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How and when to use conversation topics, attributes, and tags
How and when to use conversation topics, attributes, and tags

Conversation topics, conversation attributes, conversation tags. What’s the difference?

Beth avatar
Written by Beth
Updated this week

There are 3 options available to you (based on your subscription) if you wish to categorize and label conversations. These will allow you to track common themes or problems:

Each method has its benefits depending on what’s important to you, but in general we recommend using a combination of all three. Read on to find out about the differences between these methods.

Our Product Education team has created a short video comparing conversation tags and attributes 👇


Conversation topics

Conversation topics are the most consistent, automated way for you to categorize every conversation in your workspace.

You define a a set of keywords and phrases to include (or exclude) and any matching conversation will be automatically added to a topic:

Topics can be applied retroactively to your existing conversations, and require no manual input from your customers or team.

Intercom’s machine learning engine will also suggest new topics for you based on trends in your conversations, opening up potentially missed insights and opportunities.

Conversation topics are purpose built for in-depth reporting too, so you can really dive deep into the subjects your customers chat about:


Conversation data attributes

Conversation data attributes are the most structured way to group your conversations because you can define a specific type like: Text, Numbers, True/false or even a list of predefined values.

They're excellent for categorizing all of your conversations for reporting purposes. For example, by type, urgency, product area etc.

Conversation data attributes are perfect for managing your inbox. For example, if you have a “Priority” attribute it could be set to "high, medium, or low". You can then use these attributes as filters for Inbox Views, and conversations will move in and out of views in real time.

For comprehensive reporting, conversation attributes can be set as required, which ensures that every conversation is correctly identified or categorized before it's closed.

If your teams use tickets, you can create ticket attributes to store this information. Same as conversation data attributes, you can make these required and use them in your Inbox Views.

Conversation tags and attributes can be applied automatically using Workflows, but only conversation attributes can be collected from your customers directly.

This lets you group conversations by values that can’t be discerned from keywords. For example, a customer could choose between “bug report” or “feature request”, or let you know how urgent their request is:


Conversation tags

Conversation tags are the most flexible, and specific as they’re applied to individual replies in a conversation.

They’re useful for marking a particular part of the conversation so you can find it later. For example if you’re highlighting beta feedback for your engineers, or need to bookmark conversations affected by a bug or outage.

Tags can also be applied automatically by Workflows, but not defined by your customers.

Tags are particularly useful for an individual’s needs, like highlighting a list of conversations to learn from, or collecting a showcase of your team’s top GIFs. 😉

An example conversation

To demonstrate how all these methods can be used in conjunction with one another, let’s take an example conversation:

  1. The teammate has tagged this conversation with ‘“Beta candidate”, something that can only be added by a human or automatically via a Workflow. They can now easily pull this conversation up, or share it with the product manager leading the beta.

  2. The teammate has defined the conversation attribute: Urgency as “High”. The conversation can now be assigned and handled accordingly. You can also let the teammate set the urgency through a Workflow.

  3. The topic "Support, Help, Customer Support, Seeking Help" has been automatically applied based on the keywords the customer used. This conversation can now be explored in reports among others for an overall understanding of how often this topic comes up, and how the team handles it.

Summary

Topics

Attributes

Tags

  • Mostly automated (can be updated manually if needed).

  • Consistently applied.

  • Applies to historical, and future conversations.

  • Can suggest and track trends you didn’t know about.

  • Ideal for trend reporting.

  • Available in CSV exports.

  • Captures more granular detail that needs a human to understand.

  • Can be provided directly by customers.

  • Perfect for workflow management.

  • Available in CSV exports.

  • Great for marking specific messages in a conversation.

  • Available in CSV exports.

  • Ideal for an individual’s categorization needs.


💡Tip

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