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 →

Raviv 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 ✕
1exchanges match
0on raw tape
0redirected or not addressed
Answered produced feed D 5 · C 5 · P 4 · Cm 4 4.60

Q And what is the, so, so, uh, again, I've read your bio, so folks know you kind of come from enterprise world, but, um, why did you guys decide to get specifically into this space? What did you see that made you excited about it?

A Oh yeah. So for the past 15 years, I was usually in a role of a product designer, building marketing technology. That was usually my job as a user experience designer to better understand customers. So I've been deployed both quantitative and qualitative techniques to understand people. Um, as we, with analytics and structured data, that's, that's great, but that's only telling you that what is happening, not so much the who and the why. If you want to go deeper on unlocking the buyer's mindset, You need to understand people on all different level, which usually involves doing things like persona development, journey mapping, contextual observation, customer interviews, um, and then you just end up with tons of text, and maybe even a PowerPoint. But that's totally static and siloed. So we thought, hey, what if we could, ah, do what's called dynamic buyer profiling and use some AI and natural language processing to basically process tons of text of what people are writing about or saying in emails, even recorded sales calls. And keep this like systematic listening to your buyers and then push all of this big back to your CRM. We are built on top of Salesforce where both marketing and salespeople can use this data to better communicate with, with buyers.

AI assessment note: “So we thought, hey, what if we could, ah, do what's called dynamic buyer profiling”

page 1
Made with StarZero

Turn any episode into a week of clips.

This entire site, over 2,600 episodes transcribed, diarized, checked and made playable, runs on the StarZero media pipeline. Drop in your own episode and the podcast clipper finds the moments worth sharing, cuts them, captions them, and reframes them for every feed.