Tech Brew Ride Home - (Portfolio Profile) OpenAxis

Episode Date: April 24, 2022

Founder Alex Damianou tells us about OpenAxis, which tells stories with data. If a picture tells a thousand words, how many does a chart tell? Easily and beautifully visualize data with an accessible point-and-click, no-code, no-pivot-table tool. Learn more about the Ride Home Fund. Learn more about your ad choices. Visit megaphone.fm/adchoices

On April 4th, 2023, around 2 in the morning, a man was found stabbed multiple times on a sidewalk in downtown San Francisco. Hey, who did this to you? What happened next turned the story into a political firestorm. Reports have identified the victim as Bob Lee, the founder of Cash App. From Bloomberg Podcasts, this is Foundering, the Killing of Bob Lee, beginning April 16. Welcome to another bonus episode of the TechMeme Right Home, another portfolio profile episode. We're going to talk about another great company that the Right Home Fund has invested in. We're going to talk about Open Access today, which you can find out more about by going to OpenAxus.com.

And we're going to talk to the founder of Open Access. Alex, thanks for coming on the show. Thanks for having you, Brian. All right, Alex, let's do super simple right up top. What is Open Access? What are you doing? Awesome. Yeah. Open Access is a data storytelling platform. We want to simplify and democratize the entire data storytelling process. So anyone, you know, regardless of their technical ability, can tell stories with data.

So you can easily visualize, share, and collaborate. And in doing so, we want to create a sort of community of data explorers and storytellers that can crowdsource insights and work collectively with the second order effects of increasing data transparency, data literacy, and all that fun stuff. So super dumb and simple, forgive me, but essentially you're a tool to help people make graphs, basically explain ideas beyond words, right? Yeah, absolutely. That's one part of it. So when you break down data storytelling, it's actually kind of a long process. You have to find the data, then clean the data, then visualize it or create a chart,

and then perhaps sharing and collaborating. So we do those three things. We help you create a chart very easily, right? It's very simple, simpler than Excel or Tablo or any complicated tools out there. But we also help you find data, clean data, other people might have already sort of uploaded in a community that you can build upon each other's work. So simple data creator plus sort of data repository

plus collaboration tools equals open access. Sort of like a GitHub for finding and putting together the data sort of like you would find and put together your code, right? Exactly, absolutely, and within a community, because, I mean, we can go into it, but we realize that when we try to solve the data visualization problem, people are like, okay, well, where did I find the data or how I clean it? That's actually harder than me actually creating a simple chart. So solely over time, we realize we have to actually condense the entire data storytelling process

and not just solve one part of it. Well, before we get into the details about that, tell me about your, background, your entrepreneurial background, your career, that sort of thing. What led you to this idea, basically? Yeah, absolutely. Good question, because I've never done this before. It's my first tech startup. So the genesis is actually 2020. So the zeitgeist of the year was like no shared basic facts, elections, misinformation. So that was one issue that kind of indicated to me that, okay, we kind of have an issue with data literacy and transparency in society. And the second thing was my last job.

I was the National Policy Director for Andrew Young's 2020 presidential campaign. If you remember, the guy with the math hat, very data-driven ethos. I also never was in a presidential campaign. There's a story behind that if you want me to get into it. Yeah, give me that real quick because I feel like everybody fell backwards accidentally into that campaign. maybe Yang himself as well. Go ahead. Yeah, absolutely. Okay, then I'll take two steps back for context really quickly. Political economists, I worked in the Nine Nations for a bit.

I spent five years abroad in Africa and the Middle East. I was in South Africa, Ghana, Kenya, Abu Dhabi, and Saudi Arabia, mostly conducting economic research and consulting governments to help them improve foreign direct investment. I came back to the U.S. I started my own macroeconomic and geopolitical research firm, mostly selling research to hedge funds that wanted to kind of understand how the world works and then how it impacts the markets.

Really cool work. Terrible outcome input because it just worked in the markets. So that was really like disillusioning. And I was like, well, what can I do next? You know, because my career so far has been looking at like the social contract of government, private sector and civil society and how they work together to kind of just advance their nations. And I never really pulled the government lever. And here comes this guy, Andrew Yang, who's like running the president.

He's an entrepreneur. He's not ideological, David driven. And I thought it was really compelling. Like someone, I think, sent me an Instagram video of him. And I really just started watching a lot of his videos. I read his books. Smart people should build things, which I think every entrepreneur should read. I think it's awesome.

