Bobby Pinero, CEO of Equals, on bringing joy to finance teams

Well, there's obviously the analysis use cases, financial modeling, there's forecasting, there's data analysis. That's one. Another is folks using Excel as a mini database. They just load data in, use it as a place to reference information. Another is the spreadsheet as a project management tool. Another is the spreadsheet as a document or a place to house information that's maybe a little bit more subjective, qualitative, not quantitative.

When you go through the market, you can start to see that products organize themselves against those use cases. So the spreadsheet as a database is the Airtable use case. The spreadsheet as a doc or like as a place where qualitative information lives, that's kinda like Coda and Notion, they play in that space. The spreadsheet as a project management tool, that's Smartsheet. And yet nobody had really taken on the spreadsheet as an analysis tool.

That was the pain that I was feeling. Airtable was around when I was at Intercom. Notion and Coda were around when I was at Intercom. Smartsheet was around, but none of them were viable tools for the problem that I had. So the whole thing was, can we build the best spreadsheet on the market for what is arguably the most powerful use case of Excel—analysis, financial modeling, working with data.

In short, how would you describe Equals?

Equals is a next generation spreadsheet. You can think of Equals in 3 parts. One is a spreadsheet, a spreadsheet that works just like Google Sheets and Excel. And then it's got 2 added components to it. One is it's connected to live data.

So it connects to anywhere you as a software technology business work with your data - any database, data warehouse, but also the most commonly used SaaS tools. And then it connects to all the places where you and your team do your work. And so you can go from raw data to analysis to shared analysis in Slack and email and Google Slides, all on the Equals platform.

Yeah. Can you talk about one thing I'm curious about, how has the core customer evolved over time? Who's using Equals inside the org today and how do you think of the core jobs to be done?

Yeah, so definitely, we built Equals with me in mind. I mean, there were just so many workflows I had at Intercom that we would keep falling back to and we'd say, "Okay, how can we make Equals really awesome for solving that?" And so it led to a lot of the product things that we ultimately built.

The original persona was somebody that looked very similar to me - first finance hire at a technology company, 20 to 50 people. The thing that we were more opinionated about in the beginning was, we really wanted to find finance people that knew SQL. Finance people that know SQL are rare.

As much as it's a hill I die on—because learning SQL, and when I say learning SQL, I mean just writing, pulling from a database, reading, writing a query to be able to pull down information is so basic, finance people can learn it in a matter of weeks, and it will make them 10 times better at their job—it's still a rare thing.

When we set out to build Equals, we were like, we want to find people like Bobby who knew SQL when they're a finance person. And when we do find them, oh my god, they get Equals. They love it. They're like, "Holy shit, this is the thing I've been looking for." And yet they're still very rare.

So in the evolution of our ICP, we've needed to move beyond—despite my own stubbornness on the matter—people that know SQL. And so we've had to build a lot of products to help support finance folks who don't know SQL get familiar and comfortable working with their database. Lots of feedback, lots of iteration. "Hey, does this make sense? Do you understand how to pull this down? Do you understand how to filter this, to join this, without actually understanding the concept of SQL?"

From there, we've moved beyond just the finance persona. We've started to bring in a lot of founders, founders who have to do a lot of early stage analysis. So we've kind of moved down market from where we started, to seed stage, 5 person startups who need to build out a set of reporting to run their company, to raise money.

Then we've moved adjacent to finance, into ops folks as well who do a lot of, it's kind of the most obvious place to move.

You know, at a certain point, 30, 40 people, your company maybe hires their first rev ops person. They have Salesforce in place. They have HubSpot in place. They need to start doing some reporting out of those tools. The out of the box reporting those tools give is pretty mediocre, or pretty limited. And so we find that they have to do a lot of customization and they end up doing in the spreadsheet.

Those that's kind of been the evolution so far, and we pick off a lot of different people and use cases along the way, but those are kind of the 3 core ones that we've found.

What about the data analyst type persona?

