The Exchanges

Every argument clarity score on this site is built from rows on this page. Each question and answer was assessed with names hidden, the host's own answers included, on four things from 1 to 5: directness (does it answer the question asked), coherence (do the ideas follow), precision (concrete details and clear references), compression (says a lot per word). The weighted mix (30/30/25/15) is the exchange score. A person's published score averages their exchange scores on raw tape only, at least 8 of them, shrunk toward the cohort mean. Full method →

Kieran Menon no published score: no usable exchanges on raw tape, and a fair score needs 8+ record → ← everyone

Every exchange below was scored with names hidden, four dimensions each from 1 to 5. An exchange's score is 0.30·directness + 0.30·coherence + 0.25·precision + 0.15·compression. The published score averages the raw tape exchange scores and shrinks small samples toward the cohort mean, so five great answers can't beat twenty good ones. Produced feed rows count only toward coarse estimates, never toward a full score.

clear all ✕
1exchanges match
0on raw tape
0redirected or not addressed
Answered produced feed D 5 · C 5 · P 4 · Cm 4 4.60

Q I see. Interesting. Okay. So base fee is about 50 K employees. If I'm paying you 80,000 bucks a year, something like that. Um, cool. All right. And then I guess, give me more of the, more of the backstory here. So you launched 20 17 with three co-founders. How did you guys get your first customer?

A It was actually, um, you know, given the, um, kind of time we'd spent in the market, we kind of had a lot of, uh, networks that we reached out to, and, uh, went out and kind of spoke to a lot of people, so it's not that we woke up one day and came up with this, uh, solution, um, we actually did go out and talk to a lot of, uh, executives, and then we realized, you know, the, the whole workplace tech was kind of exploding, um, but when you kind of looked at, Right at the beginning, the onboarding piece, uh, there was a huge vacuum in 2017, 20 18, but it was still a nice to have. It wasn't, you know, a need. Um, and so very candidly, our, our growth has happened in the last two years since the pandemic. Uh, for the first two or three years, we were kind of building the product with a couple of POC customers like Unilever and Fidelity Investments. Um, and then in the last couple of years, it has, um, pretty much taken off for us, uh, fundamentally.

AI assessment note: “building the product with a couple of POC customers like Unilever and Fidelity Investments.”

page 1
Made with StarZero

Turn any episode into a week of clips.

This entire site, over 2,600 episodes transcribed, diarized, checked and made playable, runs on the StarZero media pipeline. Drop in your own episode and the podcast clipper finds the moments worth sharing, cuts them, captions them, and reframes them for every feed.