And the war on normal people. And I got really into it. I donated for the first time. I never donated to a candidate before. And I decided to show up. to one of his fundraisers in Dumbull, Brooklyn. I didn't know anybody, by the way, just showed up. And I met him and his team, and it was clear that they had never done it before either.

And we chat and we're leaving at the same time. And then Andrew's Uber arrives before mine. And he kind of remembers me in my name is that, hey, Alex, where are you going? And I said, Midtown. He said, oh, me too. Hop in. So now I have this exclusive 20-minute Uber ride with Andrew Yang. It was awesome. You know, we just chatted about ourselves, our lives, why we make the decisions we make.

And then I kind of just pitched myself and said, hey, like, I'm a political economist. I'd love to help you on any way I can. You have great ideas on domestic policy, you know, human-centered capitalism, universal basic income. Your foreign policy is kind of light. Let me help you out for free. And it's like, okay, cool, because we don't have that much money. I think this was like before the first debate. And I mean, with this team the following week.

But I was so excited Brian to help him out and show value that I put together two decks, 250 slide decks, just full of data on charts, just using data to tell a story about the country on solicited if you didn't ask me for it. And it seemed to pay off because after a meeting or two, I was offered a job that I didn't really know existed, which was to be the national policy director for the entire campaign. And so for the last five or six months of the campaign, I worked on that. And it was an awesome experience to try to craft policy through a data-driven lens and apply like entrepreneurial frameworks, you know, like sprints around, you know, how we, how we

create data and policy. And it was a really awesome experience. And that led me to to realize we'll have an open access. So I can tell you two things that kind of happen in the campaign that led me to want to do something about it. One is it's really hard to tell stories of data and collaborate. Even when you're the data-driven candidate, you know, we would get data from think tanks and academics, you know, pushing their kind of policies. And it was so messy. I would get like version 8 or 9 and 10. And then I would get an email and then I would get, you know, some other form.

And it was just very sloppy and messy to collaborate. That was one thing. The second thing within the campaign, which, you know, I would argue is akin to a small business, was across departments. They struggled to use data for their work. So, for example, the fundraising team could barely use Excel, let alone table, that the CTO was pushing on them. You know, the voter outreach team didn't really know how to use anything.

So the data team became a bottleneck. We became a bottleneck because no one could use existing tools because they were too complicated. We couldn't collaborate with others. And as a result, we were kind of limited in our ability to pump out policies. That was the one internally. Externally, something that was actually having was, I think, kind of cool, was the Yang gang, as they're called, our ardent supporters, would actually take the data from our policies, like universal basic income,

and they would go on the subreddit, the Yang for President's subreddit, and create their own charts. They were actually creating a de facto community where they were collaborating. It's like, oh, what about this data set? What about that chart? To the point that I was actually checking

what they would come up with often because we had a small team, and they were a really helpful resource. So I thought, you know, why can't we have a community where people collaborate around data and kind of crowdsource insights? Because that was brilliant.

And then, yeah, the campaign ended. We lost very badly. And I wanted to, I wasn't really too keen on, like, continuing the government path. I did help out the Biden administration campaign a bit. But I did want to figure out a way to use sort of tech to solve this because we met a lot of tech people in the campaign. This is also a new world for me. Like a lot of our supporters were, you know, from Silicon Valley. And I kind of opened my eyes up to all the problems they were solving with tech.

that was really cool. So I applied to this, what do you call it? One of those startup generators where they were just bringing founders and kind of matchmake. So I came in as, it was called Antler in New York. And I was coming in as a business founder. There's some technical founders. And then they'll see if you can find some founding team with a whole that idea. So I went to that. And it's during the pandemic. So everyone's at home anyway. So there's really a lot of upside to just trying this. And it was really a problem that I wanted to solve. So I met my two co-founders there, essentially.

Patrick, who's a data scientist and a full stack developer. He was at Via Transportation and also the Federal Reserve Bank. And he said, yeah, even as a data scientist at VIA, we were a bottleneck for the marketing team, the comms team, customer success. They kept coming to us to help. And we were always very slow to help them out because they couldn't use any of the existing tools. Then I met Andrew, who is a product development. or designer and he was on Microsoft.

