#106 Automation and Data...Spreadsheets on Steroids w/ Henrique Cruz (Rows.com)

Hello and welcome back to another episode of the Process and Automation Podcast with the Automation Guys. Yeah, here at the Process and Automation Podcast, Arno and myself are covering a lot on all things low-code, no-code, workflow, process mining, AI agents. Yeah, really, really a lot. So pretty much all things process and automation and everything which is around that. So, and of course today again won't be different as we have another great interview episode planned. Yeah, in today's world, so we know most businesses are running on data. Good automations require good data and AI is depending hugely on data. So yeah, business leaders need to work with data in a meaningful way, but the reality often is that people are stuck with spreadsheet over spreadsheets and more spreadsheets to run the business. And I get, get, get the people who love Excel and all these things. It is there, it's available on everyone's machine, ready to be used, but is it scalable? And is it a great foundation for our business processes and for our businesses going forward? So yeah, we know there is a better way. In fact, many better ways, I think. And, and today we will find out more about data. So, so slightly different angle to our, our topics. Usually we come from sort of workflow task management. And of course, we, we, we love data and we need data. Yeah, today we approach it slightly from a different angle. So without further ado, it is with great pleasure to welcome our next guest. Yeah, he works at the company ROSE and as head of growth. And yeah, with that, welcome Henrik, welcome to the podcast.

Thank you, Sacha. Thank you, Arno, for having me.

Yeah, Henrik, we are very excited to hear your insights today, more about data, and of course, learn more about Rows. And yeah, to kick off, can you please share with our listeners a bit about yourself and what you do at Rows and how it all started?

Yeah, of course. I lead our growth team at Rows. So Rows is rows.com. We're a modern spreadsheet, and I think it really started with the idea that even though we have all of these other tools and all of these SaaS tools, workflow tools, et cetera, at the end of the day, the business language that a billion people know are spreadsheets. And so our whole workplace tools are being transformed, first moving to the cloud, collaboration, now AI tools connecting to other tools. And we feel that the spreadsheet is probably one of the last software tools where the market leader is 40 years old. And we think that there's a very important piece as into why this is the right time to build a new spreadsheet. And so that's what we've been building for the past few years. For me, in growth is really around talking with customers, is around marketing, is about building the onboarding experience, about everything that surrounds our data platforms as well. And that's kind of what I do on the day to day.

Yeah, brilliant. Yeah. So, yeah, Arno and myself, we have lots of experience, over 20 years of experience. We're nearly as old as the spreadsheet provider you were talking to, talking about. So, yeah, we have worked with numerous vendors, of course, to deliver all these sort of data projects, automation projects, local projects. So, where do you see then sort of, there's obviously a lot of tools out there. So, where do you see the competitive edge for Rows in the market?

Yeah, it's really two things. One of them is Rows is a spreadsheet connected to the other tools that you use. So if you're a marketer, Rows is connected to TikTok, to Facebook Ads, to Google Analytics. If you're in operations, it's connected to your Postgres or MySQL database, right? Or if you're in IT or you're a developer, you can connect it to your own internal APIs. So this is a really big value proposition. The data comes with a spreadsheet. You don't need to code. You can import your data. You can analyze it there. This is a big part of how you can make the spreadsheet part of your workflow and not have to code VBA, look for add-ons or anything like that. Then, of course, there's an AI layer, but I'll actually skip this. Then the other big value proposition is the sharing component. So what we see is that spreadsheets weren't built to be shared. That's why when you create a chart, it's like this rectangle on top of your data. That's why if you share it on mobile, it's not responsive at all. It just wasn't built to be a tool for people to share. But at the end of the day, a lot of the things that people do on spreadsheets are going to end up in a PowerPoint or in a report or something that you share with a client. And so our spreadsheet is kind of beautiful by default. So when you create a spreadsheet, you add elements to a page so that it's composable already like a dashboard. When you share your link to your spreadsheet, it is mobile responsive by default. You can add things like date pickers and buttons to make it interactive. And so you can go from a spreadsheet into a dashboard in one click. And so these two things, the data layer and the sharing layer, are really the biggest drivers of what makes Rows special. Yeah.

