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 →

Jes Bickhart no published score: no usable exchanges on raw tape, and a fair score needs 8+ · coarse estimate ≈4.5/5 from 6 produced feed exchanges 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 Thanks. Let's, let's take a little step back. Um, tell me what, What did, what problem, um, did, uh, Minnow solve? I know you mentioned, um, aggregators, um, but just, uh, so I can wrap my head around it in terms of.

A Yeah, yeah, so you sit down at the college after a long day, you crack a beer, uh, and you just kind of open up Netflix and start scrolling, you open up Hulu, start scrolling, Disney Plus, start scrolling, um, and, you know, it's like, there's no playlist, you know, unlike Spotify or Apple Music, you open it up and you know what you're going to listen to right away, and you get greater information right away, but with Film and TV, the sampling time with music is like three to four seconds. You're like, I kind of like this or not. Tilbury TV, like, you have to watch it in 20 minutes to something to figure out if you like it. You do that two times and you're done for the night. Like, you're not going to keep watching something. Um, so, so sampling doesn't work the same one day in film and TV that it does use it. And so the content discovery became the problem, that hair on fire problem that we really wanted to solve. Um, and a part of solving that is building a robust recommendation algorithm. And, um, you know, everyone has their own internal That no one did horizontally across all of them, and that's what we tried to solve for.

AI assessment note: “content discovery became the problem, that hair on fire problem that we really wanted to solve.”

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

Q Nice. So how did you, so tell me about the distribution channel. How did you, um, get this in the hands of users?

A I'd say there was probably two distribution channels that worked for us on the B to C side. Um, one was organic social and the other was PR. Um, you know, we, because we developed on a big channel, we, we felt that it was probably worth it to spend on PR. Uh, so I'll speak to that first. Um, a lot of, I mean, This is, there's a lot of, like, controversy on whether you should pay a PR firm for launching or not. Um, you know, we didn't really want to be on TechCrunch. We wanted to be on a more, uh, mainstream periodical. And we got our first press break from Mashable, um, and then we got a follow-up from FastCup. And those two pieces, um, and we worked with the PR firm Rogers and Cowan, um, in Los Angeles, they're right down the street.

AI assessment note: “two distribution channels that worked for us on the B to C side... organic social and... PR”

Answered produced feed D 5 · C 4 · P 4 · Cm 3 4.15

Q Can I, I, so if I, if I understand you correctly, I might be able to relate. Did you just kind of get the idea and just start running with it?

A Exactly. There was not a whole lot of, like, prep and, and thought that went into it. It was more of, this is a consumer pain point that I see being potentially a long-term problem for people is too many applications to subscribe to, too much content. How do I actually find stuff? Um, you know, something apart from search, you know, discovery is such a big problem. It's still a big problem. Um, you know, as we can get into later, the problem with all of these aggregators is business model. And, uh, it's that, that's the, that's the big, big, tough nut to crack. Um, and, uh, so, so yeah, there was no, there was not at all. I thought that went into this design to start building, you know,

AI assessment note: “Exactly. There was not a whole lot of, like, prep and, and thought”

Answered produced feed D 5 · C 4 · P 4 · Cm 3 4.15

Q story has been awesome. Um, I, I guess if you had, you know, going through all this, like, you know, I, I love just the story of what you Build and how you were able to weave this into, you know, a successful acquisition. If you had to give, um, just three pieces of advice to founders, you know, looking to get acquired, what do you think those would be?

A Um, break down the most valuable assets of the business. Um, and then kind of talk to friends that are not a part of your day to day and kind of talk about those assets in particular. Like when we broke down, like our Instagram account, 600,000 people, like That's valuable to a brand, and either we're going to PCL this and sell it off individually, or we're going to find a buyer for everything. Fortunately, we did find a buyer for everything, but if all of your assets individually are worth something, it's probably a premium to buying everything together, unless you can find that perfect buyer. We were lucky. We found some luck and wanted everything. Um, but if, if you're in a situation where you're ready to sell, you could probably find a premium for every different asset that you'd find. Um, so number one I'd say is, is break down those assets. Determine a value for them in, as far as they get a, um, added premium, and then potentially go find buyers for individual assets that way. Um, number two is, uh, probably, um, go in person, you know, talk to biz dev people in person. It's their job to scout acquisitions. So like if they want to do partnerships, they want to buy, like go talk to them.

AI assessment note: “break down the most valuable assets of the business.”

Answered produced feed D 4 · C 4 · P 4 · Cm 3 3.85

Q where I don't watch a lot of TV. I'm just kind of like, all right, it's growing fatigue. So, okay, I get the problem. And, and now this, this is like a, a meaty big, um, problem because you're working with Netflix and Hulu. Um, how did you, what did your go to market look like in terms of getting this in the hands of, um, Um, customers or usage?

A Yeah, good question. So number one was making sure that technology worked. And then number two was building out. So unlike what I would recommend for most entrepreneurs is like just build and ship the first version. Um, we had a competitor, a very successful competitor that did that. They built just for mobile and they did really well on mobile. But people don't really watch content on mobile while everyone comes out on mobile. Um, And so like, if you're on a couch, you're not going to be watching Netflix on this thing, especially if you have web mobile phone, if you have a message, it's not how people. So, but they did it, they got, they acquired users that way really wild. So what we wanted to do for our GTM early on was let's develop for everything. So like let's develop for iOS and Android, let's develop for CTV. So, um, Apple TV, Android TV, and it was not hard to, let's develop for Roku. Um, let's develop for web and let's develop for tablets. Like, let's adapt for tablets. So anywhere where you're watching your content, you'll also be able just to Pull up your playlist or whatever, you know, the algorithms of who you are and what we're trying to watch. Um, and that's a very expensive technological way to launch a product.

AI assessment note: “what we wanted to do for our GTM early on was let's develop for everything”

Partly produced feed D 3 · C 4 · P 4 · Cm 3 3.55

Q Very nice. But, um, so now I'm wondering, um, what, what made you decide to sell the company?

A Covid happened, and, um, you know, you would think the opposite happened when people are at home watching how it's at any place at the surface, uh, but a very, Quickly. Uh, we were VC backed. Um, we needed to keep raising money in order to, um, maintain this free service and platform that we provided people. So very quickly became apparent that we needed to pivot into a B to B strategy, something that we could actually get money from. You know, we didn't have a hundred million users. We couldn't monetize via ads. Um, and, and that also was kind of getting a little shady, you know, Facebook was getting a lot of flack during that time, um, for monetizing on user data. So we pivoted to a B to B strategy. Um, where we saw an opportunity with a company like Nielsen and Cantor to, um, create like a, a streaming, um, big data, uh, opportunity for investment companies, um, to learn what people were streaming, what people were subscribing to and unsubscribing to, um, you know, specifically that metric that is so valuable to people, um, especially here in the financial services industry. I want to know whether Netflix is going to have a good or bad quarter according to analyst expectations. So we had this robust data set of people telling us what they were subscribing to and what they were unsubscribing to and why. And if we could build a B to B platform that would enable us to kind of e…

AI assessment note: “Covid happened... we needed to keep raising money... became apparent that we needed to pivot”

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