The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
00:17:41 · Alex Mashrabov, Harry Stebbings
[00:17:41] S0: So that that... That's a great question. So business revenue is slightly over 50%. Wow. Yeah. On the consumer sides, it's also very important to break it down. On the consumer sides, out of these 50 is around like 10% is pure consumer use cases, pure consumer. And that's roughly people who use it on mobile. Mobile. So share of our revenue from mobile is less than 10%. We are very different from many other companies. But there are lots of aspiring creators, like basically those people who are freelancers doing social media marketing projects projects and so on, who try to learn video AI so that they can make more money. It's true that their behavior is a little churny. Within a year, most of them actually come back to try again. And we do believe that over the time, most of them are gonna figure stuff out, and they're just gonna become this new AI native workforce. So it's still important for us to educate them. That's why we invest so much in Hixfield Academy, YouTube channel, and so on. But we also are fully cognizant that we will never be able to win in the markets of subscriptions of $20 a month. So Why? Because I think today, Google and OpenAI, they pursue ads so much. But fundamentally, I think they are going to completely demolish all their prosumer subscription markets, which is $20 a month subscriptions. [00:19:09] S1: Oh, so you're saying that because they provide a horizontal product that's very good, you're just gonna not pay for a lot of the verticalized products that you just pay $20.30 dollars a month for.
00:19:09 · Harry Stebbings, Alex Mashrabov
[00:19:09] S1: Oh, so you're saying that because they provide a horizontal product that's very good, you're just gonna not pay for a lot of the verticalized products that you just pay $20.30 dollars a month for. [00:19:19] S0: Yeah. I do believe that. That's essentially what's gonna happen over the time. I know this is a very contrarian bet, but at least we can see some of that [00:19:27] S1: it cannibalized Canva's growth, if you're honest. A lot of the low hanging fruit on the consumer design side that Canva used to serve can now be done in OpenAI in particular. Is that what you're talking about? [00:19:39] S0: Yeah. And I do believe this is just the most apparent example, but there are a couple more which is which is already happening. And I do believe that's that's why for... At Higgs Field, what what really matters for us is how we... Even if we get someone on, like, $20 a month subscription, how can we show them value? How can we make them to upgrade to over... To spend over thousand dollars a year with us? [00:20:00] S1: Can't believe that's 6,000,000 a year from $99. That's the best ever slide on a fundraising deck. Yeah. [00:20:07] S0: And all of our customers are gonna do the same. Exactly. [00:20:10] S1: Can I ask, you mentioned that kind of churn rates? When you look at
00:20:10 · Harry Stebbings, Alex Mashrabov
[00:20:10] S1: Can I ask, you mentioned that kind of churn rates? When you look at [00:20:13] S0: thirty day retention rates for consumers and ninety day retention rates, what are yours and what is good? So there is quite massive drop within the first month just simply because people don't fully realize the value. That's a core priority for us to actually get better in that, so showcasing the value. Is it, like, half or... No. It's it's maybe, like, 30% drop. Okay. But then it's it's really flat after that. It's... We look obviously at, like, logo retention. I wouldn't say it's great, but because, like, we all remember, like, b to b SaaS era, like, retention was expected to be... Logo retention month one was expected to be over 80%. So clearly, have a lot of work to do on user education to get there, but some things are truly phenomenal. Like, when I look at the core... At the business segments and NRR at month 12, obviously, like, you're gonna argue it's like eighteen months old company, like, what are you talking about? But still, when I look at the numbers which I have today, NRR at month 12 is over 300%. It just never happens in B2B SaaS, right? So that's why I'm saying that while there is substantial churn in month zero and we have to do a better job with user education to address that, expansion is unprecedented.
00:21:27 · Harry Stebbings, Alex Mashrabov
[00:21:27] S1: Can we actually just unpack the two different go to markets? Because you got consumer and you got enterprise. And I spoke to quite a few of your competitors in all honesty before this show. And I said, hey. You've got Alex coming on. What should we ask him? Everyone said the same thing, which was an admission of their respect for this particular kind of GTM. They said you've executed the most impressive influencer campaign in tech. And now what I wanted to understand was when you look at the consumer growth, what worked, what didn't work, and how [00:21:58] S0: do you reflect on that? That's a good question. So first and foremost, like, the goal is to make sure that the best commercial video content is generated on Hixfield, and we show all the workflows of how to make such professional looking videos. And we have an in house team of over a 150 creative professionals. 150. It's almost half of the whole work... Workforce, frankly. And those people, they make product launch videos. They make tutorials. For example, we made the first AI generated movie, which is also obviously a very sensitive topic. But what's important, we open sourced all of it. And what we learned is that for ninety minutes of, let's say, TV quality content, it was over hundred hours of yet generated content. So creative decisioning, picking the right piece is still very important. So that's really what we are focused on, and that's what's driving most of the most of the revenue. So you're saying [00:22:57] S1: the the growth in consumer subscription is through own content and distribution?
00:22:57 · Harry Stebbings, Alex Mashrabov
[00:22:57] S1: the the growth in consumer subscription is through own content and distribution? [00:23:02] S0: Yes. We don't do any page. [00:23:04] S1: Early on, you made an interesting architectural decision to have your own models, and then then you've since walked that back. Can you talk me through why did you choose own models and why the walk back? [00:23:16] S0: Oh, yeah. Obviously, this was obviously, this was my mistake. I'm gonna be... I'm gonna do my best to be transparent. What I need to admit, at some point of time, I really was thinking that chasing benchmarks is valuable, but I don't believe this is just sort of corporate psyops, frankly. I was part of the large organization, so I know what happens. What happens is that everyone just thinks, like, We need to show some progress, so we need to have some benchmark. But then when I talk to the top researchers from these labs, especially larger companies, what happens is that they start to put test data into the training. They start to kind of use leverage test data to use LLM as a judge for training of the models, use all the various tricks to basically gain benchmarks, get quarterly bonuses, so on. That's like, who cares, right? So if I make my couple million dollars a year in one of these labs, I can move to another lab easily. So that's unfortunately what's happening in larger organizations.
00:23:16 · Alex Mashrabov, Harry Stebbings
[00:23:16] S0: Oh, yeah. Obviously, this was obviously, this was my mistake. I'm gonna be... I'm gonna do my best to be transparent. What I need to admit, at some point of time, I really was thinking that chasing benchmarks is valuable, but I don't believe this is just sort of corporate psyops, frankly. I was part of the large organization, so I know what happens. What happens is that everyone just thinks, like, We need to show some progress, so we need to have some benchmark. But then when I talk to the top researchers from these labs, especially larger companies, what happens is that they start to put test data into the training. They start to kind of use leverage test data to use LLM as a judge for training of the models, use all the various tricks to basically gain benchmarks, get quarterly bonuses, so on. That's like, who cares, right? So if I make my couple million dollars a year in one of these labs, I can move to another lab easily. So that's unfortunately what's happening in larger organizations. [00:24:14] S1: That's- Can I just stay on that? Yeah. What do you mean? You're saying that they are incentivized by benchmarks. And so because of that, they are doing artificial things to improve their scoring and benchmarks, which actually don't increase output efficiently.