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Anonymize names and numbers in text data

Anonymize names and numbers in text data

Owned by François Forest
Last updated: Jan 21, 2025 by Carlos Carasco
2 min read

Detecting personal information

With Feedier, you can automatically detect Personal Data such as names, account numbers or groups using Feedier’s NLP Entity detection engine.

Here is an example with a text feedback,

The product was great but I had a terrible experience with Paul Dupont.

Paul Dupont is automatically marked by Feedier as an attribute.

Feedier comes with several attributes which are detected automatically during the Text Analysis:

  • nlp_personal_name

  • nlp_organization

  • nlp_number

Anonymization process

Go to the Actions page

  1. Click Segments → Create a new segment like “All feedback“ with a selctor on “Time Period” “Greater” than “Today”, so it detects and matches all new feedback.

  2. Go to Automations → Select your segment (created in step 1) → Feedback Update.

  3. Set the attribute name to nlp_personal_name and custom text to **** → Click Add

  4. Set the attribute name to nlp_number and custom text to **** → Click Add

  5. Click Save

Now, whenever Feedier will detect a Personal name or large number (such as account ID), they will be replaced by **** automatically.

It will only work for new feedback entries.