We fit less with them. They tend to fall more into the traditional toolset. There's this concept of the modern data stack and data analysts and data analytics engineers. And it's funny because I've always had this weird kind of, I've never really considered myself an analytics person, always just been kind of a finance or business type person.

I find that there's kind of a fork where the more business and finance, ops-type folks, they like to work in a spreadsheet. They're former consultants, former bankers, former PE folks.

Then you get the other, you get more of these analytics folks, and their preferred tooling, and there's a lot of great tooling out there for them, but they'll prefer more to use an IDE or a hex. They like to write their SQL. They like to write their Python. They are totally cool, totally okay. Not the way that I think when I do analysis.

So, again, we come across them every once in a while. There are data analysts that end up using us, but not really the ICP.

Yeah, that's really interesting. I want to come back and chat more about that. You mentioned Equals as a next generation finance tool. We talk about connecting with live data. In your mind, if Equals is a next generation spreadsheet, what is the tooling that goes with a next generation finance stack, and what are some of the characteristics? For Equals customers, what does their finance stack look like, of which Equals is a part?

Yeah, we find that a lot of folks still live on QuickBooks and NetSuite, a lot of the Brex and Ramps of the world, a lot of Airbases. But in my experience, and the reason why there's been an opportunity here, is that when it comes to all of these out of the box reporting or "Hey, we'll set up a bunch of SaaS metrics for you," or "Spend a month with us and we'll click and you'll have all the insights into your business that you need," it just ends up not working.

They end up not being tools that finance professionals feel comfortable falling back into. And so in some ways, there's still just this void, I think, in the finance stack, which is obviously the opportunity that we're chasing with Equals. There's still a void for the majority of the finance professional's workflow.

There are a lot of tools that try to solve particular accounting problems or expense management or vendor management. But there's still a gap in this "Hey, a big part of what we do as finance professionals is understand our business, report on it, share insights, model it." And to this day, I still think most of that happens in Excel, in Google Sheets. We're trying to chip away at that, but nobody has really gotten that stranglehold on that piece of the workflow.

Yeah, that's interesting. You know, there's the famous Steve Jobs quote, "bicycle for the mind." The spreadsheet is something where you also do your thinking. It's not just something where you produce a report. You also use it as a tool for thinking better. So it's kind of interesting to hear you talk about not just better outcomes, but also tools that are part of the creative or analytical process.

That's exactly what we set out to build with Equals. My most compelling pitch on Equals, the thing that if I go the deepest place within myself and say, "Why am I spending this much of my life working on this?" The answer is exactly that - I want to build a tool that inspires people.

There's nothing more fun as an analyst or as a finance person than being on the scent of an answer, an insight. To build a tool that gives people, that makes it fun and joyful and delightful and playful and modern to go and actually hunt down the answers to your business problems. That's the ultimate thing. That's the thing that gets me most excited is to give people something that they're like, "Shit, yeah, I actually want to spend the next hour digging a little bit deeper into this because I've got this tool that makes it really fun to do that."

Finance people, we just haven't had that for so long. Engineers get GitHub, designers get Figma, marketers get, I don't know what marketers get, Google Analytics? You tell me, I don't know the marketing space that well. But you get the point - a bunch of different teams have gotten a bunch of new fun tools. Product people get Linear. Where's the tool for the finance folks that makes it fun for them to do their job and to be good at the thing that they do? That's the whole intent behind what we're trying to build with Equals. How we get there is just semantics.

Yeah, you talk about the challenge of building a horizontal product and horizontal go-to-market. I'd love to address those two things. One is, can you talk about horizontal go-to-market, how you thought about it, what's worked, what you've learned?

Yeah, that's been the hardest thing. That's probably the thing that's probably been the biggest surprise to me. I thought, and it might just be where we are in the journey, but when we started, people were like, "Oh, building a spreadsheet and building a horizontal product, you guys are nuts. Can't do it." And we did it. Not easy, but we did it.

Then it was, "Okay, let's take it to market." And the thing we've learned in going to market is, when we first launched Equals, we talked about it a bunch of different ways, but we talked about it as a next generation spreadsheet or the spreadsheet you've always wanted.

