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 →

Amir Orad 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
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Answered raw tape D 5 · C 5 · P 4 · Cm 4 4.60

Q you position this almost, I guess, from a business standpoint? When, when, when, uh, presumably you go talk to IT buyers or even marketing buyers, uh, this jungle of companies out there, uh, and people have heard all the buzz terms and all the Hadoop and the Spark and The memory databases and all those things. How do you position this as being the, the core answer to their problems?

A So we don't sell technology. All of these slides, no one knows. No one cares. People don't care. People want to solve business problems. So what we tell people is quite simple. If you're a business department, business user, you can use Excel and it's good enough up to a size. Then you can use Tableau and it's great up to a size. And then you have this void where you are being told build a warehouse, get IT involved, and put visualization on top, or go to Hadoop, Spark, right, et cetera, et cetera. Everything from Tableau breaking to I need to spend a million dollars on a Hadoop cluster, Is where we come in. If you cannot afford to spend a million dollars, and you cannot wait six months and get IT involved, and you need results, that's where we come into place. So people buy Sisense today and, you know, many people buy Sisense to let business users or business departments get value from complex data without the burden, the pay, the assembly line, right, et cetera, et cetera, et cetera.

AI assessment note: “So we don't sell technology. All of these slides, no one knows. No one cares.”

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