He was also a former management consultant. He's our Harvard Stanford guy. You've got to have one of those. And he said, yeah, even though we were kind of pros at it, it's still, you know, paying the ass to do it within an enterprise if you're not a technical department. So we said, okay, is there a way for us to simplify data story telling? People fundamentally want to understand.

They want to understand themselves, their work, the world. And from my experience, at least, data is fundamental to that truth and is a driver progress but you know it's a little bit intimidating people you know are not that data literate it's hard to be data transparent and just existing tools from our experience are just too complicated so like all right how do we how do we you know democratize it and we came up with a prototype sort of thing where it was a simple data device tool we're like okay what's a what's the biggest problem think creating charts is a hard problem table is too complicated i don't use r or python um so we just

We did that and we got into tech stars with this idea very quickly, which is awesome, kind of validated. At least this is a problem that enterprises have. And we did some customer discovery and we talked to a lot of marketing columns teams and said, yeah, you know, we're expected to use data for work, but we struggle with tools, the data teams, a bottleneck. In fact, sometimes they weaponize data that we can't, you know, use. So it's kind of like a last mile problem with an enterprise. Like, you know, we need the tools to be able to do the work ourselves.

So we said awesome. But we learned that enterprise sales is a long cycle and the CTO and data teams will basically say there's no problem at all. What are you talking about? We don't need whatever you're selling, even though the marketing comp teams are kind of like crying in the corner. So we said, okay, we're not really going to survive, but we try to go direct enterprise. Is there like another use case here?

And then a trend was sort of happening where because a lot of these marketing cons people were like former journalists and they would say you should actually look into the media and industry, they might have this use case. And we realized that there were a lot of journalists leaving their big media companies to start their own substacks and go independent. And we said, okay, well, if they're going alone, they probably want to team more to help them research. They probably not making their own charts.

They probably wouldn't have something branded. So let's talk to them and see there's a use case. And we did. And it was great. Everyone said, yes, I need help. I barely use Excel. I usually just aggregate a bunch of research and do screenshots and it's, and it's a lot of research. just doesn't look good for my sub-second and the brand I'm trying to build.

So if you can solve the two problems of, one, helping me find clean data fast, and two, help me create a simple chart, then I will absolutely use you. And we realize that they're a really cool go-to-market strategy for us because they become like a cashful positive marketing channel, right? If they create charts on our platform and they send it out to their audiences, it creates a lot of impressions, right? And that creates feedback loops and user-generations. content and network effects and that will drive signups.

So this is sort of like our go-to-market theory. We did some tests. And yeah, it was about 5,000 like impressions per sign-up, which is great because a lot of our sub-suckers are being aware-less now, have millions aggregated together in terms of subscribers. So, okay, cool. I think we have a go-to-market. We're going to use writers and journalists, cashful positive marketing channel, and it'll

help us get content on the platform. And then eventually we can kind of be like a Trojan horse into the enterprise. What's called, what do they call it, the bottom up approach, similar to Trading View did it, Slack did it, GitHub did it, where you kind of consumerize a product, get a bunch of users under a freemium model, and you can start converting them into paying users, and then eventually an enterprise will drag it in because everyone will start using and say, why don't we just get an enterprise subscription? So that's been the model and the plan.

And we've just started executing it after we raised our business. around and I mean, I can give you a, you want to tell you how it's gone so far? Well, so to contextualize it, yeah, essentially where we are right now is some of these sub-stackers that are in your beta. If you're reading their substacks, you're going to see, you know, charts and data that they have used your platform to put together and using the YouTube model of the embed.

That's, as you're saying, hopefully going to, you know, spread virally and naturally as these things. things do. And so hopefully it'll clue other people into open access as a tool to do that. But we're right now this month at the beginning of that stage, right? So some of these sub-stackers are sort of coming out of the closet, as it were, with open access. Yeah, absolutely. We're finally getting into onboard. And it's been pretty exciting so far. So when you do actually create a chart in open access, which this enables a lot of the feedback loops, is there's a backlink.

So readers can actually click on it. They can access the data. They can comment, like, and they can actually create a chart on top of the work of the author. So for the author, it's a cool way to use us as a distribution channel for their content, but it's also a cool way for them to get engagement with their readers beyond them just like liking it or commenting on it. Right. And you mentioned the collaboration and the community aspect as well, so that, again, if you're somebody that is trafficking in ideas and trafficking in research, it's, this is also a tool not only to help you do that, but then to sort of crowdsource the sort of idea collection and generation and correction even, basically. Absolutely. Yeah. And it's a place where you can actually find where other people worked on and build upon their work.

