Webhooks are wonderful

Arpit Choudhury
The Glue of the Internet
4 min readDec 5, 2018
Image from Pixabay.com

A webhook, also known as a web callback, is a method that enables an app or web service to send real-time information to another application. The occurrence of an event triggers a webhook and sends over the data instantly.

Integromat has dedicated Webhook modules, but you may also use the webhook trigger module available for a ton of apps. All such modules are marked with an Instant tag.

In this article, I will take you through the process of setting up a custom webhook on Integromat to receive data from an external service called Parseur, an email parsing tool that enables you to automatically extract text from emails. The extracted data can then be stored in an Integromat Data Store and if needed, sent over to a Google Sheet or a CRM via one simple scenario.

Some popular CRM tools on Integromat

Here are 3 easy steps to create a scenario on Integromat that will receive data from Parseur and store it in a Data Store:

Step 1: Configure a webhook to receive data

In a new scenario, choose the Custom Webhook module as the trigger and proceed to add a new webhook. Give it a name that will later help you recall the source that triggers the webhook and save it.

Add a new webhook

A new Webhook URL will be generated and Integromat will begin listening for data to automatically determine the data structure of the webhook. Copy the URL to your clipboard and move to step 2.

Step 2: Trigger the webhook

To do this, you need to head over to your Parseur mailbox dashboard. If you haven’t created one yet, you may follow this guide to get started. On the dashboard, go to the Export section and then to the Webhook tab and create a new webhook by choosing a trigger event and pasting the Webhook URL obtained in the last step.

Create a webhook on Parseur and paste the Webhook URL obtained from Integromat

Now you need to forward an email to your Parseur mailbox address to trigger the webhook.

Once you do that, head back to the Integromat scenario to make sure that the webhook’s data structure has been successfully determined as shown below.

The Data structure of the webhook has been automatically determined

P.S. You may also re-process an existing email under Documents instead of forwarding a new email.

Re-process an existing email on Parseur

Step 3: Set up a Data Store module

Add a new module, search for Data store add select the Add/replace a record module.

Add a Data store module

Next, add a new Data store, and set it up by either choosing an existing Data structure or creating a new one (this is the data structure of the Data store and is unrelated to that of the webhook).

Select an existing Data structure or add a new one

For help with creating a data structure, please refer to this article.

Once the Data store has been added successfully, you can easily take the items received by the webhook and map them in the respective fields in the module panel as shown below.

Map the items from the webhook module’s output

Well, that’s it. Now run the scenario once and re-process the email on Parseur to see the scenario execute beautifully and store the extracted data into the newly created Data store.

Successful execution of the scenario

You can easily add more modules to this scenario to send over the data to multiple services simultaneously or use a router and filters to store specific data in each of the subsequent apps.

Use a Router to send specific data to each of the subsequent apps

Your emails contain data crucial to your business. Don’t ignore it and sign up for Parseur if you haven’t already.

If you found this article useful, do share it with others. If you have questions, don’t hesitate to respond with your queries. You may also join our thriving community on Facebook to interact with other automation enthusiasts and experts.

New to Integromat? Create a free account to access all the powerful features and automate manual repetitive tasks with ease.

--

--

Arpit Choudhury
The Glue of the Internet

Building databeats to help organizations turn good data into growth, and in the process, beat the gap between data people and non-data people for good.