Learn the details on how to build and optimize your tags here.

Smart tags are formed by a combination of intents and features or semantic patterns and words filters.

Intents are semantic patterns that represent a group of texts that share the same meaning. Those texts don't necessarily have to mention the specific word or words of the name of the intent. Examples can be "pay bill", "card". See here the technical details of intents.

Intents are a good way to see general information. Sometimes you want to go into more detail and that's why we have features. Features can be "credit->card->pay", allowing you to be more specific when tagging the data. See here the technical details of features.

You can use tags to automatically categorize tickets or calls and automate actions like assigning a priority to support tickets.

An example use case is to automate the prioritization of support tickets by leveraging our Zendesk Support integration, where the automation flow is as follows:

  1. A workflow is generated by importing Zendesk tickets
  2. The users creates a set of tags based on the Lang.ai suggested categories (e.g billing_issues)
  3. The user creates a trigger to change the priority of new tickets if they are tagged with a specific tag like "billing_issues"
  4. The ticket gets the priority changed

In these articles you can see how to: 

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