The Exchanges

Q Amazing. Okay, so now that we understand the funnel, tell me about the price. How do you decide what to charge?

A I think the, the, the price was There are like two stuff. It's, um, first one is like a market benchmark, uh, and you compare to like existing solutions, et cetera. So we decided to go with like 10 dollars per month per user. And the second stuff is also based on the, I would say like the willingness, willingness to pay and or indispensable your tool is. And for example, in some, uh, teams like product design and so on, we know that, um, They have like essential workflows built with clap and we can really monetize this easily. So we have like a one entry point, which is like the one, a team plan, which is like 10 dollars per month per user. But then we can also upsell to like 20, 30 dollars per month per user by adding like other features such as like meeting recording and so on.

AI assessment note: “first one is like a market benchmark... And the second stuff is also based on”

Q Okay, so no, no revenue. Okay, got it. So you, when did you start coding? You started coding, I think, back in twenty-twenty, right?

A No, we actually, like, started coding, uh, end of twenty-twenty, beginning of twenty-twenty-one. Um, for six months, we really, uh, build the product. Uh, we launched in private beta in July twenty-twenty-one for, so for actually, like, for 10 months, we remained in private beta. Uh, we had actually, like, a huge white list of, uh, 3000 users. So we had a lot of, like, people to onboard, but I think the goal was really to, um, understand, like, the use cases, uh, where we have, like, a quick activation and virality, um, also validate that the retention is good, and once we had, like, a good user retention, that's the moment we decided to open the product, um, rebuild, like, the website, the branding, the content, and so on, refine the onboarding to say, okay, now we are going to test to open the product on the product end.

AI assessment note: “we actually, like, started coding, uh, end of twenty-twenty, beginning of twenty-twenty-one.”

Q Okay. And, and so what is your goal? When do you guys want to launch pricing?

A Um, it's, it's, it's a good question. I think we want to have like a pricing model. We like define when we open the public, uh, we, we open the product to public beta, uh, because like, you know, like the, I think like at first we were like a bit naive, uh, we wanted to launch like the pricing model in like one year or two years, but we realized that if you launch a product that is like free from the beginning and then you launch the pay plan maybe one year after you, it's going to be like super hard. To do it. So what we want to do is really to have like the pricing plan, uh, ready when we open the beta.

AI assessment note: “have like the pricing plan, uh, ready when we open the beta.”

Q And what utility based upsell like will you build? Is it like would a per seat model work or a number of recorded videos per month work or like what's the usage metric?

A Yeah. So basically I think like the, it, it will be like based on like the, the video recorded. Uh, but then the question is also in terms of, like, features limitation. Um, the idea of clap is really to be like a new decision making system, and we are going to launch a lot of, like, features linked to that. You know, like, for example, one of the primitive features of clap is what we call in context feedback. So it's really, like, feedback type with specific, like, minute, but also, like, zone of your, like, video. And right now it's more like text plus, like, emoji feedback. But tomorrow we'll have, like, for example, system of, like, polls, Uh, system of like video feedback or voice feedback, et cetera.

AI assessment note: “it will be like based on like the, the video recorded”

Q top of funnel. We understand conversion into active users, 20% or about 1400 today. So you almost have five, 6000 total signups then, right? So maybe 7000. Yeah. So you've got 1400 active. You guys then start going, you know what? We need to make money from this. We can build a real business. So how did you think about what to charge and who to show the paywall to?

A Okay, so it's actually a good question because we, we have, we try to build a PLG model, and when you build PLG, you always, you always have a debate about what is the right moment to launch monetization, and we actually, like, decided to launch it pretty early, not to have a payroll, but at least to monetize the existing user, because for us, it's really a way to assess if you have product market fit, because, like, meaning if people are ready to pay for it, it means that you have, like, something that you want to scale, So we've done two things for that. Um, the first one is that we actually like contacted, uh, the accounts that we knew, uh, and that we are actually like using a clap a lot with basically like more than 20, 30 users and so on. And the second stuff we did was pure, purely like to show a pop-in in the product saying, uh, you've reached your account limit. Now it's time to pay, uh, head direct to the pricing page and then book a call with me.

AI assessment note: “show a pop-in in the product saying, uh, you've reached your account limit”

Q And what niche are you building it for though, right? So like, if you look at like frame.io for video editing, they do a good job of this, but it's for a very specific niche. Like, are you targeting salespeople or product engineers or something else?

A Yeah. So like the goal for clap is really to build a product for like anyone in the company. And it's funny that you mentioned like frame.io because it was like part of like the, the testing we made to launch like this feature. We use like, we kind of act frame.io to like understand, okay, what drives adoption, what drives engagement on the video. If you want, we like collect feedback. So for us, like the goal is to like build a product that anyone in the company can use. But in terms of like go to market, what we've noticed, like the product teams as we like the, basically like the early adopters, because they have like super, like, you know, like visual use cases, like they want to.

AI assessment note: “the goal for clap is really to build a product for like anyone in the company”

Q Don't you have to, don't you have to go super deep on that niche? Like if you try and be everything for everyone in the company, you just get diluted. But if you build specifically for a product manager, you can go really deep and just dominate and charge more.

A I don't know, because I think in the end, like, our end goal and our mission is we to, you know, like, help people work from anywhere. What we've noticed, like, if you want to work from anywhere and free your calendar from, like, back-to-back meetings, you need to master, like, asynchronous communication. And basically, like, the idea is to say, like, the way it's done today is mostly, like, limited to, like, asynchronous written communication. With Loom, you add context, but you don't have, like, the whole decision-making system. And we like the ideas to like, and the mission of clap is to democratize like this way of like making decisions and like aligning internally. So, uh, I guess like it would change like the mission of the company to say, this is like just for product teams. And the second point.

AI assessment note: “it would change like the mission of the company to say, this is like just for product teams.”

Q Oh, wow. Okay. Got it. And what, what, what got these VCs so excited? Were they VCs that you guys already had relationships with? Cause they saw what you built previously or how'd they find the LinkedIn post?

A Yes, I guess it's like, uh, it's kind of, um, like, it's what people need right now. Um, and you, like, we spend a lot of time really, like, iterating on, like, on the positioning, on the narrative, uh, before, like, making the announcement to make sure, like, it speaks and it resonates to people. Uh, I think, like, what this is like is when you come with, like, a strong narrative, which is not about, like, creating a new product, but, like, creating a new category. Uh, and then, like, we, Also like work with like for a few months before, uh, just to basically like test the ID. So basically like what we did, we did some consulting missions and the idea was to take maybe like the 15, 20 different like products on the market and test them as if it was like our own MVPs. And we like understand, okay, what are like the right use cases, uh, what drives like engagement, what drives like, and in the end we had like a prototype, which was like, I feel like quite precise, and we are like super like, I guess, accurate to explain, okay, this is like the reason why, for example, we need to have like this in context feedback feature. This is like the reason why we need to basically like store like recordings like this way, etc. And I think it was like the mix between, yeah, like the category narrative, but also like the product design, um, We came up with like with the, with the prototype.

AI assessment note: “mix between, yeah, like the category narrative, but also like the product design”