remove personal identifying information (PII) such as names, addresses, email addresses, and mobile numbers from your data while preserving the integrity of the remaining information.

To redact customer data, follow these steps:

  • Download the customer list from the Customer section by clicking on "Customer" and then selecting "Export Customers"
  • Select the customers you wish to redact from the downloaded list and remove the others from the CSV file
  • Upload the file to the Customer Redact section
  • Confirm the redaction of the data

No file selected

[[customerDataCsvFileName]]

In your uploaded CSV, we found that following records have duplicate name / email / mobile number. Please verify and confirm that all records are expected to be redacted

Name Email ID Mobile number Sales channel
[[result.UserName]] [[result.UserEmail]] [[result.UserMobile]] [[result.Platform]]


Auto Redact

The auto-redact feature will automatically run on a daily basis and redacts personal identifying information (PII) such as names, addresses, email ids, and mobile numbers from our systems without any intervention from your side.

Our Auto-redact feature allows you to define the time frame of redaction based on the user's inactivity of 30 days, 60 days, or 90 days.

To use the Auto-Redact feature, follow these steps:

  • Enable the Auto-Redact Service
  • Select the time frame of redaction based on the user's inactive status of 30 days, 60 days, or 90 days. You can adjust this setting at a later time
  • Confirm the redaction of the data

Please note: The data redact process typically takes 2 hours to complete, as the service needs to thoroughly scan and redact all instances of sensitive information. We recommend not running or scheduling the broadcast during the data redaction window.

The Auto-Redact will run daily between 12:00am to 2:00am Central European Time (CET) for the EU Instance.

If necessary, you can temporarily disable the Auto-Redact service using the Enable/Disable toggle button




Delete account

THIS IS JUST DUMMY TEXT FOR NOW - Data redaction is the process of hiding and protecting sensitive information by using advanced analytics techniques such as Natural Language Processing (NLP) and Named Entity Recognition (NER).

Sometimes it is also misinterpreted as data anonymization. But in data anonymization, the information is masked, whereas in data redaction the information is completely removed.

Data redaction is the process of hiding and protecting sensitive information by using advanced analytics techniques such as Natural Language Processing (NLP) and Named Entity Recognition (NER).