The challenge in that is that “spreadsheet” means a whole lot of things to a whole lot of people. And so in practice, what was actually really hard about this was we just brought in a ton of people looking for a ton of different things.

I would be on sales calls or demos, in any given week, I'd be talking to a finance hire at a Series A company - awesome. I'd be talking to an ops person at a Series A company doing some Salesforce reporting - fine. I'd be talking to a demand gen person at an agency who's trying to automate some AdWords analysis for all of their clients - okay, but tangentially kind of related use case for us.

Then I'd be talking to a support person at a company who's trying to do some support metrics. Then I'd be talking to a pet resort manager who is trying to manage the hours that they staff for their dog resorts. Then I'm talking to a DJ at a DJ booth who has a spreadsheet they use to run their playlist. Then I'm talking to a district manager at a school in New Jersey who's trying to do some analysis for their principals.

I'm sitting there and I'm like, "How can we build good demos? How can we build good onboarding flows for this? How can we build a repeatable sales process when I'm talking to 10 different people across 10 different use cases, across 10 different connectors?" And so it just became really hard to know what to do next, teach other people how to do that, craft our messaging that would land with each one of them.

What we've had to do is just simplify and kind of narrow the scope of the things that we offer to the world and build top of funnel in those things. If you go to our marketing site now, you'll see very prominently at the top of Equals, we can serve a bunch of different use cases, but you'll see we focus on revenue reporting, we focus on CRM reporting, and we focus on a lightweight kind of BI tool for startups.

Those are the three use cases we want coming in the door. Those are the paths by which we've built onboarding flows, paths by which we know how to talk to prospects about. But it's taken us a while to get there.

Now the name of the game is just building those repeatable processes and filling top of funnel for each one of those use cases. But that feels way more tractable than just taking a massive spreadsheet with a bunch of different use cases to market.

On the positioning side, it felt like early on you were kind of leaning into the persona of the finance person who could write SQL. It seemed like, from a product development standpoint, you were building out a lot of data connections. Today, it feels more like you’re leaning into dashboards, reporting, and BI. Has product development followed a progression from data connections to the spreadsheet layer, and then to the display layer? How has product development aligned with your go-to-market strategy for a horizontal product?

Yeah. So there's a bunch of learnings in here. The place where we started with Equals was on the spreadsheet. The spreadsheet was like the foundation of the thing that we had to build. When we first launched Equals, we launched with just one connector, and it was SQL databases. That matched to that persona.

We spent a lot of time working on the spreadsheet itself to start with because we knew the bar for what people would need when they heard "spreadsheet" was insanely high. We didn't want to go out with an MVP product; it was still an MVP product, but it was like a very complete spreadsheet when we first launched. It's gotten a lot better since. We started with the spreadsheet, then we went to connectors. Connectors were always the first big bet with Equals.

We talked about this from the get-go with Equals. The whole thesis was we don't want to change too much. We don't want to change anything about the spreadsheet. The spreadsheet's right. We want the formulas to work the exact same way. We want pivot tables to work the same way. We want charts to work the same way. It should be, down to the keyboard shortcuts, exactly familiar when somebody jumps into Equals. They know what they're doing. We bet that if we build really great data connectors, that will be a 10x experience for people, and it was.

What we learned through that process was that it works really well, but it works really well for an individual contributor in the company. It’s the person who is doing the work. That’s the person you’re saving a bunch of time for. You’re saving time for the analyst or the first finance hire who’s like, "Okay, I spend 5 hours a week building this report, and now I can do it at the click of a button." Awesome. Great. But, guess what? The CEO doesn’t really care about that because the first finance hire might be saving 5 hours, but they were spending that 5 hours on Thursday night anyways doing it. So it doesn’t really matter to the CEO.

The next evolution for Equals was how do we make Equals more powerful, not just for an individual, but for an organization so that more decision makers care about having Equals, seeing Equals, and being exposed to it.

