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 →

Simon Gillett 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
1redirected or not addressed
Not addressed produced feed D 1 · C 3 · P 3 · Cm 3 2.40

Q I was going to say, well, you know what they say, when anything is free, you are the product, uh, which in this case, let's talk about sort of how you're understanding and understand the data, right? Do you anonymize all this stuff when someone connects it? How do you, like, how do you treat data that's connected to your platform?

A Yeah. I mean, think of it service based, right? So what, what rather than productized, I mean, we don't charge SAS subscriptions like time period, time bound access, uh, payments for, for ATM, but then we do, we do enable the merchants to get great analytic insights into the, into the, into the business. So that helps with demand forecasting and, you know, and whether it goes into a funding conversation down the road later is, Is, is a later conversation, but that ability to do financial planning and resource planning with the same forecast, the same forecasting technique that amazon.com uses does attract quite sophisticated merchants who want to forecast their sales revenue, you know, they want to do their business owners manage expenses and understand the businesses performances. And this is, uh, entirely free and delivered within one day training period of the AI and the modeling that happens Take place to split the training data into, into the models does take some period, but we say that we can deliver that forecast within one day.

AI assessment note: “think of it service based, right? So what, what rather than productized”

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