How we Gained 3 Million Users in Just 3 Months! | Gamma CEO Grant Lee & Jon Noronha

Before you rush into trying to apply new technology, start with a problem. Find a problem or space you're personally passionate about. Because AI aside, if you're going to be starting a business to solve a problem, you're going to be invested in it for many, many years. My name is Grant Lee. I am the CEO and co founder of Gamma Reimagine the way people share and present their ideas. Traditionally, people use tools like PowerPoint and slides to, to encapsulate their thinking and to then communicate that with others. At Gamma, we're trying to build a new set of building blocks to help you achieve the same goals. But doing it in a way that feels new, feels easier, and allows you to generate output that isn't possible with current tools. We have millions of users worldwide. Korea, Japan are among some of our fastest growing countries. Users in this country is really embracing this idea that new building blocks can gives them a potential to create new things. And they're eager to build, they're eager to embrace new technology and they're willing to be these early adopters of things that allows them to free up their creativity in ways that they couldn't do in the past. I've always known that I wanted to start my own business. One of my uncles started a line of a chain of bakeries and my parents even ran their own restaurant. And so very early on I saw the sort of energy they put into building their own business. I've always had that spirit in me to want to do that for myself. I eventually went into a career, something pretty different, where I went into consulting and investment banking, where I got to see what it takes to really build a business and grow a business at scale. What separates a successful business versus one that sort of stalls or is not able to build something long term? Seeing that world allowed me to be exposed to many different types of businesses. I eventually wanted to take what I learned and apply that to a much earlier stage venture. So I ended up joining a startup as a first finance hire. The company name was Optimizely. When I decided to join Optimizely, the decision was driven a lot by a mentor's advice, which is when you see a rocket ship, you strap yourself on and you go for the ride. And Optimizee at the time was going through a phase of hypergrowth. I think the biggest lesson learned from Optimizely is that every business can embrace the spirit of experimentation very early on. And experimentation is going to look different at every stage of the business. When you're very small, experimentation is really about trying to learn from your users, a lot of qualitative feedback, talking to them, understanding what their pain points are, showing them initial concepts or prototypes, and then being willing to go back and iterate on that. Companies that embrace experimentation understand that when you ship a product or a feature, that isn't the end, that is the beginning. That is the beginning of the learning. Learning from users, understanding how they're actually using the product such that you can go back and improve and continue to improve over and over again. Met my two co founders at optimizely. We all joined pretty early on and worked together for five plus years. John is incredibly gifted at listening to all of our customer support tickets.

My name is John Nerona and I am one of the co founders and head of product at Gamma. In college I studied computer science. I wasn't sure if I wanted to be a software engineer because I thought it was very antisocial just sitting in front of a screen and I thought that wasn't really for me. I am an extrovert. I like talking to people and working with people. And I actually found an internship at Microsoft as a product manager. I knew it involved talking to people and working with them to figure out what you're going to build and why you're going to build it. And I was really drawn to that and I ended up sticking with that. So I went back to Microsoft full time as a product manager. When you build a search engine, everything is quantifiable and has metrics. So I learned a lot from that. A couple years into Microsoft, I realized I wanted to be closer to the startup scene, wanted to actually get exposed to more startups. And so I joined a company that had just raised their Series A called Optimizely. And my own job at Optimizely involved either giving presentations or receiving presentations for six to eight hours every day, nonstop in meetings. So that was kind of where the company all started. It was our experience of sitting through that and thinking there has to be a better way to communicate ideas at work. That's how the company was born. So for me, some of the strengths I tried to lean into and really develop as a product manager were constant curiosity. I've always been interested in learning more about how people are actually using a product and what their challenges are. At large companies, that usually meant digging into data. So I would say one of the strengths I've worked most on is quantitative analysis so that you can actually understand your company's metrics. Smaller companies, it's often been much more qualitative so it's doing a lot of very hands on user research and understanding what people are really doing with your products.