From there came dashboards. Dashboards have been a total game changer since we launched them 6 months ago. We've seen it not only be a tool that opens up sales conversations in the beginning. We can now get in front of a CFO or a VP of finance or a CEO and say, "Hey, look, we’re going to get you a dashboard that looks like this on which you can see all of your core SaaS metrics. You can see your sales pipeline. You can click in and dig into things." They start to get that on a daily basis, and they’re like, "Holy shit, this is powerful."

The evolution has followed who our initial user and buyer was. We’d end up in sales calls and lose deals because it was just the analyst pitching the tool, but the CEO or CFO didn’t get it. Now they do, or now they see it more. It’s more obvious. A big part of what we push now is making dashboards more prominent, leading with dashboards. It’s kind of the end result. It’s the thing that ultimately drives value across the company. For the ones that care, we’ll show you the rest of the product. We’ll show you how you can get there. But for the decision makers, dashboards are the main thing they want to see.

Kinda zooming out a little bit, I'd love to get your help understanding the BI market and how you see it. There have been a few big exits, like Looker. You've got Sigma Computing, which just raised $200 million. ThoughtSpot, which is a pretty hot pre-IPO company, Domo, which raised an ungodly amount of money, and Mode, which recently had an exit. Metabase is a really interesting, powerful tool for connecting to your database and doing some things, but it doesn't seem to be building a massive venture-scale business. How do you see the market, and how do you segment it out?

Yeah. It’s a really tough market. We’ve very intentionally stayed away from being a BI tool and ending up in RFP processes. It’s a very competitive market with not a whole lot of differentiation between the tools. I’m sure if we had the CEOs of each one of these companies on the call right now, they could give us a million reasons why they’re all different, but ultimately they’re not all that different. They’re basically an aggregation and visualization layer that sits on top of a database, each of them. They’ve got slightly different bells and whistles, but that’s what they are.

My whole view on that world is, and I think this is ultimately the opportunity for Equals in one of its grandest forms, if you look at the way that most analysts today work with BI tools, typically what happens in a company is they start with a spreadsheet. They go into Google Sheets and build a prototype for some sort of dashboard. They say, "Hey, team, we gotta track MQLs, and we gotta track MQL conversion rate by channel, and we gotta track that down to paid customer. Here’s what it looks like in Google Sheets. I did a bunch of work to make sure all the data is correct. Everybody agree this is the right thing? Cool."

Then they spend 2 weeks hardening that or building it out in Tableau. When something looks funny on that dashboard, like MQLs spike or conversion rate drops, guess what they do? They download all their data back into Excel and dig into what happened. Then they go fix the dashboard. Maybe it’s a data anomaly, maybe there’s some trend they need to adjust for, whatever. But they bring it back into Excel and then go back into Tableau. It’s this convoluted and roundabout workflow that almost wouldn’t have to exist if a spreadsheet could actually connect data, automate your analysis, and publish a dashboard. You could cut that whole thing out.

I think there’s an opportunity to upend the entire BI market. A big part of our strategy is to get in with early-stage companies and prolong the time before they need to bring in BI tools. Over time, we aim to build enough features in Equals so that you don’t have to go and buy BI tools. You’ve got a visualization, aggregation, and automation tool in a spreadsheet. I see a lot of people doing the same things over and over again in the BI space. I think there’s a whole different factor upon which to attack it, and that’s what we’re trying to do.

You talked about the modern data stack before, and we’ve distinguished it a little bit from Equals. Is it a tailwind for Equals? To what extent are your customers connecting to SaaS versus databases or data warehouses?

To answer the first part of your question, I think it’s... I don’t know if it’s a tailwind or a headwind for us, but one of the big value props of Equals today for our segment of the market, which is, again, downmarket, is that you don’t have to go through this modern data stack process. It’s pretty daunting.

