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October 5, 2022

As the CFO Role Expands, a Single Source of Revenue Truth Remains Elusive

Vipul and Jim speak with Vestigo Ventures about the data problem facing modern CFOs, the impact it's having on small and mid-sized businesses, and their journey to create a single source of revenue truth that enables CFOs to drive business health.

Transcript Highlights


The Customer File is somewhat in the HubSpot lore as the ultimate spreadsheet that - regardless of all the other technology investments and systems that we had either built, bought, or partnered with third parties to stand up - actually ran revenue by month, by subscription, by customer, all the way through an IPO.

And so the beloved file started off as any good early-stage company does, with the CFO saying: I can't get my IT team or my product team to help me build and project the story. o I'm going to use my own Excel skills--and maybe some FP&A skills--to actually manage the revenue of a subscription business.

Fast forward from 2008 when the file was first seeded, to 2014 when the file had over a 100,000 records in it, because it had the historical story as well. Not just active customers, but customers that were in trials or freemium. And so let's just say we pushed the boundaries of Excel, we made it through an IPO. The biggest life lesson out of that customer file is there is no shame [in using Excel] because clearly the company did well and Excel is forever. And so for anyone that says they've got the perfect systems, I would just challenge them and say that I'm sure Excel is one of those perfect systems--that tech stack that most SaaS and software companies use these days.


The finance community will call it a roll forward file or an MRR file or a customer file. It's got a lot of different names but it's an Excel sheet that basically has a gross oversimplification in two simple tabs. One is who are my customers and what do they pay me? And what are the dates related to that? And then there's another file that's really long because it has many months of what they actually paid you.

For investments, particularly that are Series B or later, you build a file like that because that's how you do projections. That's what CFOs used to do projections. And so the question that Jim and I started exploring is: it would be cool if you built a platform that would produce this file because the file wasn't the problem, producing the file was the problem.

And that's what we've done at Saasworks. Now as we have found our product market fit, we find ourselves being a little bit bolder, and in the recent demos I said, well hang on, before you leave the call, let me show you the $10 million file, because we've spent about $10 million in the data platform to build this one file.

Everything else is a way to consume what's in that file. But that file is what has taken the longest amount of time and the most engineering hours to build. And believe it or not, we call it the CDF, which stands for Customer Data File.

How do you not name it the customer data file given what Jim had been through? So that's what we're doing and it was pretty fascinating to see how investor mindset-oriented the team that Jim was working with was. He told me, well everybody does this. I said, I've looked at over a thousand companies in the last 10 years and nobody had something auto-populated like this the way you guys have.

That started to germinate this idea: if you could automate this customer data file, it would change the way a business could work. And if it could be as accurate as necessary in order to make good decisions, it could help every department, not just the finance department.

And then we spent about a year and a half researching this topic because we wanted to make sure we weren't a solution looking for a problem. And it turns out everybody really wants something like this customer data file --ergo the $10 million Excel file we've built.


The humbling thing for me as Vipul and I were doing our research over the summer of pre- Sassworks: we were talking to well-funded multi-time founders. People who had built some really interesting businesses or had surrounded themselves with people who had built really interesting businesses and subscriptions were becoming pretty common.

But we would ask some very simple questions like, hey, can you share your last three or four board decks with us? Hey, could you actually just share your last 12 months of revenue? And what really humbled me: 4 out of 5 (then just multiply that by how many conversations we had) literally said, you know, no, I don't really know. I can tell you what we told the board. I can tell you what's in our billing systems like Stripe, Zora, Recurly, or Chargebee.

In all honesty --and this is not a knock against them-- it's a reflection of how hard it is to do this. They didn't actually have audit quality or even investor quality revenue metrics.

That's what finally hit me when the feedback from these founders was, Yeah, I don't have that and I would like to have that.