Anytime there is a technology shift like AI, there is this temptation for founders to take this technology and then go search for a problem. I think it's always easier to start with acknowledging what problems already exist out there. Find a problem or space you're personally passionate about. Because AI aside, if you're going to be starting a business to solve a problem, you're going to be invested in it for many, many years. You need to be willing to spe time in that space for two, three, four, five years to really be able to know whether or not you can build something special out of that. So before you rush into trying to apply new technology, start with a problem and then figure out, okay, are there ways to take advantage of everything that's out there, not least of which AI, and apply that to solving that problem for your end users. I think when we first started telling people about what we were working on, the problem itself is pretty universal. When you talk to many people, there's very few people that say, I love making slides. And so I think people understood the problem, the problem resonated. What we did was spend a lot of time in the beginning just observing people create PowerPoint presentation. And we saw them doing the same things over and over and spending so much time doing the work to format and design and then oftentimes moving back into like a document and then go back into PowerPoint to like go back to designing. It was a very disjointed process. So we believe that ultimately we can come up with a new way of creating. And a new way of creating requires different building blocks. If it didn't require so much effort to format and design, maybe the overall experience could be dramatically simpler, much faster, and hopefully more delightful for the end user. The first versions of the product are definitely very rudimentary. You're trying to get at the essence of what you believe your product could be one day.

So we built a very basic text editor without a lot of features that was just broken up into sections. And so in each section you could type words, you could add pictures. Then there was a present button where you could step through each of these sections one by one. And when you step through them, you could animate it like a presentation. So most people using our product wouldn't really retain with it. They would try it out and give us some feedback. But it was not a replacement for anybody's workflow.

When your first users are your friends, and former colleagues, you almost can't listen to the type of feedback they tell you because they don't want to hurt your feelings. So what you really do is you try to trust the numbers. Are they coming back to your product without you nudging them or telling them to? You're trying to then just kind of look at patterns in the usage. Where do people drop off? What are people actually using of users that stick around to inform where you think you're making progress?

And actually, the way we got through that early period without a lot of validation was we relied heavily on using our own product. So even though our product wasn't good enough for anybody outside to use, we forced ourselves to use it from very, very early on. For everything we did inside our company, all of our notes, all of our meetings, we even made up reasons to give presentations. But we forced ourselves to do it every, every week. And that process of living inside of our MVP and seeing all the things that were wrong and broken led to constant improvements. Every single week. Our product got 10% better, 10% better, 10% better%, 10% better. And that added up over at least a year, probably even a year and a half before. We had something that I would say was actually good. And that was the first time that we actually launched. Our very first version of this was we had a private beta. So all we had was a landing page, just said a little bit about what our product was and had a sign up button. And through those we, we actually got our first, I want to say maybe 1,000 or 2,000 signups for our private beta.

Our first thousand users was really a gradual sort of snowball over time. We started with any of our friends or former colleagues that spent a lot of time building presentations, and many of them would go on to share it with their co workers or others that they knew that also had the same pain point around building presentations.

But even that wasn't really a product launch. It was just a landing page. We didn't actually publicly launch our product until, I think it was last August. We launched on Product Hunt and we put a lot of work into that Product Hunt launch. We had already tested our products in private beta for several months at that point. And so we knew which parts of it worked well. And we actually relied on a lot of video to show off those things. We redid our landing page and we really tried to nail our messaging and our onboarding for that. That Product Hunt launch also went a lot better than I expected, actually. We ended up being the number one product on Product Hunt and we saw a clear spike in signups, where suddenly we got thousands of signups in our product just over the course of a day. Although we had that first upswing of users, it still plateaued and then leveled off at a lower rate to the point we were getting maybe hundreds of signups a day. After that, it wasn't enough for us, enough for us to feel really confident that we had actually nailed the value proposition. So we spent probably six months after that just iterating with that base of users we were getting. I emailed every single person who signed up and I asked, how did you hear about us? And do you have any feedback for us? I emailed the ones who ended up using the product and also the ones who took one look and didn't use the product. And we actually went through all that feedback and just looked at what were some of the most common problems that people brought up. Sometimes it was missing features, sometimes it was bad expectation setting. So we very gradually iterated on that until we could do a much bigger launch this past March.