So, so sorry, maybe before Arno, you, you jump in. What kind of sort of target market do you see for, for Rows?

Right now, number one target market, marketing people, growth people in companies. So people do who already spend a lot of time in spreadsheets and do analysis on marketing channels, growth channels, paid marketing campaigns, etc. We have then a second group of users that we call them ops. So people who, for example, connect Rows with Zapier or connect Rows with Make.com connectors to build workflows on the spreadsheet and then level, level other integrations to do kind of continue the automations. And One of our most popular data connectors is actually HTTP. So people connecting directly to their back offices, connecting directly to their APIs. And so that's kind of a second group. And then the third group are just people who use it for day-to-day spreadsheet things to be build their stock portfolio analysis and track the price of Bitcoin. It can be to use our Chrome extension to scrape leads from LinkedIn and add it into a spreadsheet. That's kind of, we call it everyday tasks. For spreadsheets.

Awesome.

Yeah. Yeah. It looks like you've covered quite a few high-level use cases there anyways, because my next question was about the use case for this. And of course, you know, I think there's unlimited use cases for spreadsheets out there, and it sounds that this is quite an interesting product in the way you can categorize, I guess, the personas of the people that uses it. So my question really is just Obviously, you guys see a lot of use cases out there. For spreadsheets, it's probably quite hard to identify something that stands out, but I'm going to try my luck. You know, what have you seen that somebody's built using Rows that kind of stands out and you think, wow, that's actually quite incredible. This is not just a spreadsheet and a bit of workflow and HTTP request. This is really quite a nice way and a creative way to build something that actually makes a difference and makes a big impact in a business?

Yeah, I'll tell you a traditional type of use case and then a very creative one that maybe it's the one where we say, look, I'm not sure you're supposed to use Rows for this. So the first one, like one of our really breakout features is called embeds. So you imagine you do an analysis and you take a chart from Rows and you put it in another tool. right? And people use it often with a wiki called notion.com, which is a new, like a very modern wiki. So a very typical case we have, for example, very big retail operations who are doing their paid marketing reports in Rows, and then they take the charts and they write a document in Notion and they embed the charts, right? And then the data refreshes every day, for example, and then the charts also automatically refresh. This is kind of a bread and butter type of use case. You come in, import your Google Ads, Facebook Ads, TikTok Ads, analyze the data embedded into a Notion document. A very creative use case that we have, we actually have a customer in South Africa who is a manufacturing firm that uses Rows to manage all of the operations. So using GET, PUT, and POST, they connect to their warehouse system to know the inventory of the different parts. They connect to their like purchased order software to add new purchase orders. And all of it is done through spreadsheets. So you can see there's like a view environment where someone comes in, wants to check the inventory, wants to create a purchase order with a few different items, clicks a few buttons, talks to the API to update the inventory, talks with the API to generate the purchase order, send it to production. And it's a very like steroid use case for spreadsheets. And this is where we see kind of the frontier between spreadsheets and building internal tools or software, software for teams. So I would say that 80, 90% of the people are building these analysis, these reports, lists of leads, etc. And then there's a small minority who are really doing millions of executions on the spreadsheet, connecting to their APIs, really building large-scale tooling on top of the spreadsheet. Okay.

Oh, wow. That's, that's brilliant. So yeah, it really becomes like a like another layer, application layer.

Yeah, we have another interesting use case is we have now a native integration with OpenAI. So you can think of like a wrapper for ChatGPT, but into spreadsheet formulas like equal sentiment analysis, equal extract text, find fact. And we see a lot of people building workflows for this. So a common one, we have a quite large e-commerce website that all of, whenever there's a new customer support ticket through make.com or Zapier, it adds a new row to Rows, which then runs a classification model with OpenAI and equal classifies_openai formula to tag it into different tiers of what, what the customer ticket is about to then generate reports of how many tickets am I getting per week? How are they being tagged? What are people talking about? And then share this with the customer support team and the development team. Okay.

All right.

