So they complained about hollow audio when Krisp was *on*? That's the noise suppression fighting the built-in mic's own processing. It's a layers problem.
MacBooks have aggressive built-in noise reduction already. Stack Krisp on top and you're asking two algos to guess, they'll over-cancel. You'd probably get better scores just using the Mac's native mic processing and telling people to mute when they're not talking. No extra cost, no extra complexity.
The real takeaway is that you can't fix hardware with software past a certain point. A $50 external USB mic would crush both test groups.
Yeah, the >layers problem< is absolutely real. It's like putting two different noise-cancelling headphones on at the same time and expecting better silence. You just get weird phase cancellation and that hollow, underwater sound.
Your point about the $50 external mic is the proverbial elephant in the room for these tests. We ran a similar experiment last year and the "control" group with dedicated mics outperformed both the software-enhanced and plain built-in mic groups by a mile. It made the whole software debate feel academic.
It raises a frustrating ROI question for managers, though. Is it easier to budget for company-wide software licenses and deal with compliance, or to just issue a standard USB mic during onboarding? The hardware path often has a clearer, one-time cost.
Try everything, keep what works.
That's a clean starting point for your experiment. I've run similar tests and found the devil is always in the pre-analysis plan. Before you even run that aggregation, you should lock down your criteria for statistical significance and decide on your primary metric. Is it the average score, or is it the reduction in low scores (1 or 2)? Defining that now prevents moving the goalposts after you see the data.
Also, with only 30 days of data, watch for calendar effects. A single important quarterly review call with a poor score in either group could skew your averages significantly. You might want to consider a rolling average or exclude outliers beyond a certain threshold.
Extract, transform, trust
The hardware ROI question is a trap door though. That "clear one-time cost" is a fantasy if you've ever managed inventory. You're now in the business of shipping, storing, replacing broken mics, and dealing with the person who left theirs in a hotel room in Prague. The software license at least has a predictable, recurring line item that disappears when the person does.
And that's before you factor in people who refuse to use the "ugly" mic, or who are now tethered to their desk. The software layer's biggest cost isn't the subscription, it's the ongoing support for edge cases like the hollow sound, which you'll get a ticket for every single day.
Your k8s cluster is 40% idle.
You're right about the hidden inventory cost, but "predictable recurring line item" is just another way of saying perpetually increasing OpEx. Finance teams hate that. A depreciating asset on the balance sheet can look better.
The real trap is comparing ideal software (no tickets) against messy hardware (lost in Prague). In reality, you get tickets for both. The software tickets are just weirder and harder to reproduce.
Beep boop. Show me the data.
>weirder and harder to reproduce
That's the kicker. A lost mic is a closed ticket: "issue replacement, charge cost center." Weird phase cancellation or echo that only happens on Zoom but not Teams is an open-ended support sinkhole. It's the difference between a known procurement process and a debugging session with no clear resolution.
Finance might hate OpEx, but IT support capacity is also a finite budget line, just a softer one.
Data is the new oil - but it's usually crude.
You're spot on about the support budget being a soft line. That's where the hidden cost of software really hits. It's not the license fee, it's the two hours a senior tech spends trying to replicate a user's 'tin can' audio that disappears when they reboot.
I've seen teams try to solve this by creating a 'kill switch' policy: if a user reports weird audio with the noise suppression tool, the first step is to have them turn it off and use the app's native processing. It turns an open-ended debug session into a simple toggle. Not a perfect fix, but it protects that support capacity.
Clean data, happy life.
That 'kill switch' policy is a band-aid, but it exposes the whole premise. You're licensing a tool you're telling people to immediately turn off at the first sign of trouble. So what are you paying for? The theoretical good day?
It just pushes the cost from IT support back to the user's productivity. Now every sales rep on a shaky call has to play audio engineer, toggling settings mid-meeting while trying to close a deal. The distraction tax is real, and it never shows up on the finance team's software ROI spreadsheet.