Bhavik Vashi: B2B SaaS Masterclass & Business Model Learnings, AI Opportunity Speculation, and Southeast Asia Market Uniqueness - E281

In the discussion between Jeremy Au and Bhavik Vashi, several key insights were shared regarding B2B SaaS, AI, and personal experiences. Regarding B2B SaaS, it was highlighted that building a successful B2B SaaS product at a lower price point requires careful consideration of unit economics, including accurate estimation of customer lifetime value and acquisition costs. Many companies tend to underestimate these factors, leading to challenges in profitability. Additionally, Bhavik emphasized the potential in Asia for B2B SaaS, where lower price points for serving consumers and businesses are matched by lower costs, creating a balanced equation. The impending commoditization of cloud computing was also discussed, which is expected to lower costs for software companies and facilitate higher volume business models.

The conversation shifted to AI, where both participants explored its potential impact. While acknowledging uncertainties, they speculated that proprietary data sets could become increasingly valuable, potentially benefiting startups by leveraging AI technologies. They also mentioned the need for a nuanced approach, considering ethical considerations and potential challenges such as bias.

Lastly, Bhavik shared his personal experience of relocating from the US to Asia. The decision involved leaving behind established personal and professional networks, and while family and friends were reversible, the professional implications were more significant. However, Bhavik expressed satisfaction with his choice and highlighted the growth and learning opportunities it provided. Overall, the discussion provided insights into building B2B SaaS products, the potential of AI, and the personal challenges associated with making bold life decisions.

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Jeremy Au: (00:42)

Hey, Bhavik, really excited to have you on the show. Good to see you. Another UC Berkeley alumnus here on the show and also, this is our fourth time trying to record this. So a lot of blood, sweat, and technical troubleshooting has happened to get to this one.

Bhavik Vashi: (00:57)

Super excited to be here. Go bears and here's to hoping this one is the charm.

Jeremy Au: (01:03)

Yeah, this is the charm. So, Bhavik, could you introduce yourself real quick?

Bhavik Vashi: (01:08)

Yeah, sure. My name's Bhavik Vashi. I currently serve as the Managing Director of the Asia Pacific Carta. Before this, I spent almost a decade at a company called Anaplan, and I've spent most of my career in B2B SaaS.

Jeremy Au: (01:19)

So how did you get into B2B SaaS? Because it's a subset, specialized. It's popular today, but how did you personally get into it?

Bhavik Vashi: (01:30)

Complete luck. If I'm being completely honest with you, I started my career at Big Four so I was at KPMG, and I didn't like it very much. I had a busy season coming up around the corner and I made a goal for myself. I think it was Thanksgiving break that I was going to get out before the busy season. That was my objective and so I just started asking around and trying to find opportunities with somebody that I knew at Deloitte Consulting I was asking for a referral at Deloitte Consulting, but she told me that if you're going to join Deloitte, and if you're going to join the team, you're going to end up working exclusively on projects related to a technology called Anaplan, so rather than come join me and do all of these Anaplan projects, you might want to check out this company called Anaplan. So Anaplan was the only B2B SaaS company I spoke to, and it was the one I ended up joining and then I found myself in the industry.

Jeremy Au: (02:25)

So when you joined B2B SaaS you know you didn't have much, but what were some unexpected or surprising learnings that you learned in building this? Because I think back then it was very new, right? Today, everybody's like, God, it's a playbook. It's a SaaS conference, SaaStr conference, but what were some surprising personal learnings that you took away since you got into it for the first time?

Bhavik Vashi: (02:48)

Yeah, it was super new. I think Salesforce was pioneering, to some degree, the category and so we always used to talk about Salesforce internally as well. I think they were like the benchmark and then Workday was just coming up, at the early stages of Workday. My early learnings about SaaS, I think was just the incredible simplicity of the business model, almost to a point where I was like, is it too good to be true? Because you have this product, you invest in building it more or less once, I mean obviously, there's an ongoing investment, but you get the substantial portion of the value created upfront and then you're just able to sell it and scale a business around it at a gross margin profile anywhere between 85 and 90%, which is incredible.

