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 →

Rob Nelson 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.

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2exchanges match
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Answered produced feed D 5 · C 5 · P 4 · Cm 4 4.60

Q You do a great job. I'm looking at your executive view on the page right now in terms of presenting the data, but people can get lost in this. Um, have you moved this stage further yet in terms of building a machine learning and AI to actually make recommendations on what people should do with the data?

A Yeah, we're, we're starting that process, right? I mean, um, we're not really getting into the business of, you know, this is what the numbers are telling you. So take this action. We're not so interested in that as we are like, what, what's the most effective thing to track in your business? And what we're seeing our customers, our most successful customers track is, um, all around the customer acquisition process, right? With, you know, and B in the B to B world, it's, you know, starting with ad spend, uh, leads generated, uh, sales opportunities and the conversion rates and deals closed that ultimately trickle down to revenue. And sales generated. So it's that whole, that whole funnel and being able to visualize that in real time to drive behavior and, uh, growth in the company.

AI assessment note: “we're starting that process, right? I mean, we're not really getting into”

Answered produced feed D 5 · C 5 · P 4 · Cm 4 4.60

Q That's a big give up, Rob. I mean, a lot of these hubs, a lot of these companies, their whole ARPU kind of increasing strategies around adding seats. Why'd you make that decision?

A You know, the thought of, uh, one guy running a single user seat, uh, managing BI in his back cubicle makes me throw up in my mouth. I just hate that idea, you know, and, and where we're trying to democratize this process and data and BI, You know, it kind of goes in, it plays into our mission where, like, hey, we don't care if you're in marketing or in sales, connect to the apps that you use, pull the data back, build reports, and get it out in front of the team. Um, so whatever department that you're in, um, we want, we want users to do that. So, um, we charge based on the number of metrics that they use, or that they're tracking, or the number of reports that they build. Okay. So, uh, our average, uh, you know, average, our ARPU is, is like, 600 dollars a month.

AI assessment note: “where we're trying to democratize this process and data and BI”

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