TemperStack
Intermediate8 min readUpdated Mar 18, 2026

How to apply text parser with regex on Make

Quick Answer

Use Make's Text Parser module with regex patterns to extract specific data from text strings. Configure the pattern, test with sample data, and connect to other modules in your scenario.

Prerequisites

  1. Active Make account
  2. Basic understanding of regular expressions
  3. Text data to parse
  4. Familiarity with Make scenarios
1

Add Text Parser Module to Your Scenario

In your Make scenario, click the + button to add a new module. Search for Text parser and select Match pattern from the available options. This module will allow you to apply regex patterns to extract data from text.
Tip
Position the Text Parser module after the module that provides your text data source.
2

Configure the Text Input

In the Text field, map the text data you want to parse. This can be from a previous module's output, a variable, or manually entered text. Click in the field and select the appropriate data from the mapping panel that appears on the right side of the screen.
Tip
Use the data tab to see all available variables from previous modules in your scenario.
3

Enter Your Regex Pattern

In the Pattern field, enter your regular expression pattern. Use parentheses () to create capture groups for the data you want to extract. For example, use Email: ([a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}) to extract email addresses.
Tip
Test your regex pattern in an online regex tester before implementing it in Make.
4

Set Global and Multiline Options

Configure the Global match option to Yes if you want to find all matches in the text, not just the first one. Set Multiline to Yes if your text spans multiple lines and you need to match across line breaks.
Tip
Global match is essential when extracting multiple instances of the same pattern from a single text block.
5

Configure Case Sensitivity

Set the Case sensitive option based on your needs. Choose No if you want to match text regardless of case (e.g., matching both 'Email' and 'email'). Choose Yes for exact case matching.
6

Test the Configuration

Click OK to save your configuration, then click Run once to test your scenario. Check the execution details to verify that your regex pattern is capturing the expected data. The matched groups will appear as separate variables you can use in subsequent modules.
Tip
Use sample data that represents edge cases to ensure your regex pattern handles all scenarios.
7

Map Parsed Data to Subsequent Modules

In the next module of your scenario, you can now access the parsed data. The captured groups from your regex will be available as separate variables (e.g., $1, $2, etc.). Map these variables to the appropriate fields in your subsequent modules.
Tip
Name your capture groups descriptively in your documentation to remember what each group represents.
8

Handle No Match Scenarios

Add error handling by configuring what happens when no matches are found. You can set up conditional routing using filters or add a Tools > Set variable module with default values to handle cases where the regex doesn't find any matches in the input text.
Tip
Always test with data that won't match your pattern to ensure your scenario handles failures gracefully.

Troubleshooting

Regex pattern not matching expected text
Verify your regex syntax and test it with online tools like regex101.com. Check for special characters that need escaping with backslashes.
Only getting first match instead of all matches
Ensure Global match is set to Yes in the Text Parser module configuration.
Captured groups showing as undefined
Check that your regex pattern includes parentheses () around the parts you want to capture. Verify the pattern matches the text structure.
Module execution fails with no matches
Add error handling using Break or Rollback directives, or use conditional filters to check if matches exist before processing.

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