Diving deep into B2B SaaS metrics with Chitra Balasubramanian, CFO at CircleCI

Episode Description

In this episode of Diving Deep, Subscript's CEO, Sidharth, has an engaging conversation with Chitra Balasubramanian, CFO at CircleCI.

Sidharth and Chitra go deep into B2B SaaS metrics as they discuss:

• How analyzing subscription data by cohorts can unlock surprising insights for your business
• Why strategic finance leaders need to double-click into their SaaS metrics
• One critical piece of advice for companies adding usage-based pricing
• Why it's more important than ever for finance teams to master large volumes of data
• And more!
  

Show Notes

Follow Sidharth: https://www.linkedin.com/in/sidharthkakkar/

Follow Chitra: https://www.linkedin.com/in/chitrabalasubramanian/

Follow Subscript: https://www.linkedin.com/company/subscript/

About Diving Deep with Subscript

Diving Deep with Subscript is a video series where we dive deep and explore SaaS metrics with leading investors, CEOs, and finance leaders.

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Episode Transcript

Sidharth Kakkar
So the first question I have for you is why do you think it's important for leadership teams at subscription companies to understand their subscription metrics? What is the "so what" of it to you?

Chitra Balasubramanian
I think it's just so fundamental to the business in order to know what are the causes of revenue growth, what are the areas where if you invested X and you can get Y as a result, I think without understanding the underlying metrics, and particularly for a subscription business, the subscription metrics, they're unique versus kind of classic P&L metrics. Right. You can't necessarily look at your P&L and say, okay, based on the past results, I know I need to invest more here in order to generate additional revenue or what have you. You really do need to dissect the metrics into sort of useful categories and useful modules, if you will, or smaller buckets of information in order to truly understand what's going on. So I think it's just table stakes, honestly. To run a business, you need to understand the foundation of what's driving your business.

Sidharth Kakkar
Yeah. What sort of cadence do you all look at it on? Like, the core metrics that drive the business, especially as a leadership team.

Chitra Balasubramanian
Yeah, we look at it pretty frequently, I would say. And one thing I will kind of caveat a little bit is we do have a subscription element to our business, but also a usage element, too. So there are sort of some unique metrics in both of those categories that we do pay attention to, but we look at metrics every week to see how things are trending. But for certain types of metrics, you do need time and duration and time for the data to really sort of bake, especially cohort metrics. It's something that you need those cohorts to really develop to understand what the patterns are. And so for that, we do look at it in different intervals. The things that we can look at in a shorter cadence, we do, but certain things, you just kind of have to wait it out a little bit to really understand what's going on.

Sidharth Kakkar
The usage based thing is really interesting because you are like pioneers in it, but now everyone else is doing it in the last couple of years, Circle has been doing it for a decade. So I'm curious, like given all that experience, advice for companies that are starting to add a more of a usage based model and how they should think about their business and the business metrics as a whole.

Chitra Balasubramanian
I think it's a really good question. And the biggest advice I would give is spend time operationalizing it. Spend time thinking about what are all the touch points that affect usage from an actual operational infrastructure perspective. In order to be able to truly understand your data, you have to have good plumbing, right? You have to be able to track data points at the customer level, at the product level, as kind of microscopic of a level that is reasonable. It's good to be able to have that in place so that later on you can slice and dice as you need to, to make the business decisions that are kind of at that point in time, relevant. And so I do think spending time understanding the metering system, do we have a good system to understand that? Because that's going to affect billing and visibility to what's being billed. So things like that need to be well thought of kind of at the outset, otherwise it's really hard to sort of dig yourself out of that later on. It just is not possible because with usage data, there's high volumes of data and you need to have a good system to be able to understand it.

Sidharth Kakkar
Yeah, it's been fascinating to me that in the last handful of years, sort of data capabilities have become such an important thing for finance teams. It didn't used to be that way, right?

Chitra Balasubramanian
I think data has always played a role for finance teams. But I would say to your point, the amount of data, the sort of units of data that needs to be processed, there's just so much more that it's hard for finance folks who were just sort of used to excel, being the tool of choice, to really be able to kind of grapple with that much data. So we do need to kind of welcome tools, welcome new methods and data, and really apply sophistication to this data in order to solve the problems we need to solve, in order to model the business, forecast the business, you can't just expect to be able to process all of that and some of the classic tools that we use. So I think it's really important to have good technologies, people focused on different aspects of the problem, because the problem is just growing in complexity to be able to handle the types of data that we need to. It's much like software development, right? There's a ton of complexity in it, just given all of the services that companies use, open source, third party libraries, just a host of kind of interwoven complexity.

Chitra Balasubramanian
And I think the same holds true for data. It really is the foundation of business and it's just getting more and more complex and it's just accelerating in that complexity. It's hard to kind of stay on pace with that without the right tools.

Sidharth Kakkar
So true. I'm curious at Circle, in the time you've been there, there's been such tremendous growth. What are the subscription metrics you've been obsessing over as you've gone through this period of incredible success?

