If you’re drowning in client calls but struggling to actually capture what matters, you’re not alone. Juggling feedback from a dozen Zooms or Google Meets each week is a special kind of chaos—and typing up notes later is nobody’s idea of fun. This guide is for anyone who wants a straight-up, realistic way to use Tldv AI features to pull real insights from multiple client calls, without a ton of cleanup or wishful thinking.
Forget the hype—this is about practical steps to make client feedback summaries less painful and more useful.
Step 1: Set Up Tldv—and Know What It’s Good At
First things first: Tldv is an AI-powered meeting recorder. It sits in on your calls (with permission), records audio and video, transcribes the conversation, and offers AI-based summaries and highlights. It works with Zoom, Google Meet, and Microsoft Teams.
What you’ll like: - Records meetings automatically or on-demand. - Decent, fast transcriptions. - AI-generated summaries of what’s discussed. - Tagging and search features for later.
What you shouldn’t expect: - Perfect summaries—AI is good, but it’s not a mind reader. - Deep context or judgment—AI can miss sarcasm, emotion, or nuance. - Magic grouping of “themes” across calls (you’ll still need to review).
Pro tip: Get Tldv set up and test it on a low-stakes internal call before letting it loose with clients. Make sure everyone’s cool with being recorded—don’t skip those consent disclaimers.
Step 2: Record and Transcribe Your Client Calls
Once you’ve set up Tldv, use it to record your client meetings. Here’s how to get the most out of it:
- Record everything, but don’t rely on memory. The point is to capture details you’ll forget by tomorrow.
- Take live notes if possible. Tldv lets you tag moments or type notes during the call (these become time-stamped highlights).
- Remind clients they’re being recorded. It’s not just polite—it’s the law in lots of places.
What works well: - The AI transcription is usually accurate enough for most business conversations. - Tagging key moments (“client frustrated with reporting,” “asks for feature X”) makes it way easier to find relevant bits later.
What to skip: - Don’t waste time correcting every typo in the transcript. If you need legal-grade records, use a human service. For feedback summaries, “good enough” is actually good enough.
Step 3: Use AI Summaries, But Don’t Trust Them Blindly
After the call, Tldv will generate an AI summary. It’ll usually show up in your dashboard in a few minutes.
Here’s what the AI summary gets right: - It catches the main topics and action items. - It often pulls out questions and concerns the client raised. - It’s fast—way faster than rereading a transcript.
What it gets wrong: - It can gloss over sentiment (“client had questions” vs. “client was clearly annoyed”). - It sometimes misses subtle but important points. - If your call goes off on a tangent, AI summaries can get confused or generic.
How to use it: - Skim the summary for the big picture. - Check the time-stamped highlights for anything you tagged live—these are usually the most valuable. - If something looks off or vague, jump to that moment in the transcript or recording.
Pro tip: Don’t copy-paste AI summaries directly into your client reports or product feedback docs. Use them as a starting point, not the finished product.
Step 4: Pull Feedback from Multiple Calls—Here’s Where It Gets Messy
You’ve got summaries from five, ten, or even twenty calls. Now what?
The honest reality: There’s no one-click “give me the themes from all calls” feature in Tldv (as of mid-2024). You’ll need to do a bit of manual work, but the tools help.
Here’s a workflow that’s actually doable:
- Export or copy the AI summaries and highlights from each call.
- You can export to Google Docs, Notion, or just copy/paste into a spreadsheet.
- Skim for repeated issues, requests, or questions.
- Look for patterns: Are three clients asking for the same report? Did two mention pricing confusion?
- Group feedback by theme.
- Use simple highlighters or column tags (“feature requests,” “pain points,” “positive feedback”).
- Don’t overthink it—this isn’t a PhD thesis.
- Pull direct quotes when they really nail the point.
- AI summaries can be bland. Sometimes a client’s own words (“this dashboard makes me want to cry”) have more impact than any paraphrase.
- Ignore outliers—unless they’re major.
- Don’t chase every single odd request. Focus on what’s repeated or urgent.
Pro tip: If you’re doing this monthly, set up a template doc or table you reuse. It’ll save you from reinventing the wheel.
Step 5: Share, Act, and Iterate
Once you’ve pulled out the main themes and real feedback, it’s time to actually do something with it.
- Share summaries with your team—don’t just dump transcripts on them. Use the highlights and grouped themes.
- Flag urgent or repeated issues for follow-up.
- Keep it short. Nobody wants a 10-page doc of AI output. Aim for one page of “here’s what clients are saying, and what we should do about it.”
- Iterate. After a month or two, tweak your workflow. Maybe you need better tags on calls, or maybe you realize some meetings don’t need recording at all.
What to Ignore (and What to Watch Out For)
Let’s be real: AI can help, but it’s not a miracle solution. Here’s what you shouldn’t waste time on:
- Don’t obsess over transcript perfection. It’ll never be perfect, and that’s fine for feedback summaries.
- Don’t expect AI to catch company-specific jargon or inside jokes. You’ll still need a human in the loop.
- Don’t pay extra for “advanced analytics” unless you actually need them. Most people won’t.
Watch out for: - Privacy and compliance. Make sure you’re allowed to record and store these calls, especially with clients in different regions. - Data overload. Recording every meeting is tempting, but you’ll end up with more noise than signal. Be selective.
Wrapping Up: Keep It Simple
Summarizing client feedback across multiple calls doesn’t have to be a nightmare. With Tldv, you can skip most of the grunt work—just remember that no tool can replace a bit of human judgment. Start small, improve your process each month, and don’t buy into the “AI will do it all for you” fantasy.
Focus on capturing what matters, sharing it clearly, and acting on the feedback that keeps coming up. That’s what actually moves the needle.