It's less about using the BI tools or using the products out there. It's really about getting the data right, which is really the art and the science, not one or the other. And I think that's probably why HubSpot spent so much maintaining that customer file-- because it was a source of truth that you could make business, finance, and investment decisions from.


There's a lot written about saying, “hey find this sort of north star when you're building something and say what are you gonna build towards?

We know what the 1% or the 0.01% are spending. You just heard it from Jim, three people turned into 12, right? And that's just 12 full-time people - who knows what the part-time resources were before you're spending millions of dollars building this customer data file.

So the thought process here was: how do you approach this? How do you go about this? And having been on the investing side with Pyramid, we learned our way through it. Once you've seen the dark side and you understand how investing works, you say, hey, you know what? There's really a method to this madness of doing research.

So, one of the things we did is we spent nearly a year researching and saying let's make sure we're not a solution looking for a problem. And that is something I learned on the investing side, which is too often you would meet companies that started to show wear and tear early in their journey because it was a solution looking for a problem. That's why Jim and I spent the time saying, let's meet a hundred plus finance and operating teams and founding teams. Let's meet dozens of VC and PE firms.

One of the things we changed here is hey, why take that risk? We've got six to nine months. If this is a good idea and we think it's a multi-decade secular backdrop--it's a good trend to go into--then what is it gonna matter when we start, right? Whether it's six months here or six months there. So that was a pretty big difference in terms of what we found.

You would hear from founders over and over saying, if only I would get a chance to build it, right? If they did know that it wasn't a solution looking for a problem. The second thing was I'd like just some time to build it, right? But too often you heard stories of people building something that did 80% of what everybody wanted and a hundred percent of what nobody wanted.

As an investor, one of the first things you wanna figure out is, how happy are some of your earlier customers. Did you really nail the value prop for them before starting to scale it? So we took a second learning and said, let's really make sure we get this right for a handful of customers.

So Jim and I started just coming up with names like Data Volunteer or Design Partner. And we saidwe're gonna build it with those customers with true openness and transparency. We wanna make sure we meet a hundred percent of your needs, so they got something that's working for them.

Now if you're gonna do those two things, the third lesson is to make sure you match the nature of the capital. If you wanna build it right, you need these Data Volunteers, then make sure you have the right “patient capital.” When we raised the capital, what does that mean? What does patient capital mean? What does the right type of capital mean?

We knew that this thing was hard to build, and we knew that it was going to be expensive, so we didn't raise a million-dollar angel round. We said, let's bring in the right kind of folks but also the right amount of capital. Our angel round ended up being almost $6 million in terms of what we raised. And that was because we knew we needed it to build this customer data file. As simple as it sounds, simple things are the most expensive things to build, it was gonna take some time.

We're nearly three years into this journey at this point serving three customers and saying, hey let's make sure we nail it for them. That was pretty darn cool to be able to do because it was once we knew that these three customers are super happy, is when we started to commercialize and go to market. Until then, we didn't even really have a website. We didn't need one. Our investors were okay with that. Our team was okay with that and our customers were okay with that because the only customers were people that volunteered to work with us.


We're selling to what we believe is the future - at least for the next decade if not two decades - what we're calling The Office of the CFO.

Selling to them is really hard because they've been extremely underserved. And so we think of it as the rise of the CFO.

A lot of people have to learn through data or experiments who their ideal customer profile is. We have the luxury of doing a little bit of that, but also saying, hey, this is a financing business, it's subscriptions, and the lead constituent is a CFO who really does control the capital both in coming in and going out.

And so if you can make some decisions like that really early on. We've had people join our team and say, we need to build faster or we need more features, and we just say, no, that is not who we are. That is not what our customers want.

Those are really hard early decisions to make and so I encourage any entrepreneur who's going through a lot of inputs to limit the number of inputs. Look at the one or two outputs that they truly believe matter for the success of the business and for their team. I think if you can make some of those irreversible decisions early on--and you're not gonna get them all right--really does help you build and shape the company. Otherwise, there are just way too many inputs out there.


