In this episode we chat with Henrique Cruz (Head of Growth) from Rows.com about creating spreadsheets on steroids with seamless tool integration and powerful AI features. Henrique reveals how Rows makes working with data so much better, more productive, and more fun. Tune in to discover how Rows can elevate your business automation game.

Top 3 Points:

1. Spreadsheets on Steroids: Rows.com offers modern spreadsheets connected to various tools like TikTok, Google Analytics, and internal APIs, making data integration seamless and code-free.
2. AI-Driven Insights: Rows’s AI Analyst feature has driven explosive user growth, enabling businesses to gain insights and automate data analysis with ease.
3. Flexible Data Sharing: The platform’s emphasis on data sharing and collaboration ensures that users can create beautiful, interactive dashboards that are mobile-responsive and easy to share.

Visit Rows.com

Connect with Henrique Cruz (Head of Growth): Henrique Cruz | LinkedIn  

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Hello and welcome back to another episode of the Process and Automation podcast

with the automation guys.

Here at the Process in Automation podcast,

Arno and myself are covering a lot on all things low code, no code, workflow, process

mining, AI agency.

I 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 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 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 today we will find out more about data.

So slightly different angle to our topics.

Usually we come from sort of workflow, task management, and of course, we love data, 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 gross.

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 roles.

And to kick off, can you please share with our

listeners a bit about yourself and what you do at Rose and how it all started?

Yeah, of course, I lead our growth team at Rose.

So Rose is rose.com dot.

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, around marketing, 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 Arnold myself, we have lots of experience, over 20

years of experience.

We're nearly as old as the spreadsheet

provider you were talking about.

So 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

rose in the market?

Yeah, it's really two things.

One of them is Rose is a spreadsheet connected

to the other tools that you use.

So if you're a marketer, roles is connected to

TikTok, to Facebook ads, to Google Analytics, if you're in operation, disconnected to your

postgres or MySQL database, or if you're an 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 will actually skip this.

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 it.

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 the 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 rose special.

Yeah, so sorry, maybe before arno, you jump in.

What kind of sort of target market do you see for rose right now?

Number one, target marketing people, growth people in companies.

So people who already spend a lot of time in spreadsheets and do analysis on marketing

channels, growth channels, faith marketing campaigns, etcetera.

We have then a second group of users that we call them ops.

So people who, for example, connect roles with zapier or connect roles with makeup connectors

to build workflows on the spreadsheet and then lever 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.

We call it everyday tasks for spreadsheets.

Awesome.

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 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.

What have you seen that somebody's built using

rose that 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 roles for

this.

So the first one, one of our really breakout

features is called embeds.

So you imagine you do an analysis and you take

a chart from Rose and you put it in another tool, 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.

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, embed it into an ocean 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, purchase for their 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 with the API to update the inventory, talks with the API to generate, to

generate the purchase order, send it to production.

And it's a very steroid use case for spreadsheets.

And this is where we see the frontier between spreadsheets and building internal tools or

software for teams.

So I would say that 80, 90% of the people are

building these analysis, these reports, lists of leads, etcetera.

And then there's a small minority who are really doing millions of executions on the

spreadsheet, connecting to their APIs, really building a large scale tooling on top of the

spreadsheet.

Okay.

Oh wow, that's brilliant.

So it really becomes 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 chat

GPT, but into spreadsheet formulas like equal sentiment analysis, equal extract text, equal

client fact.

And we see a lot of people building workhorse

for this.

So a common one, we have a, a quite large e

commerce website that whenever there's a new customer support ticket through Make.com or Z,

it adds a new road to Rose, which then runs a classification model with OpenAI and equal

classifies, underscore OpenAI formula to tag it into different tiers of 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.

Okay, all right.

I guess a very pragmatic way to do things and get it done right.

And it's quite interesting.

I guess the add in that you can plug in OpenAI

as well have sort of real time analysis on sentiment, 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 just solve practical

problems, like you said, not just creating spreadsheets to capture date and the usual way

of doing it.

But it sounds like the power is also in the

fact that you can share.

You could do a lot of analysis, which is

great.

I like the fact that there's, there's a

company that actually runs the operations on it.

That's quite a scary thought.

If you say that and you use excel perhaps in

the same sentence and.

They are still out there as well.

So I think it's just at the end of it speaks to the simplicity of 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 X Fortis 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 accustomed 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 zero here, they use a slack there and

then to bring it all together in one usable interface or data driven interface.