At the time of our public beta, we didn't have any of our current AI capabilities. So we actually ended up spending a lot of time after our initial public beta launch really redesigning the entire creation flow with AI at the core. And we realized at some point we would release this to some of our early users to see how. See what the feedback was. And the feedback was tremendously positive. We could see that people that already understood the value of Gamma, once they got AI, it made them work even faster and unlocked a different level of creativity than they had before, and they embraced the tool even more.

And actually, the hard problem before AI was that we could work really, really hard on trying to create a better alternative to slides, but it was very hard for someone to actually see that and grasp what it was. There was this huge blank page problem where we could tell you five benefits of Gamma, but you had to invest an hour of your time to make something cool before you could really see those benefits. And so most people just never got over that threshold. The activation energy was too high. AI has completely changed that. AI lets you see that first hour of magic in the space of one minute instead. And so that totally transformed our onboarding and activation.

So then we prepared for a much larger launch around AI and releasing our AI capabilities. And that's when we just started seeing, you know, usage and engagement go through the roof. And this is at the point where we also started thinking about how would we actually price and package the product.

The big Difference with AI compared to a lot of traditional software products is that AI has a high marginal cost. You have to pay to run these models. And so we realized we couldn't afford to give everybody unlimited usage of our AI for free. Very last minute before our launch, maybe a week before, we quickly built out a system of credits just to limit how much AI you could use at the start. And so we launched with 400 credits per user. When you signed up, they used it a ton. And very quickly they would go from 400 credits to 0 credits and they would say, how do I get more? I want to keep using your product. Why won't you take my money? Basically that became a really strong sign of willingness to pay. And so very quickly monetization went from a low priority to the top priority. Not even because we wanted the money for ourselves, but because we needed a way to unblock these users to use us more. And we built a very hacky, prototypey version of monetization to begin with, where we didn't even have a buy button inside our product. It was purely a link. We would send over support. We used Stripe for monetization and we would manually go into Stripe and create a payment link and send it to somebody and add credits to them. And that very quickly validated that people were willing to pay. I think within an hour of sending our first payment link, the first person paid. And that allowed us maybe like a month and a half ago to launch self serve pricing in the products. And that's what's gotten us past our first thousand paying customers. The one that has most amazed us has just been the sustained signup growth that we're seeing. So we're now in the millions of users. And just recently we crossed over 50,000 people signing up in one day. And actually that day was the 4th of July, which here in the US is like one of our biggest holidays. And so nobody was even at work. But it showed us actually the international growth where people outside the US were discovering our product and using it in ways we couldn't even imagine. So we've been really happy to see how quickly we've been able to monetize many of these new signups.

I definitely see AI as being the ultimate partner to somebody to unlock human creativity. When you have AI in a tool like Gamma, we think of it as having basically a design partner that has unlimited creativity, but also unlimited patience so they can sit with you. They never get bored of the type of questions you ask, they never get bored of the struggles you might have. And AI as your partner then really takes your own work to levels that you wouldn't be able to accomplish on your own and definitely within your the timeline of your own projects.

I think the core competency that we're aiming for is helping people express ideas easily. If you break that down into sort of our different job functions, if you think about our designers, it's about empowering other people's creativity. It's putting yourself in the mind of someone who is actually not a designer themselves, but who needs to express ideas and really having deep empathy for them and finding ways to make their job a lot easier. And then for engineering, it's often about creating a very frictionless user experience, which includes things like performance and reliability and just overall smoothness that contributes to that feeling of like easy, frictionless authoring.

I think it's a really exciting time to be an investor or operator in AI. The speed at which these markets are moving is both intimidating and pretty awe inspiring. That being said, there's clearly a lot of hype in AI and we do see a number of teams that seem to approach building an AI with a mentality like, how do I leverage AI to build a product? And I actually think that's backwards. I'm much more interested in customer obsessed teams that say, hey, what's a customer problem that I've identified that my customers are facing or a point of friction? And out of all of the tools that I could use to go try to address that problem, is AI potentially the best one to do so? I personally am excited about applications, where companies are leveraging AI to move humans from more of a creator role to a curator role. And Gamma, of course, is one of my favorite examples of this.

We believe that Gamma can be that tool that anybody can pick up, learn, embrace, and whatever ideas they want to share or communicate. They can use Gamma to create dramatically beautiful content that they're proud to share with others.