Briefly clarify what SaaS as a financing business means. What I'm hearing from you: by offering a software as a subscription, you are effectively financing the upfront cost that a perpetual license would, and you hope that the customer can grow into the cost. Because it's sort of buy now and pay forever.


Yeah. This same piece of software might have cost a million dollars up front by turning it into a monthly subscription. It's no different than Netflix, right? If you tried to buy that entire video library, I don't know what it would cost and I don't know what I'm gonna use or not use. What the SaaS model really unlocked is pay for the value you're getting and pay for it in installments. And so it is really a financing business. It's a leasing business in a different way. You could give it a lot of different terminology. I have a car as a subscription today. My subscription costs nowhere close to what the car does.


One of the things that we looked at was how to support the office of the CFO. What is the experience they would be comfortable with (because they're likely not technical buyers)? They're really looking for value and that value is in time or dollars or some combination of those. 

So how do we build enough trust and confidence that they're willing to give us data that's pretty sensitive? That data can be used to raise capital pre-IPO. That data is likely going to be used in downstream reporting, internal decision-making, financial planning, and analysis - all the things around the data.

To do that, we looked at it and said, we have to be an extension, not a replacement.

CFOs, heads of finance, CROs…anyone in a C-level position: they don’t have time to log into tools to go get their data. They don’t want to be trained

You're not gonna onboard a CFO to your platform. You're just not. I know I wouldn't if someone calls me and said, “we have to do onboarding.”

So we said, let's flip that on its head and let's break the wheel of SaaS and the beautiful part of SaaS is its software. It's easy to access, it's on the internet or it's over a VPN, or whatever the technical terms are. But for CFOs it's just gimme my data in a way that I can consume it. So by going single tenant that led them to give results, don't promise results. Do the work, don't talk about the work that has to be done, model it to their business. Don't make their business model yours. And I think one big sin of Saas, and this is again where we kind of said product-led growth is great for high volume, low complexity use cases. And it's an amazing model. For low volume, high complexity use cases, which most CFOs are really dealing with, support them, don't encumber them with more work. So our solution is three things:

  1. it’s a very robust, very sophisticated data platform, You could call it custom customer data platform for any technophiles out there listening.
  2. it's data cleansing and data synthesis. And those are fancy words. Everyone's data's a mess. No offense, it happens if you've built a good business because that means you've changed your pricing model, your packaging model. Your customers have evolved, they bought more products. Anyone can show me a clean set of customer data pre-IPO I'll buy you dinner if anyone's willing. I just don't believe it exists. It's like Snuffleupagus, right? They just don't exist. It's really fricking hard.
  3. most products out there today truly want the customer to model and adapt to the product. And that's a huge change. And what that's really saying is, “Hey, congratulations, Mr. And Miss CFO You've built a great $50 million a year business, but your special snowflake isn't that special. And we're gonna tell you how it should look.”

I just don't think that works. SaaS is an extremely nuanced business model, whether it's consumption-based, transaction-based, user-based, pricing, or a combination of all that. It's really nuanced. So the contrarian view we have is:

We're going to build something that feels highly personalized and has the capabilities to allow us to map to the customer's business, but do it in a scalable and repeatable way. 

That's Vipul’s $10 million spreadsheet. Build the tech that allows them to get what a hundred million dollar a year or a hundred billion-dollar a year company has. Give them access to the same thing, which is honestly how SaaS started.

If you look at like a company like Salesforce, they're saying, we're gonna disrupt the Oracles and the seas of the world. We're gonna give you an online CRM for a fraction of the cost. You look at a HubSpot of the world, and they said, Hey, we're gonna give you a sliver of what an Omniture does at a fraction of the cost, so you can sell and support multiple of businesses. We're trying to do the exact same thing for CFOs and C-Suites: enable them to do everything that a multi-billion dollar company would build internally. We're just doing it with them for them using a sophisticated tech platform that we do the hard work


You hear one version of the story and say, “Hey, this is who we believe we serve. Here's who our customers are, here's our best segments and this is where we really excel.” You dive into diligence and you learn something different. It didn't happen all the time, but it happened frequently enough. And what you would learn is this is almost not even fair because the investors would have a mini army looking at your data, picking everything apart, segmenting it, cohorting it, and saying, “Okay, here's where you do really well. Here's where your lifetime value is really good. Here's where your lifetime value is not that great.”