So yeah, it's a, I guess, a very pragmatic way to, to, to do things and get it done.

Right.

And it's quite interesting, I guess, the, the add-in that you can plug in OpenAI as well, have sort of real-time analysis on sentiment, which, which is good. It sounds like something that's very easy to get started with. So I can imagine from a use case perspective, people will dive in and sort of just solve practical problems, like you said, not just creative spreadsheets to capture date and the usual way of doing it, but it sounds like it's the power is also in the fact that you can share and you could do a lot of analysis, which, which, which is great. I like the fact that there, there, there's a, there's a company that actually runs the operations on there. That's quite a scary thought if you say that and you use Excel perhaps in the same sentence.

Yeah, and they are still out there as well.

So yes, I think it's just at the end of the day, it speaks to the simplicity of a rows and columns interface and how people understand how to put data in, how to read data from that. I think we've all been learning that for decades, and I think people just default to it. Usually all of these reporting tools, and one of their most popular features is always the export as CSV option. Yes, people want to have a flexible, simple way of looking at the data and creating a chart here and filtering it and changing the format. And no tool is really custom to exactly what you want, changing specific color type, and a spreadsheet just adapts to that for simple use cases.

Yeah, it becomes this layer, isn't it? This other layer to connect to all your different platforms, because that's what lots of businesses use indeed. They use Xero here, they use Slack there, and then to bring it all together in one usable interface or data-driven interface, that's quite exciting. Yeah.

And we don't want to replace BI tools, but we know that there's an in-between for you want to look at some data, do some one-off analysis and something that maybe you need a data team to work on, or the opposite, you receive a report or a dashboard and you want to download the data to keep working on it. and you need an interface to do that. And yeah, it's kind of this in-between layer.

Awesome. So yeah, you mentioned earlier, so you might not want to talk about AI, so maybe that was just for this area or so, but do you see, do you see, how do you see, sort of the future of ROS? And I'm sure there is, there's more AI in it.

Yeah. Yeah. What I meant was, I think the, the major two value propositions are the creation and the sharing. AI is a big, big component of Rows, actually. Our story is that it took us 5 years to get to 50,000 users, and then we launched an AI agent called an AI Analyst. And now in less than 1 year, we went from 50,000 to 1 million users on top of the AI feature. And so basically what we've built is an AI agent where any table that you have in Rows, you can talk with it. It gives you insights, prepares pivot tables. You can ask specific questions about your data. And this really took off on social media, people building videos on YouTube on how to use it. We have traffic, thousands of people every day trying the product because of this. And, but what I meant is this is a natural extension, I think, of where software is now, like these new LLMs and every month or every two months you see a relevant enough update that changes a bit how the features that you can build. And I think it's a little bit like being working on the web and on the internet in the late '90s. It is inevitable that this is happening. It's inevitable that every tool will become a little bit of an AI tool. For us, it's really been transformative because a spreadsheet is a very manual process analyzing a spreadsheet, like create a table with this, filter the data through that. What is the campaign with most clicks? What channels are working better? And this is exactly the type of problem that a hybrid LLM plus computation engine can solve together. So this is what we're doing.

Yeah, in my mind, that actually sounds like a very interesting use case right there, to be able to ask spreadsheet questions, right, about your sales data without actually going in and analyzing it yourself. So that sounds pretty powerful, actually.

A lot of the work we've been doing over the last year has been fine-tuning that experience, helping people ask questions, what type of questions. How do they look like? And so we're doing a big AI release in a month, I think, and just keep pushing. Oh, awesome.

I think we have to do a few tests and test runs as well for our community here. Yeah, definitely interesting.

So I've got a sort of a next question really, and this is more to do with using rows and, you know, kind of like with a wider digital experience slash, I suppose, a bit of soft transformation as well, because I can imagine something like ROSE is a really, really good tool, very pragmatic to get started, connect things up. And, you know, looking our sort of world we live in, especially myself and Sasha, we, we talk a lot about automation. What's the best way to automate something? You know, is it a workflow tool? Is it a case management tool? You know, is it an RPA bot? So, you know, so for me, this is sort of something new. I had a quick look at the product. It's adding the ability to sort of start processes based on data. So for people that want to get started with this tool, you know, what is sort of your advice? Where do you get started? What is the sort of things you need to look out for? What's fit for ROSE and perhaps something that you might think, well, that's like a conventional workflow that needs to be a workflow that needs to be done in a workflow tool. So how do you get started?