And that was a big realization for us talking to writers. A lot of them, when they say, okay, I'm going to write about this, but I actually don't know where to start. Can I just browse your platform and see what people have come up with? So we realized that we had almost like a, what's called the cold start problem, where it's like, okay, writers want to come in and produce content, but they actually already want to have content on it. And then from the reader side, they just want to consume the content.

So we realized that, oh, my God, are we turning into like a social media platform for data and charts? This is kind of interesting. because the biggest benefit for them would be, I would love to just build upon other people's work and see what they have instead of like starting from scratch. Because that's a problem now with existing database tools. You're in a silo. It's up to you to figure out what the inside is you want to draw and how to do that. But with open access, you can just search, you know, wealth or unemployment, and you can see,

okay, there's 20 datasets. You know, this data set has 13 charts on it. Oh, this is a really cool expert on the topic. and it kind of leads you to their content or their sub-stack, whatever it is. And it's just a cool way, like you said, to crowdsource insights. And that's the real kind of benefit that we realize we're creating with this community where you can collaborate and build upon other people's work. So that's what we've been doing with these sub-sac writers now.

We've been really narrowing that category. And we realize that we actually narrow it even more because there's still so many industries, right? Like, is it economic data? Is it political data, climate? So now we've narrowed it even further to just writers who focus on economic data and politics. And it's been going pretty cool so far because over time as they upload these data sets, you're indirectly providing clean data for other people who are built upon. And you're actually creating a source of truth.

We're kind of becoming the hub for economic data or the hub for political data. And that's going to be a cool way to launch into other industries going forward. So, yeah, as we're working on now, building a simple chart creator that you can customize, giving collaboration tools for people to kind of like remix data sets in charts, the same way you would remix like an Instagram, which I think is really fun. And I seem sort of where it goes. But I'm pretty excited about it because I just want to see what people come up with.

I'm, you know, even with COVID-19, like that was probably the only time in history where so many eyeballs are looking at the same data. And what happened? Like, random people came up with really cool insights. I don't know if anyone saw like Thomas Quayos hammering dance. article. Absolutely. He's excited to use us.

You know, he just came up with awesome insights and had 60 million views. So if you give people space and tools, they're going to collaborate and come up with really cool things. So if anyone wants to see what we're talking about, if you go to open access.com and you click on the little beta button, like I'm looking right now, we're recording April 20th. I can see some of the charts that have been created today, this week, from from some of the beta testers. And then if you click on each one,

depending on which one you're looking at, there's obviously, I can see already comments and things like that coming in. And so someone could then build off of the chart that they've drilled down on and rebut or add to or what have you. Where are we in the beta right now? If people were curious right now about signing up and starting to use the platform,

Are we still on a wait list or are we getting close to throwing the doors wide open? If someone listening right now wants to really dive in, what's the status? Yeah, absolutely. So we've onboarded a good chunk of the waitlist already. And we realize that as writers are using us, the readers want to click in and start playing right away. So we're going to actually close it, like, reduce a friction there. And if you want to actually access the beta, you can do it sort of right away. It's like you will have to like log in and you will have to put in your email,

but you'll get beta access the same day. So yeah, you can go right now to open access.com and sign up for the beta and you'll have access the same day. So yeah, we're excited about it. And one thing that you kind of also alluded to before with the writers is they would tell us the biggest pet peeve they have is actually like charts that they can't click on. So they do research to see like a chart from financial times with economists during the rounds. They can't click on it to P&G. It would take them half an hour and actually find the source thing. They actually love that about ours as well.

whenever you have a chart in open access, there's always a backlink. So hopefully over time, we kind of almost have a cultural shift where people are expected to show their data and show their work because they're expected to have that on open access. So that's also kind of exciting. And I'm clicking on it right now, and like I did a tag for Fred. I can't remember what Fred stands for, but it's everyone's favorite sort of data source for, what is it, economic market participation, labor market participation. And so I'm, I can't remember what? click through on this, and here we go. Labor Force participation rate chart.