Chitra Balasubramanian
Yeah, definitely. It's evolved over the years. I would say, as our business has shifted to more usage, I'd say some of the classic subscription SaaS metrics we continue to look at unit economics, LTV, CAC, payback, all of these are very critical measures to just constantly keep an eye on. But I would also say any sort of cohorted metrics are just ultimately very critical and we apply this customer segmenting them by cohort, not just in terms of vintage of coming onto the platform, but also based on product adoption, how have those cohorts shaped out? We pay attention to this. I obsess over all of this. I think given that we also have a land and expand business model, paying attention to dollar base net retention, revenue retention is very critical. Are we seeing that appropriate level of adoption over time and again, cohorts are a great way to do this. Segmenting customers by different characteristics as well helps with that kind of understanding. There isn't a single metric that I'm fixated on, really it's a collection of metrics that are all really important because they tell a different piece of the story. Right, so expansion metrics tell you the story of are you able to have that adoption and continual value creation for the customer over time? That is a very specific problem that you want to look at the right metrics for. Are you bringing on customers at the right pace, looking at your new logos and relative to your CAC and other things like that? Right, so there are different things that I like to pay attention to based on what we're trying to solve for.

Sidharth Kakkar
You know, one thing that struck me, I think we met like 18 months ago and every time you've talked since. The thing that struck me is that you use cohort analysis more than almost any other finance leader I know, which is awesome. And the thing that I wanted to ask you is it's so hard to do and so you only end up doing it if you really think it's worth it. And I'm curious, like to you, what is the so what for the business? When you look at your subscription data by cohorts, like, then what?

Chitra Balasubramanian
Yeah, it's really important because I would say that again given how our business model works, where there's both a self serve element, there's also a sort of top down enterprise sales motion and there's a journey that the customer goes through. And the only way you can really understand that journey is to look over time. Right. You need to be able to understand a longer duration of customers. And when you got thousands of customers, it's not always practical to look at it line by line. And you do need to kind of have appropriate groupings to be able to study the data, to be able to make kind of practical analysis happen frequently. Right? Like if you are constantly trying to do it line by line, you won't necessarily see the big picture. There's like a forest for the trees issue there. And so the cohort analysis really helped to process, again, lots of volume of customers over time and it's amazing the trends that come out. Like you really see that there is an underlying motion when you look at the data that way. And so I do think it's very valuable because it helps you understand what's going on.

Chitra Balasubramanian
And if you make changes to the business, again studying that data and seeing if inflection points have changed as a result of a business change, you can see that in the cohorted data very nicely. Like this cohort, which started off under this new model, is developing differently than the previous version of it. And so being able to study that data gives you a lot of understanding on how certain changes to the business actually manifest from a customer perspective.

Sidharth Kakkar
I would think that pricing is like an obvious sort of type of change that impacts the cohorts. Are there others you have in mind as well? Like business changes that then you can see the reflection off in the cohorts and better understand what happened?

Chitra Balasubramanian
Absolutely. The pricing is to your point. Absolutely. You'll see that pretty much immediately in the data. But I would say with regards to other things, if you make changes, for example, that help with a particular stage of the customer's journey, maybe there's a new feature that comes out or there's some extra efforts and work that your customer success team may have done to improve the customer's experience. You may actually see that in the cohort as well. Like there might be a change to when expansion happens. Like maybe they were able to pull it forward by a month by doing certain initiatives and being able to actually see that in the data becomes important. And so again, cohort analysis are a way that you can see across large groupings of customers how these types of changes manifest.

Sidharth Kakkar
That's so good. The staffing is like it's probably the most expensive decision that you make as a business and being able to see the impact of that is absolutely that's great. In an ideal world, what is the level deeper that you wish finance and or executive teams could go into their data? Like, where do you think everyone would benefit if they thought a little bit or a little bit one step further?

Chitra Balasubramanian
Yeah, this probably again varies company to company. For every company I think that double click or the deeper clicks in may be a little bit different. But I think ultimately you want to be able to double click on those areas that reflect the drivers of the business. You don't want to just get more information for the sake of more information. You want to get information, deeper information on what's actually driving change. And sometimes you have to do that by looking at data at a customer level. Sometimes you might have to look at that at not just a product level, but even a kind of subproduct level, if you will, like being able to understand. If you want to just understand why did revenue grow in this cohort earlier than in these other cohorts? That's a question you want to answer. You want to be able to actually double click into something to see that, oh, it's because this product SKU got incredible adoption all of a sudden now the mix of revenue has shifted because of this new thing. But you need to be able to actually double click on something to see that if you don't have that level of deeper level of information kind of indexed to the revenue, it's harder to do that.

Chitra Balasubramanian
Or it just becomes a data project that takes weeks on end. So being able to actually quickly double click and say that's why. I think, again, it could vary from company to company in a usage based model. It very much is going to be at the again, depending on the company itself, it could be more of a data level. It could be more of what are the things that drove additional usage. And then being able to understand that becomes becomes important.