Think about if you’re a Series A company, and you’re the CEO, and you need to hire a finance person or an analytics person, and they’re like, "Okay, we’re gonna bring in the modern data stack." There are like 4 tools in there, plus a 6-month implementation, plus hundreds of thousands of dollars to spend. You have to bring in Snowflake, 5tran or Airbyte, DBT, and a BI tool on top of that. You have to hire an analytics engineer, build transform tables. It’s a beast of a process. By the way, you might build the first version of it, and it’s going to take you 5 years to get it working properly.

We offer an alternative. For companies that want to go through that process, Equals works fine with that. We can plug into your Snowflake database, and you can write SQL against it. Great.

For those who don’t want to go through that whole process or aren’t ready to make that sort of commitment, we offer an alternative. That’s been really compelling for folks. It’s a way to work with their product analytics database, their Postgres database, their HubSpot data, and their Stripe data, all in the same tool without building out all these transformations and data warehouses. We’re kind of agnostic about how people get their data, but we offer an alternative to the modern data stack.

When we talked about the modern finance stack, you mentioned new expense management tools like Brex, Ramp, and Airbase. There was also a brief renaissance of FP&A tools like Runway, Digits, Pry, and Finmark. Pry got acquired by Brex, and Finmark was bought by Bill.com. Do you think there is consolidation happening? One idea is a rebundling, where Equals, for example, might be part of a finance stack productivity suite. How do you see the opportunity for Equals as a standalone company versus being part of a rebundling of the finance stack? What will it take for Equals to succeed as a standalone company?

Good question. If I start at the end and work my way backwards, there’s no doubt in my mind that the market we play in and the opportunity we have is as big as it gets. There’s no fear for me regarding Equals being a standalone company. I think we can build one of the absolute biggest businesses with the scope of the product we have now and will have in the next few years.

I’m not sure how products will end up getting bundled from a finance persona perspective. So much of the FP&A job sits outside of expense management and vendor management. It’s connected to things like Salesforce, HubSpot, QuickBooks, and SQL databases. One thesis I have is that every analyst is becoming a horizontal player across the entire company. A finance analyst now has to know about the forecast model, operating model, Salesforce, demand generation, and product engagement.

That’s the most important part of the finance job, and it doesn’t live in accounting, vendor management, or expense management tools. It’s where most of the value sits for finance folks. I think there’s an interesting play in our position, which is connecting finance to other teams across the company. Not just making finance good at their job, but making it seamless for finance to work with marketing, sales, ops, and analytics. That’s where a lot of the value gets unlocked.

I don’t know how consolidation will play out. Maybe Stripe starts scooping up some of these companies. We’ll have to see; that’s a mystery and a fun part of this.

As we know, Excel is "free." You pay for it in some form or fashion, but it’s free as part of Google Apps or Office. Equals had a freemium plan, which you discontinued, but left the door open to bring it back later. You implied that when Equals is ready to be free, it could be free. Excel and spreadsheets are powerful and accessible because they are free. How do you think about pricing and the bundling question when taking on Excel, or do you even think about it as taking on Excel?

We’re in an early stage right now. We tried free and famously failed at it and shut it off. We’ve left the door open to turn it on eventually. Equals is, in many ways, a power tool for people for whom Excel and Google Sheets don’t cut it anymore. That’s probably why freemium didn’t work. The main differentiator we have is for people doing next-level stuff with their spreadsheet, like automating analysis and pulling in automatic data.

Because we’re a power tool, we can charge and unlock a lot more value for people in terms of time saved and analysis enabled. While we are still anchored on being a power tool and an up-level to their current workflow, we’ll continue not having a freemium offering. We might experiment with it again, perhaps a version of Equals that isn’t connected to live data but offers a spreadsheet plus a dashboard, similar to a Notion-like editor in your spreadsheet. That might fit nicely into someone’s workflow and could be free, but no promises. We’ll see how it plays out.

The Figma comparison is interesting because, as you mentioned, Figma has die-hard loyal customers but also faced challenges with seat expansion outside the core designer persona. How do you think about building a die-hard following among finance people who refuse to work without Equals, versus expanding to adjacent personas?

