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Extract Important Call Information turns a conversation into fields. Instead of reading a transcript to find out whether the caller wanted a call back, you get a value called callback_requested on every single call record, ready to filter, count, or send to your own system. You set it up in your agent’s Post Call Analysis tab.

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Before you start

  • An agent that is taking calls. See Turn your agent on.
  • Ten minutes for the first field, two minutes for each one after that.
  • A list of the questions you currently answer by reading transcripts. Those are your fields.
  • You will be working in your agent’s Post Call Analysis tab.

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Steps

1

Open Post Call Analysis

Open your agent and go to Post Call Analysis, then find Extract Important Call Information.
2

Add a field and choose its type

There are three types, and picking the right one matters more than anything else you do here.
  • Identify Yes or No Questions. A clear question Brilo can answer with yes or no. Best for confirming that something happened.
  • Select from Predefined Choices. You supply the options and Brilo picks the closest match. Best for anything you want to group or count.
  • Extract Specific Information. Free text, for pulling out a specific piece of information such as an email address.
3

Give it a unique name

This is the name your systems will see, so it has rules: lowercase letters and underscores only. For example callback_requested, user_interest_level, or user_email.Name it after the thing, not the question. user_email is a good name, what_is_their_email is not.
4

Write what Brilo should extract

Phrase it as the question you would ask somebody who listened to the call. “Did the user request a call back”. “What is the user interest level”. “What is the user’s email”.Be specific about which value you want when a call mentions several. “The email address the caller gave for confirmation” beats “their email”.
5

Add choices or examples

For Select from Predefined Choices, list the options. Keep them few and clearly different, and add an option for none of the above.For Extract Specific Information, fill in Output examples. This is the single biggest lever on accuracy, and skipping it is the usual reason a field comes back empty or in the wrong format.
6

Save, then take a real test call

Save and call your agent, deliberately saying the thing you want extracted. Open the call record and check the field. See Test your agent yourself.

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You will know it worked when

You open a call record and the field is filled in with the right value, and on a call where the subject never came up it is empty rather than guessed.

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Which type to use

Prefer choices over free text whenever you can list the options. Choices give you clean values you can count, and free text gives you thirty spellings of the same thing.

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Fields worth setting up first

Start with four, not fourteen:
  1. Did they get what they wanted. Yes or no. This is the one number that tells you whether your agent is working.
  2. What did they want. Choices, listing your main services plus other.
  3. Do they need a person. Yes or no. This is your follow up list.
  4. The one detail you always chase. An email, a postcode, a policy number, whatever your team asks for twice a day.
Add more once those four are reliable.

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Where the values go

Extracted fields are on the call record, and they are included in the webhook sent after each call, so your own system gets them without anybody copying anything. See Send data to your systems and Post-Call Webhook. That makes extraction the right tool when software is going to act on the value. When a person is going to read it, a summary is better. See Personalised call summaries.

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What else you can do here

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If it did not work

The field is always empty. The detail was never said on the call. Extraction reads the conversation, it cannot invent. Tell your agent to ask for it. That fixes far more empty fields than rewording the extraction does. The value is in the wrong format. Add Output examples showing the exact shape you want. A field without examples is guessing at your format. Choices come back as the wrong option. Your options overlap. “Interested” and “Very interested” are hard to separate from a phone call. Cut to three clearly different options. It picks the wrong one of two values in the call. Say which one you mean in the extraction question, for example “the mobile number the caller asked to be called back on”. Your unique name will not save. Lowercase letters and underscores only. No spaces, digits, or dashes. Nothing appeared on older calls. Extraction runs as each call ends, so it applies to new calls only.

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FAQ

Yes. Add an extraction field of type Extract Specific Information in your agent’s Post Call Analysis tab, name it user_email, and ask for the email the caller gave. Fill in Output examples so it comes back in the format you expect.
Identify Yes or No Questions answers yes or no, for confirming something happened. Select from Predefined Choices picks from options you supply, for anything you want to count or group. Extract Specific Information returns free text, for a specific value such as an email or a postcode.
Almost always because the detail was never mentioned on the call. Extraction reads what was said and does not guess. Instruct your agent to ask for it during the conversation.
They show Brilo the shape you want the answer in, and they are the biggest single factor in accuracy for free text fields. A field without examples will come back in whatever format it likes.
Yes. Extracted fields are included in the webhook after each call, so your system receives them directly. See Send data to your systems and Post-Call Webhook.
Lowercase letters and underscores only. That name is what your systems see in the webhook, so name it after the value, like service_address, rather than after the question.
Start with four: whether the caller got what they wanted, what they wanted, whether they need a person, and the one detail your team always chases. Get those reliable before adding more.