Sidharth Kakkar
That's great. In your time at Circle, you've helped the company raise Series C, D, E, F. I think it's nearly $300 million. So question, as companies think about raising some of these more growth oriented rounds, how do you think about presenting the business to the market? And I don't know, what are the things that have led to such awesome success?

Chitra Balasubramanian
Thank you. I would say this is a very hard thing to do. And I'll say even for me, it's a challenging thing to do. But I think it's very important is to try to simplify the metrics, try to keep it at a layered level. You don't want to go very deep right at once or immediately because it's hard to understand when you're not like in the business day to day, right. So when you're talking to investors or your fundraising, it's got to be at a level that's first understandable at the high level. And of course, you need to be able to kind of back it up with more and more detail as needed. And just having that consistency through the levels and through the layers is really important to kind of have operational. You need to have that sort of available should those questions arise. But I would say at the outset, starting with a tight concise and somewhat high level data set, I think it's important and actually more helpful for everyone involved because it's just more understandable.

Sidharth Kakkar
I think everyone always talks about how to make things simple you have to understand them even better than in order to make them complex.

Chitra Balasubramanian
Yeah, it's hard. It takes actually more time to curate and to get the smaller deck than it is to throw all the slides and throw all of the tabs into a presentation. So it's easier said than done. I think that really taking the time to refine, keep questioning, is this right, is this needed? And keep going through that process, I would say is something that I would recommend doing because it actually saves time later on. Doing that upfront actually makes fundraising processes much smoother when there's that kind of almost tight package ready to go.

Sidharth Kakkar
I'm sure that even before, there's probably this step between the deck, which is simplified and more clear, and then the data room, which I'm assuming has all the stuff there's probably the step where investors maybe double click a little bit. And how do you think about that? How do you want to manage that conversation? And what are the things you sort of come try to make sure that you know super well?

Chitra Balasubramanian
Yeah, I think for businesses, SaaS usage type businesses, I'll go back to the cohort data is important. It's one of those things where ultimately that data set tells you everything. It really does. If it's analyzed correctly in the right way, it can really tell the story of the business pretty well. And so that's something that I like to really understand. How are those cohorts looking over time? Because again, it helps to substantiate also the narrative of the business. Right. It's all in there. And so that's one. And I think that, of course, your financial statements, your three statements are again, you got to have a great grasp on that and understand that backwards, forwards, forecasted, historical, everything kind of well understood. But I would say aside from that, it is these underlying metrics around your sales efficiency, your kind of unit economics, because a lot of tech companies these days are not profitable at the bottom line. Right. There's a certain amount of acceptance that you're going to invest until you get to a stage where you see that leverage. But ultimately it does need to be profitable at a unit economic level. Right. And so being able to understand that well, being able to provide evidence of that becomes important as well in a fundraising process, I would say, like having that command is important because, again, a lot of our companies at this time, we're in invest mode, but you don't want to invest when you're not profitable at that unit level.

Chitra Balasubramanian
So that's very critical. And then everything else is just about time and all of that. So these are some of the things that I would say, really to know well.

Sidharth Kakkar
Yeah, I remember there was this whole thing like we'll sell dollars for ninety cents and then we can volume or something. Okay, I know we're almost the time, so I have one last question for you. Our audience is largely series B, series C company finance folks. And I'm sure many, if not most of them would look up to you for advice. So any advice that you would give both career as well as sort of professional advice generally to those folks?

Chitra Balasubramanian
Yeah, I would say I probably say this a lot, but this is what comes to my mind often, which is things will get more complex right over the course of time. Time and complexity are like best friends, right? So they just work together and at companies as the scale occurs, startups are unique in that just the pace of change is just so great at startups relative to more established mature companies. And I would say with that can come some fear, right, of gosh how are we going to just handle that? And I would say to just take a deep breath. You can embrace those challenges as they come. There are certain things that you want to be able to put in place to manage for kind of upcoming scale. But you know, I think my advice would be like try to look at what those big rocks are. What are some of those big things? If you are able to get those in place early, can just help with that fast pace of growth. And then a lot of the other things you can kind of figure out as they come. I think it's really just a combination of it's like an 80/20 rule.

Chitra Balasubramanian
I try to address the big things. Your data I think is a big one. If you can get some good command around that and sort of the business drivers that will sort of pay dividends over time, then it's just a question of optimizing what you're looking at, what you're reporting on. That may change based on the business, but you have that underlying infrastructure clean. You can kind of evolve and scale with that for quite a while. At some point you may have to supplant that with something bigger but I would say that goes a long way and there may be other things as well where again invest in certain things now that will scale with you for a few years but you'll figure out sort of the details along the way. And I think that approach is helpful not just on the job, but even as you think about career, right, like just every day that you're learning is additive to the career. And I would say that good things come right when you're in the kind of throws of it, things may seem like wild. I think that's all great learning and it helps as you scale in the company.