What we found with our customers is you don't wanna find that out during an investment process. You wanna find that out and know that all the time.

That's why when you go to our website, you see “know your revenue” and it's a play on the words, “know your customer.” I learned a lot about KYC preceding the decade of starting SaasWorks. And so we would say, give us a chance to ingest your data. Let us enrich it. Let's bring some outside information in from something as simple as geotagging to going to their websites or really understanding deeply what industry it is.

An example would be if you just use the store-bought tools, it'll say, “Oh wow, a hundred percent of your customers are IT services?” That's probably what it would say for Saasworks. Well, that doesn't help me. What kind of customers? What type, what stage, and what geography?

We would do the unification, enrichment and reconciliation process and we would come back and say, this is a real story. We said, by the way, that segment that you said you shut off? 37% of your revenue is coming from that segment. And you know what? Be really happy you did not shut it off. It has the highest average duration in terms of lifetime value. You have the lowest discounting there. Why would you ever wanna shut this off?

And a lot of times when you're like, Oh, investors told us that was not a great segment, right? It's like, well, but, but know that decision when you make that decision. So that's an example of where you say, Wow, I was about to shut off a segment based on instincts. And the time that it takes to match your instincts with the empirics is just too hard because the work itself of producing this data is boring, right? It's really taking every customer one at a time and geotagging them. Well, who wants to do that manually? Who wants to do all these different things?

To get to the type of insights that you want to get, you have to reconcile from your customer data: your cash data, which is your billing information to the consumption data, which is your usage. So it's not uncommon for our customers to say, “by the way, your customer data (aka CRM) says you have these many customers. Your cash system (billing or invoicing) says you have this many customers and your consumption--your usage or log files--says you have this many customers. By the way, all three numbers are different. That doesn't help if you do a top-down analysis.

What we tell you is which specific things are different. For one of our customers, we said, “you got 7% of your MRI that's super happy customers, they use the product every day. Their closed-won in your CRM. No invoice ever went out. I would bill them.” They seem super happy, right?

I'm not going to lie to you, Jim and I sometimes are a month or two behind on sending an invoice out. That occasionally happens. And every founder listening to this call, if you haven't committed that sin at least once, if not once a month, I don't believe it, right? It happens because you're busy building product culture, making sure that the company's headed in the right direction. What we're saying is: take the guesswork out. When you buy a new home, you put in a home monitoring system. Why? Because you want to know if there's something you need to worry about--you put in a next smoke detector. Why? Because it tells you if there are any harmful ingredients within your home.

Similarly, putting in a revenue monitoring and protection solution like this helps you find those things that you're otherwise not going to go around your “house” saying, “let me see if I can detect ‘smoke.’” That is just silly and not a good use of time. Similarly, it’s detecting which segment is best, which segment is worth, and how that's changing over time. The third example: imagine being able to identify and say, “Hey, wait a second, we have a segment of customers, that uses just as trials.

At SaasWorks we talk a lot with the finance teams we serve saying, bulletproof your metrics and you're going to really, really protect your valuation if you do this. The data is showing us you have a consistent set of trial customers. We should take that out of the KPI mix because if you're including trials in coming up with your churn KPIs and lifetime value KPIs, it's distorted. You just need to accept and acknowledge and say to your team, “by the way, these customers? They just try and they turn after 60 to 90 days. We have excluded that. So that's a third type of insight: being able to find those things that aren't good or bad, they just are.

Suneet Bhatt

the revworks-1

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