If you think about any other product then the bottom line is very controllable. I think that was probably one of my first key learnings about how much power we had in terms of determining our outcomes based on our decisions whether to spend more or spend less and I think because of the nature of the product, I joined Anaplan, which effectively helps companies forecast a P&L. I became intimately well-versed with the variables behind a P&L. So I couldn't help but think about our own as I was implementing P&L, forecasting for a company like Workday, which has a very similar business model. So I think that was one of the key learnings and then probably right after that was again, just deep diving on each variable and understanding why it was so hard to move those in a specific direction. Like in Math, it's very easy to say, okay, we're going to drive down implementation support costs by 5%, but why is that so difficult for Anaplan versus Slack, for exampl, And just understanding those were the first things that I fixated on.

Jeremy Au: (04:39)

From that experience, what were some myths or misconceptions that you think people have about B2B SaaS as a result of your learning?

Bhavik Vashi: (04:47)

I think one of them, so as easy as it is to execute, I would say a B2B SaaS business model, I think it's equally challenging to find a genuine problem that you're solving. I think I was very fortunate to have joined a company that had a lot of success because we solved a genuine problem. So much so that we were able to fundraise an IPO and then sell the company again. That only happens if we have tapped into a significant pain point, right?

But for every Anaplan, there were tens if not hundreds of companies that just didn't make it that far and that's because it's so easy. I'd say the barrier to entry is pretty low for SaaS, relatively speaking, versus an asset-intensive industry or something like that. It's also attractive to just try to get something going, but you realize the problem you're solving either A, isn't a problem, B, isn't that big of a problem, or not that many people have the problem. It's very easy to start and fail in SaaS, I think more so than anything else because it requires a little bit less bravery to get in and then equally you can fail pretty quickly as well.

Jeremy Au: (05:54)

Right. That's a very common problem. I think people are like, oh, this is a business problem and then I'm like, well, is it a business problem? I met them and I always joke like, HR officers are all the same. As you go to every company, the HR leader of that equivalent role, cause incentives are so similar. Everybody has an individual personality and everybody's wonderful, but from a purchasing decision, they tend to be very clustered, very similar, but then I always get to it. It's like, I think a classic example was, okay, we think that HR would like to buy this and I'm like, is that number one problem, number two, number three, number four, number five, number six, number seven? So I think it just feels like a lot of folks, like you said, kind of like the identification that business need is so, what's the word, fuzzy. I'm sure you met a lot of folks who kind of had that very fuzzy sense of the role, right?

Bhavik Vashi: (06:49)

Yeah, and there's such a speed element to it as well, like equally on the other side, you'll see insanely successful companies that solved seemingly a very simple problem. I could argue Carta is one of those where it's like a relatively straightforward, simple problem like you're issuing equity to employees, you're managing a cap table, kind of looks the same for most companies, industry agnostic, and so forth. But I think the speed with which you solve the problem.

If you're a first mover, you have a little bit more a runway before anyone else tries to catch up or copies you, which is probably our advantage. But if you're able to capture that quickly, even if your total addressable market isn't that big, but you solve it all by then, you're now an incumbent in so many different accounts where you can expand your footprint differently. Or you could potentially introduce a product or service offering, either adjacent or not to that same customer and that then, you become kind of a multi-product company very quickly and maybe they're all SaaS products and then at some point, if that works out, you can kind of evolve into hopefully being like a platform company and that requires some re-architecture and rethinking of the business model. But, I guess that's the flip side of it, and that's probably what every founder is hoping for to some degree.

They know that making a better calendar app is not the end, be all of their business, but maybe that's the entry point as a simple example. So, then obviously you go back to founding teams and just execution and speed and some of those basics that VCs are thinking about every day.

Jeremy Au: (08:22)

Yeah, I think that's the tricky part. It's like either you're the best version, like Cataly, is a good example. It's like one of those simple ones, which is like, let's avoid passing the ball, ping pong, the meeting time and the location schedule, which is a giant cane in the rear. And then yeah, they did a group work job in a product-led approach, then you have other companies that are much more enterprises. They're trying, like I met an AI company, and they're like, okay, for us to work, we need access to all your company data and we're trying to do this using product like growth and I'm like, oh, hold on one moment. I don't think I want my junior person to pay using his credit card and then upload my company server to your AI machine because I don't think that it's easy for you to cross-sell back to your chief information officer and be like hey, yo, I really want to upsell this product now because he works.

