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 →

James Turner 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 ✕
2exchanges match
0on raw tape
0redirected or not addressed
Answered produced feed D 5 · C 5 · P 4 · Cm 4 4.60

Q And once you capture that data, so boom, we've made the phone call to our people. We've talked to them. We know some of the verbiage. What do you do with that data?

A Um, well, you, you can use the customer's own words sort of to sell more customers. That, that's kind of the whole voice of customer thing is that no one knows how better to put it than the people who are actually looking for it and, and, and seeking solutions. So, um, the interviews, you, you might get some, some really great phrases out of, but really it comes down to if you can find a larger source of, um, little snippets, like a, Amazon review mining is, is a thing that is great if you have a product that either has, is on Amazon or has a competitor on Amazon or a similar product or even a book about what you're selling. Um, you can go through large, large numbers of, of small reviews by people and you start to see trends and you start to see the same words coming up. Um, Common problems. And then you can literally just sort of quantify that, you know, which, which problem was mentioned the most, and you can build a messaging hierarchy out of, out of that. Like what, what, what do people, what's the first thing on people's mind that they, they need to see the second they get on your website.

AI assessment note: “you can build a messaging hierarchy out of, out of that”

Answered produced feed D 5 · C 4 · P 4 · Cm 4 4.30

Q And so what is the, when you work with a client that is just, they don't have empathy with their customer base, how do you get them to go back and be a fly on the wall and kind of look and go back to an observer and kind of an observer state?

A Um, well, I, I find that the, the best way is, is through voice of customer research. So like really digging into the words that your customers are using, like forcing people to relook at testimonials if they've got testimonials or, um, especially I find negative and critical comments that have been made if they're on a review site or if they're on even just like emails that are sent to the company. Um, you kind of get a sense of the pains that people are feeling and, and sometimes You know, um, people who are in charge of a product might sort of dismiss, oh, well, we don't really do that. And so, you know, you have to kind of play the balance of like, okay, but, but everyone thinks you do, so you have to sort of address that. And I think some, sometimes people sort of, uh, Forget that they need to address things that are obvious to them.

AI assessment note: “the best way is, is through voice of customer research”

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