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 →

Jeff Glueck no published score: only 1 usable exchange 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
1on raw tape
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Answered raw tape D 5 · C 5 · P 4 · Cm 4 4.60

Q Foot traffic, okay. Just tell us maybe how you, uh, Productize the data. How you turn this massive amounts of data that you had into something that you could sell, and then in the panel we'll talk about who you sell it to, but what, what, what, what was involved in the process of, of, of building that data product?

A Yeah, you know, it's been an evolution. So we started out with very sophisticated customers who might want data sets and actually providing them nightly data sets. Um, but there's very few people who can consume in at that level and have teams of data scientists. Um, and everything's anonymous and aggregated to be very clear, but sort of anonymized and aggregated data sets. Um, we're very, I'm happy to talk about privacy. We're religious about that. Um, but we started building, uh, sort of dashboards that analysts and companies can use. And, you know, the targets are not just like hedge funds Which I know we'll talk a little bit about today, but, but also every retailer, you know, and every CPG company that wants to understand what's happening to retail. It's QSR. It's auto. It's entertainment. It's any business that's driven by physical store traffic and understanding, you know, what's your, what's your share. And it's not just where people are going. It's who's going where. So we understand, you know, you're Macy's. What happens when you close a store? Who's gaining market share? How far are people willing to travel? We understand the home and work address of every consumer in the panel. We understand their demographics. So we can say, you're getting crushed among women in the Midwest, you know, of 20 to 35. Um, and, and we can, we can sort of analyze how far people, when you…

AI assessment note: “we started building, uh, sort of dashboards that analysts and companies can use.”

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