How do I review AI call transcripts to improve results?
Review AI call transcripts on a weekly routine: pull a sample of 20–30 calls that includes the shortest calls, negative-sentiment calls and calls that ended without the goal, read them against one question — where did this call go wrong — and group the problems. Fix the most common one in the script, then check the next week whether it stopped. One fix a week compounds quickly.
Pick the right sample
Reading random successful calls is pleasant and teaches little. Over-sample the calls where something went wrong. A good weekly sample has a handful of each type below.
- —The shortest calls — people who hung up within the first 20 seconds.
- —Calls tagged with negative sentiment.
- —Calls that reached a person but did not reach the goal.
- —Calls with an unanswered question or a ‘needs a person’ flag.
- —A few successful calls, to see what worked.
What to look for
| Pattern in transcripts | Likely fix |
|---|---|
| Hang-ups right after the opening line | Shorter, more specific opener |
| Callers asking the same question repeatedly | Add the answer to the agent's knowledge |
| Callers confused at one question | Reword it or offer options |
| Agent mishears a locality or product name | Spell it out in the script; test pronunciation |
| Callers switching to English early | Make the opening more English-friendly |
| Long agent turns, short caller replies | Cut explanations; ask more, tell less |
Group, count, fix one thing
Write a one-line note per call, then group the notes. If seven of 25 calls show the same problem, that is your fix for the week. Change only that, so next week's numbers show whether it worked.
Listen, not just read
Transcripts miss tone. Listen to at least five recordings each week, especially in your callers' main language. A line that reads well can sound rushed in Tamil or stiff in Marathi, and only the audio shows it.
Every call has a recording, full transcript, summary and sentiment in the call logs. Sort by duration or sentiment to build the weekly sample in minutes, and use custom fields such as ‘open question’ to find knowledge gaps without reading every call.
Want to hear an AI voice agent handle this on a real call?