I think the way that I would think about it is if the job that you're looking to automate requires a lot of point-to-point connections. So if it's a multi-step process, like I receive an invoice on my email address, I need to download it, and then I need to add it to a spreadsheet to extract the code to put it on SAP. It's not really the type of workflow that a spreadsheet will help much. Or if it is like only a two-point connection, when something happens here, I want something else to happen here, then I think there are better tools to solve the job. Where we really excel is thinking from what do I use spreadsheets for today? Okay, where does that data come in? How do I transform that data in a spreadsheet? And where does it go? And seeing is there automation potential here? And typically what we see is the data normally comes from a third-party tool. So maybe I need to extract data from my database, or I need to get data from Facebook, or I need to get data from an API. So this is a point where you can automate through a tool like us, or the data comes from the web. Like, I extract a lot of leads from LinkedIn Sales Navigator, or I take tables from whatever source I found on the web. So here our Chrome extension can help. So where does the data come from? Then what type of manipulation do I do in the data? Is it valid? Data science things that require Python writing scripts, then maybe this is not the right environment, a spreadsheet. Or do I do a lot of adding new columns, filtering data, pivot table, sorting? So that sort of operations. And then how do I want to share the data? Is this something that only lives in my local environment? Do I then need to share it with my boss or my suppliers or my team? And if so, do I need to build a report out of it or an analysis? And if so, like if these 2 or 3 things are true, you need data from an external system, you play around with the data and need to analyze it and you need to share it, then I think a tool like Rows is just really powerful and democratic for any business person. If not, I think there are better tools out there to build complex workflows or build databases or build robots.

Yeah, you mentioned Make there earlier, and I think that could be sort of nearly the orchestration layer for, for, for a tool like Rows, isn't it?

Exactly. We see we have hundreds of customers that use Make connected with Rowzen. There's a beautiful orchestration part, very complex putting all these things together, and then the data ends in a new row in a spreadsheet in Rowzen. Then you take it from there.

Nice. So Henrik, we have a bit of a tradition here on the podcast. We and our listeners like to get to know our guests a bit more. So, so more than just sort of technical and business side. So that's why we like to ask a few quick questions. So maybe you're up for it. Then let's start. Not a lot of weird questions, I promise. So yeah, so yeah, who is your idol and why?

I grew up watching and playing basketball, so maybe this is going to be a little bit of a biased answer, but if you've watched Netflix, The Last Dance documentary, I think it's hard not to idealize a bit Michael Jordan if you grew up in the '90s like me and playing basketball and looking at that competitive spirit and how he approached the game a lot. So I think that would be one for sure, the mindset of someone like Michael Jordan wanting to excel, wanting to win. That's something that I cannot emulate, but I can certainly look up to that. And then I think building the spreadsheet in rows, honestly, I've been doing this for about 6 years, I've began to love to read about the early computing era and the early web era. And so people like Alan Kay, Douglas Engelbart, I think they are now more and more bigger influences to me just because like thinking about how the people use software, how do you use them to create better tools, how do you use them to be more productive is a lot of the things that we think about. And I think these were some of the few people that started doing this, started thinking about it, doing demos, et cetera. So I think like two spectrums, one in the computing space and one in the sports space that I look up to a lot.

Yeah.

And I guess my next question is about reading, and I presume I sort of know the answer to this one, but we'll see. Imagine you can get all the contents and knowledge of a book instantly, or books. Which book or books would you choose?