I remember when Figma was raising their Series A and Series B, the criticism was that design isn’t a big enough space to build a huge business. They proved everyone wrong. You can’t go wrong if you build a tool that people are obsessed with. Investors love the vertical play because if you can build a tool that a team is obsessed with, you’re in a great position.

We obsess about engagement metrics, how people use the product, and how often they use it. We care that there are segments of folks who live in Equals, meaning they are in the product every single day. If you build a horizontal product with clear use cases and people who live in your product, you can build a mega business. It’s not just about finance people being die-hard fans but ensuring high engagement across clear use cases.

You talked about building a lot of product around enabling finance people to not have to write SQL. And one of those products is your AI Assist product, which is you could write natural language and then it writes SQL for you. You also have this guided workflow where you say what you want to do and then Equals progressively aids that. There's this promise of you connect your data sources, manipulate spreadsheet, and then you get your reports. But in between, it's actually much more challenging than that. You might have to understand the schema of the SaaS product you're connecting to, you have to make sense of all that. How do you think about the opportunity with AI and other product to make some of this a lot more frictionless? Does that unlock the ability for, say, a marketing manager to work with Stripe data? Is there that kind of impact potential for some of this glue product that might be a little bit invisible to someone looking from the outside?

For sure, yeah. I think we're just at the very beginning. We are just cracking the surface. I mean, this is what, I don't think I'm saying anything kind of revolutionary here, but we're just cracking the surface of how AI is going to make it into both software products and Equals, obviously being one of them.

I think you're spot on in terms of the ways in which AI starts to become really powerful in Equals. There's the obvious stuff, the easy stuff you could imagine, like a copilot for formulas and a way to go back and forth on "Hey, I've got a data set. Tell me some interesting things. Maybe build me a table, build me a chart." Easy, obvious stuff. There's still some, I don't think any of the AI models that we've tried can quite yet handle that, but we're not far away from it being able for that to exist.

I think the more interesting use cases are kind of what you alluded to where you can imagine, one of the big challenges with Equals is onboarding folks to a new schema, to a dataset. If somebody connects HubSpot and they're like, "Shit, how does this HubSpot schema work? Where do I find the things that I need to find? How do I get it into a format of data that's usable for me to build my analysis?"

I actually think one of the most interesting applications of AI for us, and we're starting to build this, is in our onboarding flows. How do you guide somebody through "This is what the schema looks like. This is maybe what a transformation of your dataset should look like. This is what an output query would be that we get to, say for example, a list of every single opportunity you've created by day with the history of everything that's changed on that opportunity over time."

Imagine if an AI thing could write that for you and show you a sample of the query and it's like, "Okay, well, now I know how to build almost every analysis off of that dataset." And so it's going to be in these subtle, nuanced, glue places where AI gets weaved in, and you almost don't know that AI is doing it for you. But that's a big part of how we're thinking about it.

There's the big launch “make a bunch of noise”-type of thing that is fun and interesting, but then there's a lot of this much deeper foundational product work that I think is where 80% of the value is going to be unlocked for folks.

If everything goes right for Equals over the next 5 years, what will Equals become, and how has the world changed as a result?

Well, I think we touched on it already a bit. For me, Equals has inspired the next set of analysts out there. And it's given folks like me 10 years ago a tool that's purpose-built for them, that they're excited to use, that they want to tell their friends about, that when they go join the next company, they're like, "Woah, okay, where's my Equals license? I need this immediately."

And obviously, look, I want to build a mega business, mega company. I want to inspire the world in the creative and playful ways that we go to market and talk about Equals and build a brand and a reputation. All that's really fun.

But the thing that gives me the most fulfillment is when I run into an analyst who's in Equals and they're like, "Yo, this is awesome. This makes my day-to-day so much more fun, so much better, so much less painful."

And so in 5 years from now, look, I say this to the company all the time, I want to walk into a Starbucks, and instead of seeing 3 out of 5 laptops having Excel open on them, I want to see Equals on them. And maybe Starbucks is wrong, maybe it's Blue Bottle or whatever coffee kids are drinking these days. But you get the point. So that's it. That's Equals in its full incarnation.

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