What does post-call analysis tell you?

A busy campaign makes more recordings in a day than anyone can hear. Post-call analysis is how a team reads them without listening.

Once the caller hangs up, a language model reads the full transcript with your instructions. You tell it what to summarise and what counts as success for this call, like “the customer confirmed the order”. You also describe the fields to pull out, as a schema: a payment method from a fixed list, say, or a callback date.

Doing this after the call matters. During the call, every extra step adds delay the caller hears. Afterwards, the model can take its time, read the whole conversation at once, and give a cleaner answer than any mid-call guess.

The output is plain data, which is the point. A CRM can’t read a recording, but it can read “payment_method: cod”. You can sort a campaign by verdict, retry every call where the customer asked for a callback, or send the right follow-up message automatically.

Two cautions. The analysis is only as good as the transcript, so a misheard address stays misheard unless the agent read it back during the call. And a vague success test gives a vague verdict. “The customer was happy” is hard to judge from text, while “the customer chose a delivery slot” is not.

Use the summary to find the calls worth a look. For anything that matters, like a promised payment date, keep the extracted field and a link to the transcript.