Educate is even more powerful if you have the team inbox (available with Respond). You and your team can add articles to conversations to answer your customers’ questions faster. Over time, Intercom learns which articles offer the best answers to each question, and we’ll recommend the most accurate ones for you to send.
Quickly find and send articles to answer questions
When a customer asks a question, their message will arrive in your team inbox, where you can add an article directly to the conversation to resolve their query quicker.
Just click the article icon and search for the article you’d like to add. Then go ahead and ‘Add’ it.

Your article will be inserted into the conversation, where you can add additional context to your message before sending it.

Share articles in context
Then when you send your article, your customer will see a preview of it where they can scan the title and context, before reading it.

Once they click the preview, it expands to show the full article, so they can read it in context.

Note: Your customers can react to articles directly from the lightbox so you can gather rich feedback.
Intercom automatically suggests articles to share
Every time you send an article to a customer from the team inbox, Intercom starts learning which articles offer the best answers to each question. In time, we’ll automatically suggest the most accurate articles to add to a conversation when a customer asks a new question.

Because we’re so precise, it may take some time before you see smart suggestions in the inbox. The more articles your team send to customers the sooner your smart suggestions will appear 😀
Pro tip: Placing relevant words customers are likely to use in your article title and description help our suggestion engine make better matches between articles and conversations.
Use feedback to improve your content
Of course, addressing customer conversations should go beyond just answering your customer’s question. Now that you’ve got feedback on your articles, you can go ahead and improve them based on real customer data. This should reduce the number of questions your customers start from your articles, saving your support team even more time 😀