Bhavik Vashi: (09:22)

Yeah. That use case that three people were doing is now going to be the top five spend for the CIO. Yeah.

Jeremy Au: (09:27)

So I think it's that delink between what the products were to sell versus what the sales motion is.

Bhavik Vashi: (09:37)

Yeah. I mean, in our era, I think that's why there were so many disruptive companies. I could argue Anaplan was a disruptive company, but we took a very traditional sales motion with disruptive technology. So we, our sales motion frankly, didn't look significantly different than SAP, Oracle, IBM. The product was disruptively different. Now, we're in like a third generation in that particular category where you're seeing the disruptive product, like Anaplan cross-functional planning. Anybody can use it and it’s very cool, and a different sales motion, which could be more product-led or really user-driven rather than buyer-driven, which I think is a big difference in product development, roadmaps and positioning and everything else.

Jeremy Au: (10:19)

Yeah, I think people tend to get this wrong. I mean, I've met so many founders. They're like, okay, we're going to do enterprise, let sales and then is this not great at enterprise sales? I'm sure you've coached a lot of founders and teams through this process, including your own, right? So do you think these are common, I think failure points you think prevent a team from learning and eventually being able to deliver great enterprise sales motion.

Bhavik Vashi: (10:45)

Yeah. I think this is realizing that enterprise sales, again, just use the same firm you like. You have to solve a problem. You have to really have a strong value proposition and frankly, you probably should have a higher ASP or average sales price associated with your product. I always worry about a company that's running a kind of sales-driven motion with a very low ASP. There's just something missing there. Because if the problem you're solving is super complex and super meaningful and super impactful, then chances are that's going to require a human-to-human interaction at some point to map out a specific context of a specific customer, their problems, and how you, as a product and maybe a product and service are going to help them address that and if you can solve, if you can orient the whole conversation around problem-solving, it's much easier to deduce a good commercial construct, right? Because it's the problem you're solving.

If you're optimizing inventory holdings by 2%, you can do some Math and figure out what the software could be worth. That's like a percentage of ROI, for example. And so that's where enterprise, I think, enterprise or sales led growth makes sense. Because you have, salespeople are good at that and there's a much more kind of, there's a much heavier relationship building aspect to that sales process because at the end of the day, it's trust. Do you trust the words that are coming out of the salesperson's mouth to help you solve the problem? Because, it's not the salesperson who solves the problem.

There's usually an implementation team or a service partner or somebody else who's going to get involved and do the dirty work to some degree and so there's a lot of trust needed to make a big commitment and so I just think everything is elevated in that scenario and so my big learning has this just like, to be honest with yourself as a founder or us as a company of like, which bucket are we in? If it's a simple product solving a relatively straightforward product problem, then let's look at probably product-led and see if you know the thesis is true. And we can just solve that problem quickly, like execution, speed. A bunch of people download it, and a bunch of people start paying port eventually. Great. Fantastic. And then figure out where we go from there versus the sales-led one. I think you need to be super strategic in terms of the problem you're solving.

Jeremy Au: (13:10)

It sounds straightforward the way you say it, but it just gets so hard in execution, right? So I think you've coached quite a few B2B sales founders as well in your role. Aside from an advisor, a consultant, and a friend. So how do you go about helping them upgrade that way? Is it like, send them a book? Send them a podcast? What do you do?

Bhavik Vashi: (13:34)

Send them this podcast, and I'll send the podcast. It's very bespoke. I mean, that's part of the, like exactly what we said. I would take the same sales approach that they would want to take with their customer, and I would take with them to understand, kind of, usually, I look at the origin story about why did you think that this was a problem worth solving? What was the genesis of it? So let's go back to that and then obviously, a lot of times the thesis has evolved from then, like once they get into building it, testing it with customers and getting feedback and all of that. So I try to understand what they're doing so that I can give them a more kind of specific strategy. So for example, some SaaS businesses are tailormade for partnerships and channel distribution and it's amazing, like everyone loves to talk about it. It's like, oh, amazing. Partnerships, channel, leverage, scale, buzzword, buzzword, buzzword, right? And it's like other people will be selling for you, other people will implement it for you.

