Pricing a Website | Justin Wohlstadter

$1 per question? We charge $19 a question. We started at $8.99 a question, and a month and a half ago we more than doubled our price to $19.99, and still we grew organically by 68%. And there's like an inverse correlation, the more we raise our flat price, like the more demand we get. But it's quite interesting, right, because if you're a consultant, right, and you're getting paid $300 to $400 an hour, and we can save you an hour or 2 of your time digging, What does that work to? It's $19. It's an obvious time arbitrage for you, basically. So you can imagine the people we're catering to right now in the beginning are consultants, advertising agents, entrepreneurs, investors. If you're an entrepreneur and you need to put together a market sizing for a pitch deck, your VC asks you, how large is the drone space? That's a hard question to answer. Right, it's gonna take you a lot of time. Is there an uber-star referral system? Is there? Yeah, that's a really good question. So basically, we have a whole review process screening internally for our researchers, and then at the bottom of every request— actually, this is not mine, so I can't read it, but basically there's a rating system at the bottom, binary system, thumbs up, thumbs down. We did some Wunder research on this, and it turns out binary is better in this case for a number of reasons. But that's another good use case, product development research. But yeah, we have an internal rating system and an external rating system. Hold on a minute, is there an Ubersaw referral system? Oh, referral. I thought it was a rating. Got it, sorry. Yes, exactly. So we have a give one, get one program. So basically for every person you invite who asks a question, you get a free question. So we actually have tons of entrepreneurs who are financing their Wonder Research entirely through Through referrals, which is kind of cool. So that is the product itself. The researchers love it because if you think about job alternatives, right, if you, you know, if you are a stay-at-home mom, right, a PhD completing a degree somewhere, or a retiree, your options are basically you can drive a car for Uber, right, you can do delivery for some startup, right, or maybe flip burgers somewhere, Or you can sit in your home in your pajamas watching Game of Thrones while doing intellectual work without having to own a car and making the same amount of money or more. So it's a really great program for researchers, and it's really exciting. I mean, they love working on like very interesting, compelling questions. And for our customers, we save them a ton of time, and we find insights that they couldn't find on their own. So both sides of the marketplace. place have a high value prop, which has, I think, been one of the reasons why it's been doing so well recently. So that's very exciting. So that's where we are today. It was not easy to get there, and we'll get back into that. Any other questions on that before I hop into it? Yeah.

So if you're charging $19 per question, that means the researcher has to Do you expect them to spend, let's say if they're getting $20 an hour, an hour to do that? Or how does— how do you value their time?

Yeah, so great question. So what we decided to do is we built a marketplace. So basically instead of saying we're getting paid $19, we're going to pay our researchers $12, right, and we're going to take a 40% margin, what we did is questions can be a variable difficulty. Right? So you could ask a question like— you have people asking travel questions, right? I'm traveling to Africa next month. What vaccinations do I need? Or, you know, we have people asking— in fact, when we were charging $8.99, we had people asking relationship advice questions. We had, you know, we had people asking product purchasing questions. So I'm going to buy a TV for under $1,000. What are the best models? So some questions are very easy to answer. Some questions, like the one our friend over here asked, are very difficult to answer.

Right?

It could take hours of research or expertise in that subject area. So what we do is when you ask a question, we post it anonymously to this dashboard that our researchers have access to. Every question is priced with a fixed price. We don't pay per hour. And that question is priced based on difficulty, which is based on a number of different variables, one of which is time on the dashboard, right? And so we pay for a request anywhere between $6 and $30 a question. So if you're a specialist in AI or in home improvement, right, and we price a question at $24 and it takes you 20 minutes to answer, you just made a lot of money, right? So yeah.

I just submitted a question.

Yes, awesome.

So I just paid for it, but it didn't tell me the price. So am I just So I just have to assume that it was $19 no matter what?

It should show the first time you ask a question, you enter your credit card.

Yeah, but I asked the question before I signed up and then it streamlined the process of setting up and registering at the same time.

Yeah, so normally when you ask a question, it will prompt you for a credit card form and deciding to put a credit card form on there is a whole other topic of discussion which I can get into too. It's really fascinating. But so we just last week Required credit card, and at the bottom of that form, maybe we don't make it visible enough. We say this question is $19.99, but your first one's free.

So if you ask a question right now, oh, so I got that for free.

You got a free question, even though I put my credit card in. Even though you put your credit card in. High five. So all of you, yeah, if you ask a question, your first one's free, and you can finance the rest via referring your friends. So this is awesome.

Yeah. What happens if What happens if we think the answer is not good enough? I mean, if I have researched a lot for something, I didn't find the answer, and I try your platform, and he does— he gives me an answer that I found already, it's not good enough, what happens?

So we have a 100% satisfaction guarantee. So when you finish your research, this is what I was getting into before with rating, you'll get a little email that says like, were you satisfied? Happy face, sad face. If you hit the sad face, it'll take you to a page page where you can ask for a redo. And we're happy to do a redo on the house or refund you for your, you know, your pay. So cool. Yeah.

As a follow-up to that, since humans synthesize information differently, is there an option up front for you to see multiple perspectives on the same question as opposed to having a redo button?

That's a really great question. So we had— we never would have thought that people would use it this way. But we actually have consultants who will submit the same question multiple times so that they can get like divergent thinking on the same topic. So yeah, that's it's a huge use case for us, which I think is really fascinating, right? Because the alternative basically our biggest competitor for Wonder is not a startup; it's two things. It's either you doing it yourself and being willing to spend a few hours of your time, or you having an assistant or an analyst. Your team do it, right? But what's interesting is your analyst or assistant can only have one perspective, right? So by basically creating this marginal cost and modularizing this piece of your workflow, you can actually get a lot more value. And you can do things also like parallelize your research, right? So you can ask 10 questions at once, whereas if you had an assistant, they'd only be able to do One at a time.

So, yeah, follow up to that. And so, and that's— there's an issue of human error in that. So just in terms of like the future of how we're going to use technology like AI, where you have like a Watson with good questions and that, are you looking at that in terms of a 5 to 10 year timeline? Yeah, integrating that so you don't have human error at all.

Yeah, also a really good question. So, uh, so I think there's beauty in human Right? Like, I think like we as humans add a lot of value to this process of knowledge synthesis because we are subjective, right? So when you go to Google today, Google is very good at giving you facts and stats, objective things, right? So if you ask Google, why is the sky blue, right, their knowledge graph does a great job of like actually calling out the answer, right? But Google is not good at the subjective. Right? Like, so if you ask for an opinion on something or anything that has a bit of nuance, Google can't show it because that requires human intuition, right? So you're right. Over time, we want to make our researchers smarter and better and faster because doing that makes them more efficient and it means we get to pay them more, right? Because it takes them less time to do something that we can price the same, right? So our short and Midterm goal is how do we build scaffolding around the researcher to make them smarter? And basically over time, 5 to 10 years, we can use AI to augment human intelligence, right? That's our goal.

Really cool stuff.

Thank you.

Yeah.