That's quite exciting.

We don't want to replace VI 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.

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 how, do you see sort of the future of rose?

And I'm sure there is, there's more AI in it.

Yeah. What I meant was I think the major two value propositions are the data and

the sharing.

AI is a big, big component of rose, actually,

our story is that it took us five years to get to 50,000 users.

And then we launched an AI agent called an AI analyst.

And now in less than one year, we went from 50,000 to a 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 enrolls, you can talk with it, it gives you insights,

prepares to give the 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.

But what I meant is this is a natural extension, I think, of where software is now,

these new LLMs, and every month or every two months you see a relevant 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 nineties.

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, 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. On my mind, that actually sounds like a very interesting use case right there,

to be able to ask spreadsheet questions 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

like? And so we're doing a big AI release in a

month, I think, and just keep pushing.

You have to do a few tests and test runs as well for our community.

Yeah, yeah, definitely.

Interesting.

So I've got a sort of a next question, really.

And this, this is more to do with using Rose 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 Sascha, we talk a lot about automation.

What's the best way to automate something.

Is it a workflow tool?

Is it a case management tool? Is it an RPA bot?

So for me, this is something new.

I had a quick look at the product.

It's add ins, the ability to start processes based on data.

So for people that want to get started with, with this tool, 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.

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 points to point connections, 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 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?

Where does that data come in? How do I transform that data in a spreadsheet

and where does it cope? And seeing, is there automation potential

here? Typically what we see is the data normally

comes from a third party tool.

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 parked 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 variants, data science, things that

require python writing shifts, 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 two or three 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 the tool light growth is just really

powerful, 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.

I think that could be the orchestration layer for two leg rose, isn't it?

Exactly.

We have hundreds of customers that use make,

connected with Rosencrantz, act as a beautiful orchestration part.

Very complex, putting all these things together, and then the data ends in a new row,

in the spreadsheet, in rows.

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 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.

Not a lot of weird questions.

I promised.

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 10th documentary, I think it's hard not to idolize a bit.

Michael Jordan, if you grew up in the nineties 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

wanted 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

Rose, honestly, I've been doing this for about six years.

I've began to love to read about the early computing era and the early web era.

And so people like LMK, Douglas Engelbart, I think they are now more and more bigger

influences to me, just because thinking about how do 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, etcetera.

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 founder with program.

There are a lot of good stories there.

A lot of marketing campaigns that we've run at wrote, were inspired in some of those chapters

or elad's gills like high growth handbook.

Very practical things for today.

Today in those two books, I would like to always have a short memory on, if not then all

of the tokens of chess.

GPT I think I could do pretty well with that,

maybe.

I think people will agree with you on the chat.

GPT 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 Mark

Andreessen shortly after their IPO.

And they like tour the offices of Netscape and

they asked for and they asked American Bryson, who was maybe 24 or 35 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 back 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.

This is the fastest way to accelerate your career, accelerate the company that you're

building.

I think maybe a hard playbook to follow, but I

think it's come back to this often.

Yeah, yeah.

This is of course why by everyone.

Even if it's not, 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, they will be more successful because of that.

And everyone who's not putting AI on everything and you start using it properly,

they will not be successful.

That's knowing in which problem should I adapt it to.

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 two, three, 4% of the world's 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.

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 like it so much.

I think a second would be maybe something

like, even though I don't do it and I've never done it, maybe something like the Catalan 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 the speed.

And I guess the Catalon 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 stack or you're talking with your engineering team.

If you have the Olympian mindset of being able to do ten sports at the world level, then I

think you're probably fine.

Yeah, I think some people look at it, it's a bit unfair.

You're doing the catalog and then you only get one medal, and then you do the swimming and

you get like, eight medals.

So it's a bit tough.

I think there's an episode with.

I think it's Chris Frock and Jerry Seinfeld in

a show that they do.

And I think Chris Frock says something like,

whenever I see a kid playing, doing skateboarding, I know that this kid, and they

do it competitively, I know that this kid is going to be alright 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 Olympia 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?

I spend a lot of time on LinkedIn and Twitter, so if you do Enrique 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, I'm enrique.com.

so that is rows.com and pretty easy to find.

Yeah, perfect.

I will put that anyway into the show notes so

that the listeners and wherever we share it, they will be able to get in touch.

As this is easy as possible.

We put the website link as well.

If you have some other things you like me to share, then 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.