You just sit there like a factory and turn out the product. Amazing, right? And it can be depending on the product, the buyer, the markets, and the ease with which a channel partner could buy or sell, and implement your technology, but it's not for everyone, again, Anaplan is a great example. We were not ready for channels and partners although we wish we were because there was just, again, too complex, too nuanced and frankly distracting as well. Like when you have a product that can do a million different things from a million different people and then you let the channels decide how the product is going to get distributed, sold and implemented. It actually can create an unexpected support burden on you as a company and as a founder, because now the thing you built for financial planning is being used for some, really bespoke HR or supply chain thing that you didn't expect. Good problem to have, you argue, but still, it can quickly snowball out of control and then you have a couple of bad customer implementations, a couple of bruises, couple of bad CSATs, that can ruin the business as well quickly because you're disruptive and so it's like, oh yeah, the Anaplan thing, they talk a good game, but they don't deliver and then you're done. You're kind of dead in the water.

So yeah, it's a very bespoke approach that I try to take with every founder channel is just one example. You could say the same for like how you structure marketing very different ways to do that. The sales versus product-led like sales motion that you talk about. Even subtle things, like do you have SDRs, BDRs, or both. One is that cost is well related to the gross margin profile and the average sales price. What is the cost basis, which then influences the talent that you have? Are you hiring? Freshers and teaching how to hit the emails and phones? Or do you have salespeople that are in their forties and fifties sometimes? Because they're selling to Global 2000 CXOs. There are so many. That's what I love about SaaS. It's like, it's so simple, like when you zoom out, but the more you zoom in, all the complexity starts to reveal itself. At least what separates the winners from maybe the more average kind of companies.

Jeremy Au: (16:34)

As you think about these average versus stronger companies, have you seen any innovation or changes or like, I was going to say revolutions, but maybe evolutions over the past five years that you think have impacted the way SaaS is produced or sold or distributed.

Bhavik Vashi: (16:57)

Yeah. I think probably the biggest evolution of SaaS is just I would say kind of decoupling a lot of the layers of the actual technology stack that's used to deliver the application to the customer or the user, right? Like we, there was, previously it was like, okay, you have your data centres and then you kind of write your code and you build your application and then you may, within the application you have different, components. You have security and authentication, you have a calculation engine, and potentially you have a user interface. These are all their decision choices of whether these are just kind of separate or they're modular, and previously, you always had to deal with the trade-off.

If you make the modula, yes, much more flexible in terms of development and innovation, but slower generally, because like data, the more times you're moving data back and forth between different things, the slower the end user, and ultimately the end user having punching in a number and getting a subsecond response versus like a one-second response makes a huge difference in how you perceive your experience and so on. Even down to the product adoption and ultimate end users logging in and using it and all of those things pretty much have been disrupted in their own right. You've had cloud computing. Everyone knows to come in and take off that whole data center thing. So it may usually make sense to do it with them until a certain point when it doesn't, and then you have to either renegotiate or decide what to do. Then you have microservices from an API perspective, which has completely changed.

Product development, you could argue, but you could have everything super modular and talk to different components and change those linkages pretty easily, which again, then gives you a lot more possibilities in terms of having your interface layer have nothing to do with your calculation nitrogen, and then you can start reusing components. So I think the whole, like, it's more technical. I feel the revolution more than anything has changed the way you think about developing SaaS, and obviously, that has an impact on how you go to market with the product as well. But I believe the revolution has been mostly on the technical side over the last five years at least.

Jeremy Au: (19:10)

Right, and I think there's a lot of buzz around AI, right? So sure you must be thinking about it all the time in terms of like, it changes how technical code is written. It changes sales, chat, and customer service sales could potentially be done. Then obviously people are talking about, oh, maybe we have micro SaaS businesses that could be done by one person. Other people are saying that AI is going to benefit the large companies that have the data instead. So how, let's just start and take a step back into say like, how do you think it impacts B2B SaaS from your perspective?

