Four meetings, one Tuesday, and you’re supposed to remember who promised what. That’s the moment most people install Otter.ai. It joins the call, transcribes it, and drops a summary in your inbox before you’ve refilled your water bottle. What nobody mentions is that Otter straight out of the box is maybe 60% useful. The other 40% lives in settings you’ve never opened.
Below is the setup I use for client work, the order I do things in, and the specific moments where it pays off. If you want the broader picture of what the tool can do, an Otter.ai review covers that ground. This piece is about actually running the thing.
Do the Boring Setup Before Your Next Call
Skip this and you’ll spend every meeting correcting ‘Our Hong Kong’ when you said ‘Auren Kong.’ Two settings do most of the heavy lifting, and if you’ve never wired up a tool like this before, the seven-step guide to setting up an AI assistant for real work is a solid primer on the general approach.
Custom vocabulary
Find Custom Vocabulary in settings and paste in the names that keep getting mangled: client names, product names, internal acronyms, the surname of the guy who always joins from his car. You can add a few hundred terms, so build the list from your last three transcripts instead of guessing. Read one old transcript and the errors jump out immediately.
Speaker labels and voice profiles
Otter guesses who’s talking using voice profiles. On a paid plan you can enroll your own voice and name the regulars in your standups, so ‘Speaker 2’ becomes ‘Priya’ without you touching anything. Do it once and every future transcript arrives readable rather than as a wall of anonymous dialogue.
Connect Your Calendar So Otter Joins Without You
OtterPilot is the feature that auto-joins scheduled Zoom, Google Meet, and Microsoft Teams calls. Link your calendar and the bot appears as a participant about a minute before start time, records, and posts notes to your inbox. A silent bot on the call makes some people twitchy at first; there’s a decent walkthrough of how these assistants behave in practice in this guide to letting an AI meeting assistant take notes for you, but the short version is that most attendees forget it’s there within ten minutes.
One habit worth building: set auto-join to only your own meetings, or only meetings with external attendees. Otherwise Otter quietly records your 15-minute one-on-one with your manager, which is awkward when the summary lands in a shared workspace.
Turn the Wall of Text Into Something You’d Actually Read
Transcription is the commodity. The value sits in what you do in the ten minutes after the call ends.
- Highlight as you listen back. Click any line to highlight it. Your highlights become a personal shortlist of decisions, separate from Otter’s automated summary.
- Ask the chat panel questions. Typing ‘what did we agree about the pricing deadline?’ returns a direct answer with a link to the exact moment it was said, which beats scrolling through 45 minutes of transcript.
- Check the action items before you trust them. Extraction is good, not perfect. Otter will happily list ‘send the deck’ as owned by the person who merely asked for it.
- Export deliberately. Copy to clipboard for a quick Slack post, DOCX when the client wants a document, PDF when legal is watching.
A Worked Example: 45-Minute Client Call to Follow-Up Email in Six Minutes
Here’s the actual sequence from last week. The call ended at 2:45pm and Otter’s summary landed by 2:47.
- 2:47 — Skim the summary. Skip the fluffy opening paragraph and go straight to action items.
- 2:49 — Open the transcript and search for ‘by Friday,’ ‘budget,’ and the client’s first name. That surfaces every commitment in about 90 seconds.
- 2:52 — Fix the two names Otter got wrong, so the client’s own name is spelled correctly in anything you forward.
- 2:55 — Paste the corrected action items into your email, add one sentence of context per item, send.
Six minutes total. The email is more accurate than the one you’d write from memory, and it cites exact wording when the client pushes back three weeks later.
Finding the Sentence From Three Weeks Ago
Search inside a single meeting is decent. Search across all of them is where Otter earns its keep. Type a client name into the search bar and you get every meeting they attended, with timestamps. Import an audio file from your phone and it joins the same archive, which is handy for site visits and interviews where nobody’s on a video call.
Two limits to know about. On the free plan you’re capped at 300 minutes a month with a 30-minute ceiling per conversation, so long workshops get chopped into pieces. And accuracy drops with heavy accents, crosstalk, and bad hotel Wi-Fi. For a critical call, wear a headset and ask everyone to say their name once at the start.
Deciding Whether Otter Is the Right Bot for Your Team
If you mainly want automatic notes and a clean summary, Otter is a strong default. If you need CRM sync, deeper analytics, or team-level admin controls, read a Fireflies.ai comparison before you commit, because the two tools diverge sharply on integrations. Teams that just want free, lightweight meeting capture often land on Fathom instead, which is part of why it keeps showing up on lists of free AI tools that are genuinely worth using.
Sharing Settings You Should Change Today
Every recording has a default visibility. Set it to private, then share individual conversations by link as needed. Turn off ‘anyone with the link can edit,’ and be deliberate about which folders sync to Slack. If your company handles anything under NDA, put a one-paragraph rule in writing for the team rather than assuming everyone read the fine print.
Also worth 20 seconds: rename recordings before sharing them. ‘Q3 pricing sync with Northwind, 14 March’ is searchable and obvious. ‘Recording 47’ is neither.
The Friday Routine That Makes Any of This Stick
Fifteen minutes on Friday afternoon and Otter stops being a pile of transcripts. Open the week’s recordings, scan for action items you never closed out, and forward anything the team needs into the project channel while the context is still fresh. Batch the cleanup into one sitting instead of context-switching after every single call.
Then do one more thing: once a month, reread your custom vocabulary list. New clients, new product names, new acronyms. That list is the difference between a transcript you skim and one you actually trust.