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.
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Answered produced feed
D 5 · C 5 · P 5 · Cm 4 4.85
Q Who are the other players that are specific to SAS pricing? You, who else?
A Yeah, I would say price intelligently comes up a lot or profit well. Uh, I know that they may be shifting a little bit with the recent announcement with paddle and everything that they're doing. But, uh, but they do a great job of offering some good, uh, survey services to figure out willingness to pay things like that, which a lot of folks take run with and use, but they don't really get into how do you implement this stuff? Like how do you actually figure out, uh, how do you put implemented discounting matrix? How do you make sure that you can actually pull this off on the other end? How do you do an executive price increase? For example, all those things, uh, we get into, uh, and that comes from, you know, a lot of the, the value creation background that I have.
AI assessment note: “I would say price intelligently comes up a lot or profit well.”
Answered produced feed
D 5 · C 5 · P 5 · Cm 4 4.85
Q Well, what does envelope mean? Is that a range or what does that mean?
A It's just a range. It's just a range with all those inputs and say all these inputs point to 40 to 80 dollars per user, for example, right? And if you look at that range, if you're trying to maximize profit, you go on the higher end. If you're trying to gain market share and get a lot of growth, you go on the lower end. And then from there, you start applying what I call psychology tactics. So things like making the pricing actually easy to absorb, easy to say, easy to sell. And that is the final piece of the puzzle is making sure that the pricing is super simple for some customer to understand. So that way you can break away from any confusion, um, and frame it the proper way.
AI assessment note: “It's just a range. It's just a range with all those inputs”
Answered produced feed
D 4 · C 4 · P 4 · Cm 4 4.00
Q if we buy this company for this valuation on paper right now, it's expensive at 15 X, but when we cross sell the, you know, 2000 dollar average ACV, this is going to be the pickup rate. And actually now it's cheap. How do you run that modeling? And is that the thought process that, that someone should go through when they think about an acquisition in terms of pricing?
A I think it's very important. I think once you start thinking about, um, when you think about the, the upside potential, right? For me, PE is potential equity, not private equity, right? So you're really trying to capture that and the way you frame that, right? And this is where it comes down also with the March pricing models that I, I asked my, my team to make sure that we're building is how do we getting that net dollar or net revenue retention number hires, uh, above one 25, one 31 40, As well as the ARR growth rate to keep that compelling, which gets you in the, in the 20, 25 X multiples, you know, barring, you know, now that the current environment's a little bit more skeptical and, uh, and, uh, around valuations. But the point is, if you have those two numbers, if your pricing model is driving that ARR top line growth and that NRR number up, your ability to get to command a higher, um, multiple is going to be a lot, a lot better.
AI assessment note: “I think it's very important. I think once you start thinking about... upside potential”
Redirected produced feed
D 2 · C 5 · P 3 · Cm 4 3.45
Q Yep. Okay. So let's just, just so people can get really get in your heads. I want you to get sort of street credit with my audience. I don't want them to see you as just like a consultant, right? So tell us about how you helped the SaaS company execute a price increase and what was the result?
A Yeah, absolutely. So I'm actually not much of a consultant. I'm more of an operator because I've built software and sold it my whole life, uh, which is a funny story, but the wheel, the real deal here is how do I help companies figure out how to price? So the first thing we do is we get into where's the growth coming from? Like, are you actually going down market, up market? Are you trying to increase your profit? Are you trying to gain a bunch of, you know, market share or network effect? That's going to tell me, okay, which, uh, which options are available to you from a model perspective. Then we get into your customer base. Who are you selling to? And no, small, medium, and large is not good enough anymore. I actually help them figure out either on a maturity curve or complexity curve, what these customers really want. Then we design and craft an experience for each group. So that means onboarding, implementation, of course, features, services, all those things. And then we price that. Once we get that, uh, that granular, the pricing problem gets a lot easier after that. So what do we do? How do we get with the number? We actually then take, uh, the ROI counts for that specific experience. We look at, uh, data we get from their customers in terms of what they find important and less important. And we apply factors there. We also look at their historical data. And see what ki…
AI assessment note: “the real deal here is how do I help companies figure out how to price?”