Bhavik Vashi: (19:43)

Yeah. That's a big question. It's got a lot of buzz. Rightfully so. I would say I was a little bit slightly more bearish on the Web3 buzz. I may be wrong about that, but just have this personal right and am a little bit more bullish on the AI bus. Maybe it's just cause I can more quickly understand its applications and use cases. And I think we're seeing that, right? As it gets, AI is getting integrated into every product and service we know quicker than Web3 ever did. And I think for me, I break it into a couple of broad areas. One is commoditized AI, which is stuff that everybody can use to enhance their offering. So like I think a good example is probably the chatbot. Simple. That's how it has already been there, like to some degree, right before this whole revolution happened. People were using bots and stuff. And then, productivity, AI, like okay, guessing what you're about to type or guessing how to finish the formula you're writing, things like that. I think that's much more commoditized. So I think every product and service we interact with will have to integrate that in and if it doesn't, we won't use it anymore and it's pretty simple. It's not a differentiator in my opinion. Like yeah, being quicker to adopt it. You may get user migration that then stays with you and doesn't read when the competitive product does the same thing. So it's a little bit of an opportunity, but like short term, I think the long term opportunity with AI is AI.

There are two components at a very high level in my understanding of it. It's like the data set against which your AI learns, right? That's like one big variable in the equation and then it's like kind of, the intelligence, like the learning model that you can build that can take any data set. So those are the two things, right? Like chat is right now, like the learning model that everyone is like leveraging, right? Cause it, it seems to be the best we've seen and the data set they've given, it is kind of like the internet, right? Up until a certain point. So I think in AI, two companies, they're going to be companies that work on the learning models. I think those are few, right? Because that's a big barrier to entry. Like you have to have been working on this for a long time you're not just going to catch up overnight on the learning model itself. Everyone we see right now is like leveraging that learning model to apply it as a productivity hack.

The second, which I think is quicker for non-AI companies to potentially figure out and leverage as a wedge Carta included, is the data set. So I think if you have a proprietary data set today meaning, it's a data set no one else has. Only you have it. That is a wedge because only you can then apply AI to that and make sense of it and make it available in whatever way you choose to, to a user base and you will continue to have that wedge because you own that data. I think that's a big one and so, I think, as I said, Carta, I think has a unique opportunity there. 35,000 plus private companies using us for Cap Table, 5,000 plus funds using us for fund administration, and so on. That gives us a lot to work with. There are other, a lot of other companies, I think I've seen some companies doing that with their own data sets. I think that the kind of medium-term opportunities like short-term productivity hacks, media-term use, and proprietary data sets come up with interesting value and then the long term will be an evolution of the learning models themselves. So that's kind of like how I think about AI right now.

Jeremy Au: (23:22)

So, what's interesting is that there's also a debate about whether you think it's startups or large companies that would benefit from this. And I think in one school I've taught like you kind of mentioned is like, the advantage goes to people who are proprietary data, right? And so that to me implies maybe companies with historical data, which implies larger companies.. And I think other people have made a claim that is really about innovating and using the capability as a business model. And so that advantage is smaller companies. So how do you think that shakes out or how do you think that plays out over the media of long?

Bhavik Vashi: (23:56)

It's a good question. I don't know. I mean it's speculative. I have a strong feeling that it's going to be large companies, because as I said, the proprietary data sets, I think just allow them to leverage the existing innovation uniquely.. So I do think in the medium term it's large companies who adapt and decide to, leverage that and a lot of large companies have to kind of go digging through their own like legal frameworks to understand whether they got the permission to use that data. Because there was a divergence in the 2010 to 2020 era of companies whose MSA kind of master's description agreement said that they would use your data or they wouldn't. And I think that that's going to end up being a bigger decision than people realized. I think the startups. Being able to be like an AI native, right? As we talk about digital natives, you could be an AI native.

