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 →

Toby Gabriner 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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Answered produced feed D 5 · C 5 · P 5 · Cm 4 4.85

Q And, and some figures have been released. It sounds like in 2016, you guys passed the three hundred million dollar run right now. Is that a pure play? Are you a pure play SAS company or is there kind of a percentage of, you know, ad spend through your platform kind of model as well?

A Historically, it's been the latter. Uh, however, um, as we moved into 2018, and it's actually a good segue into the launch of Roleworks, we're now what I would describe as a hybrid. So we have, uh, a, you know, traditional advertising type model that we bring to market, but now we're also had moved into, uh, a SaaS, uh, world. And, uh, we launched Roleworks, um, really focused on 100% on B to B marketers, while, uh, Um, we're solving a similar problem, uh, that we saw for our B to C customers. Um, the, you know, tailoring of the, the products, um, the, the customer life cycle, there's just a lot that's very different. And as we started to take a step back and see that that was a fast growing part of our business, it was very clear that we needed to create a unique standalone business unit that was going to focus on that particular audience. Uh, and what we do for them is we actually onboard their CRM data. Um, again, we enrich it with, uh, our huge proprietary data set, um, and then execute on campaigns and demonstrate by pushing back into whether it's Salesforce, HubSpot, Marketo, how we're moving their prospects along the continuum of, uh, the different stages of a B to B lifecycle sales process.

AI assessment note: “Historically, it's been the latter. Uh, however... we're now what I would describe as a hybrid.”

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

Q role works now. Okay. So SAS, as you mentioned, very different kind of business. The way you just described role works, the question I had in my head is there's a lot of these SMBs, small to middle sized companies where they'll pay for licenses to things like Clearbit, Or full contact to kind of enrich their data and time with their CRMs. How is this role works product different?

A It's different because of, uh, a couple of areas. One is, um, that it's very tied to, uh, the execution element of their campaigns. So, um, uh, you know, each of those companies that you described sort of provide different ways that they're enriching, oftentimes really enabling sales folks to, um, you know, get a better understanding of their name account list. What we're doing is actually Um, looking at even, uh, things like intense signals, um, you know, where, uh, are the, the, um, target accounts are in terms of their buying spectrum. So we're able to really kind of dig in, uh, layers deeper that are driving ultimately, as I mentioned before, the prospects through the various stages of, uh, the, the sales cycle, uh, ultimately. So it's a, It's a slightly different use case on the data, and again, what we've got are 1.2 billion digital profiles, um, we have north of three hundred million, uh, emails, um, and so we have a huge amount of, uh, intent signals that come in, and we use that to really help drive, um, uh, the execution layer, uh, ultimately on the marketing side.

AI assessment note: “It's different because of, uh, a couple of areas.”

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