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 →

Zach Yadegari 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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1exchanges match
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Answered produced feed D 5 · C 5 · P 5 · Cm 4 4.85

Q Uh, yeah, let me, let me just actually, here, I'll just make this easier, I'll just actually share the parts I'm specifically curious about. So, yeah, this onboarding flow here, right, how do you decide what GIFs to show, what headlines to show, what to put in the onboarding flow here?

A Yeah, so, that's a good question. Initially, we had no animations, we had no GIFs, it was, Very bland. We only asked the questions we needed in order to give the user their calorie daily intake estimate that they would need to gain weight or lose weight, and That was, it was purely utility, but then over time, we started A-B testing different things. We started adding in different questions, which made the user spend more time, but these questions didn't actually have an impact on the end result at all, but we saw an increase in conversion rate, and the hypothesis there, which is pretty confirmed, a lot of other people see this, is just that the user invests more time, so something like following a specific diet, it doesn't impact their app experience at all, But that actually boosted the conversion rate, adding these questions. And then we add the idea to, okay, let's add a screen that says, thank you for trusting us. Let's add a screen that says, you're going to lose weight faster with Cal AI. And that was cool. That increased the conversion rate. So how do we take this one step further? We animated those screens, tested it again, also boosted the conversion rate. So it's just been a game of creating hypotheses and then testing them out.

AI assessment note: “it's just been a game of creating hypotheses and then testing them out.”

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