Looks like this was put together around the State of the Union. It's March 1st, State of the Union 2022. There's various projects that I can click there. So, right, again, already with the cold start sort of problem, like there's existing sort of self-organizing

communities and data sets that are already being populated on there. What is what's the size of the team? right now. Like obviously you've got an MVP that you're starting to push out to the to the public. But where are we on the on the development? Like obviously it's still early days and you're narrow focusing on politics and economics and things like that. But again for people that want to start participating, there's still plenty more to build. So if they get involved,

they can help you sort of dog food and expand the product, right? Yeah, absolutely. Looking for people who obviously I have this problem that they want to deal with, but also believe in the mission, right, of improving data literacy and transparency. The team, so we have the three co-founders. I'm the CEO because I'm not technical. I'm like the traveling salesman, which is what I realized being CEO is, but it's fun. And then we have Patrick, the CTO and Andrew, the CPO, the product officer. It's like, I heard this phrase once, what was it? Hacker, hipster hustler. So we have like the complementary skill set, but the shared.

values which I think is very important. And as we've been building the products, we've hired two more engineers who are both fantastic, Attila and Sam. And we're looking now for a designer to help upgrade our chart templates. Everybody is a beautiful level, almost as if to like a New York Times level. And then probably also somewhat for community and growth because we are realizing we're created community and mentioned the cold start problem and whether it's content moderation or make sure the veracity of data and charts and growing users, that's something we're looking for as well. So, yeah, in terms of team, that's what we're looking at.

But anyone who's either a data enthusiast or wants to do research on a topic, hopefully open access will be a place where they can do that. So if anyone out there is a designer looking for an exciting new gig, get in touch with me, I'll put you in touch with Alex, or go to the website and get in touch with them there. But also, so we're talking about going to market with the sub-stackers because, you know, a lot of them are solepreneurs and things like that. But also, what about like if there are any media organizations that might want to sort of test this out for their own, you know, existing larger team operations?

Are you prepared to work with folks like that right now? Yeah, absolutely. We've actually already engaged with a lot of media companies. There are a few use cases for that, right? So they're a little bit smaller. They might want to use the whole suite, like research as well as chart creation and content distribution. So they can get more subscribers for their platform. And the cool thing why they go to market is it's not too bespoke.

We don't have to actually build more features for the enterprise beyond maybe just privacy and some database integrations. So we are already starting to look at that type of media companies. Then there's also the bigger media companies that the Axios is of the world. world where they would, you don't necessarily need our chart creator because they have multi-million dollar database teams, but they do love the idea of using us as a distribution channel for content or as a data repo where all their charts and datasets are linked to their articles. So now either the readers have more engagement, but they now have a way to acquire more users

when people search for content on open access. So that's probably the natural progression, right? After writers is media companies in terms of sequencing for industry. But a lot of interest from media companies. And again, they were like subsect writers. They do the marketing for us. And then eventually going into the enterprise for those marketing comms teams, which there's a really interest, but we have to make sure we sequence it properly.

Well, then let's end this way by doing a call to action, as it were. Depending on, you know, what you are intrigued by what Open Access could do for you. If anybody wants to get involved with Open Access, where should they go? How should they get started? And there's tens of thousands of really smart tech folks listening right now. If you have any asks from them, that's what these episodes are for as well. So tell us how we can get involved. Yeah, absolutely.

One, yeah, sign up for the beta at www.com. It's AXIS. That's one way to do it. Second way, just tell us what you want to see. You know, like what data is interesting to you? What data is hard to find or, you know, that's, yeah, not cleaned. And how do you envision collaborating with others? That's something that we're also learning about as well.

Like you see all these discussions happening on social media platforms and a lot of it is kind of devoid of data. If it was filled with data, what would that look like? And, yeah, those are probably the two main things. And what media companies would you prefer be more transit? transparent, right? We also, second order effect is making people more accountable. So we create a culture where every time you publish something you're expected to show that your work, that's pretty powerful. But yeah, generally speaking, try it out, tell us what you want to see and join the

cause if you're really interested in this mission that we have, which I think is awesome, because the vision is pretty big. Like, we will become the home of data. And it would take a lot of years. And it's like a 10-year war we're going to go for. But I think it's going to be awesome. We'll have this cultural shift and have some fun on the way. 100%. And as they say, hashtag proud investor, right home fund loves open access. And it is excited to be here right at the moment when you're launching this vision to the world.

Alex, thanks so much for coming on the show and talking about it. Awesome Brian, super fun. Thanks for having me.