Well, I think a cheat question is I would put all of the tokens that ChatGPT was trained on into a PDF and I would memorize that book. That would be, I think, very helpful. Book, I think that would be my go-to answer. Books that I go to often, again, I like books on this early age of the web. So things like Founders at Work from Jessica Livingston, the YC co-founder with Paul Graham. There are a lot of good stories there, a lot of marketing campaigns that we've run at Growth were inspired in some of those chapters or Elad Gil's like High Growth Handbook. I think very practical things for today, today in those two books, I would like to always have a short like memory on, if not, then all of the tokens of ChatGPT. I think I could do pretty well with that.

Yeah, maybe I think people will agree with you on the ChatGPT one. Yeah.

Yeah.

So yeah, what's the best advice you have ever received?

When I talk about this with other people of where we are now, I always come back to, I'm not sure if it's an advice, but I come back to an interview that was done with Marc Andreessen shortly after their IPO. And they like tour the offices of Netscape and they asked Marc Andreessen, who was maybe 24 or 25 at the time. So what's the secret? What's the secret of Netscape? And his answer was, the secret is that we're in an exploding market. And this really stuck, like the first time that I heard that, I keep going back to this and sharing this with people, because I think it's really a strong piece of advice in a way, which is, I think the best thing you can do is build something that people want in an exploding market. And this is the fastest way to accelerate your career, accelerate the company that you're building. I think it might be a hard playbook to follow, but I think it's— I come back to this often. Yeah. Yeah.

This is of course why everyone, even if it's not— well, maybe it makes sense for all software companies or for all companies to jump on AI, or maybe it's absolutely the right thing at the right time for them, or maybe not. But really everyone is jumping on it and I'm sure they will be more successful because of that. And everyone who is not putting AI on everything and you start using it properly, they will not be successful.

That's, I think, or at least knowing in which problem should I adapt it to, right? I think this is a big part, but clearly this is not going anywhere. I think just because the capabilities that exist today, if used correctly, would already, I don't know, increase 2, 3, 4% of the world GDP. I don't know, but just the models that we have today, if we apply them well, we could already be doing a lot more even without thinking about AGI or multimodal or all of these related things. Yeah.

So the final question to you is, if you could be an Olympic athlete, what sport would you choose?

Well, the first one would be basketball, I think, just because I, I like it so much. I think a second one would be maybe something like, even though I don't do it and I've never done it, maybe something like decathlon or a marathon. Because you have to be hyper resilient, like if you're in a marathon, I guess, like very resilient all of these hours at this speed. And I guess the Kaftalon is being able to do a lot of different things and a lot of different things well. And I think this translates, especially in building a company, like you, one day you're talking to a customer and then you're writing a spec or you're talking with your engineering team. If you have the Olympian mindset of being able to do 10 sports at the world, level, then I think you're probably fine.

Yeah, I think some people look at it as a bit unfair, isn't it? You're doing the decathlon and then you only get one medal and then you do the swimming and you get like 8 medals or so. So it's sometimes a bit tough.

I think there's an episode with, I think it's Chris Rock and Jerry Seinfeld in a show that they do. And I think Chris Rock says something like, whenever I see a kid playing, doing skateboarding, I know that this kid, like, and they do it competitively, I know that this kid is going to be all right in life because playing skateboards is a lot about, you know, you will fall, you know, you will get hurt, and then you get up and you go and you do it again, knowing that you will fall again. So I think skating is now an Olympic sport. So maybe like that would actually be a better pick.

Yeah. Awesome. Yeah, it was. That was sort of the round of questions. Yeah, it was a great pleasure to have you on the podcast today. So I'm sure our listeners would like to get in touch with you after that episode. What would be the best way for them to reach you?

Me? I spend a lot of time on LinkedIn and Twitter. So if you do antique rose, I hope I'm one of the first hits. If you're more curious about rose or want to learn more about what we're doing, henrik@rows.com. So that is rows.com and I'm pretty easy to find.

Yeah, perfect. Yeah, we'll put that anyway into the show notes so that the listeners and wherever we share it, they will, they will be able to get, get in touch as easy as possible. We put the website link as well in. So if you have some other things you'd like me to share, then yeah, please share them. Yeah, we are coming to the end of this episode. Thank you Henrik for joining us today. And yeah, we will be back with another episode. Very soon, and until then, let's automate it.