I think certainly there's an opportunity there because we all know how hard it is for large organizations to move and no matter how hard they try, they will not leverage AI to the fullest. That's just a matter of fact and so, there's certainly an opportunity, but I don't think it's the business itself, let me put it that way. I think startups can leverage AI to get to market faster, but they still need that innovative product or, problem that they solve better than anyone else to thrive and AI, I think just accelerates the potential speed to market or speed to scale in certain situations. I don't think that a startup who's created, like you've seen them Chat GPT plugin, or this, that, or the other, as I think, I don't know that that's a, like a lasting business model, in my opinion. Yeah. I just think it's just more powerful when a big company leverages the same functionality because of the data set.

Jeremy Au: (25:50)

So maybe in our way of saying it is the advantages accrue to those who have a proprietary large data set, and the question is, It's more likely a large company can figure it out rather than a small company to have access to that but doesn't mean a small company can't figure out how to build it themselves, right.

Bhavik Vashi: (26:07)

Now I think a lot of the companies that have huge opportunities are data companies. There are, like, ZoomInfo is, known pretty well. I think data companies have a unique opportunity right now to just introduce new products to the marketcand and new services to market. So, that'll be like a very specific, interesting space that almost every B2B company consumes from. Like most B2B companies will be subscribing to data sets because you're looking for accounts and contacts and everything to drive your sales-led motion. So I think that's like very, I've been as a potential buyer, I've been waiting to see something cool there.

Jeremy Au: (26:42)

Yeah, and I think that makes an interesting case, beecause then I don't know. A lot of technology feels like it generates new companies, right, new startups and everything. And then, I don't know, in my head, this wave of AI startups are not really going to be startups. It's going to be a technology that gets distributed across the existing incumbents in that sense, rather than a new wave of companies.

Bhavik Vashi: (27:11)

Could be a lot of M&A though, right? As I said, large companies are slow to move. If a startup gets going with something that makes a lot of sense and shows some early traction. That could be just the easier path for a big player to say, okay, we'll just go ahead and pick that one up and integrate it into this product or the whole company or whatnot and that's not a bad outcome for the startup or the investors. Right. So like, I do think it's a tailwind, right, for startups. It may not be like iconic, standalone IPO and beyond brands that sustain forever, which, which, yeah, that's a that's an interesting one where it feels like we're going through like, this is not a word, but like a re-conglamorization of industry, like this happened way back in the day and you see it in certain Asian markets, like Philippines is a great example where it's like run by 10 families with these huge conglomerates, India being another one. But you're seeing that at like a global scale almost now with some of our big tech players.

Jeremy Au: (28:09)

Yeah, no, I think it's really interesting when you put it that way as well. And on that note, we see Southeast Asia, right? There's obviously B2B SaaS and obviously, everybody knows it's been a challenge in terms of it. I think Peng from Monk's Hill said like the GDP per capita, that's an inflexion point. It says that below a certain inflexion point, labor-wise, it just makes more sense to use humans and once your cost of labour goes beyond a certain point, then you start saying like, SaaS makes more sense. You can slice and dice, right? You can be like, okay, some metropolitan areas have higher salaries and some professions within those areas will have the highest salaries as well. That automation drive can kick in for different stages at professions, but still, I think there's an overall sense that I think a lot of the companies and startups being funded in Southeast Asia are like high volume, low margin, complicated business models versus like you said, B2B SaaS is so beautiful, so simple and it's, it's hard to see it Southeast Asia. Right. So, I mean, I'm sure you have lots of thoughts about that. What do you think about it?

Bhavik Vashi: (29:10)

Yeah, I mean, I hope I'm quoting it correctly. I think it was Jan Capital, their report, which showed the emergence, albeit somewhat slow, but the emergence of B2B as a bigger share of the overall kind of venture back startup and just gen generally where money is flowing and I think we're going to continue to see that trend as the next wave for Southeast Asia. I think because of what we talked about, you're right. In terms of what you're going after, I think it's still easier to go after large enterprise companies, to your point. Like them just, the value proposition resonates so much more loudly and easily for a large, complex company than it does for a small startup, but again, the SaaS gross margin profile just allows you to be innovative and play in multiple different segments at different price points and gives just you a lot of commercial creativity in how you go about constructing your business and so I don't want to underestimate the innovators ever that they won't find a way to build SaaS for micro SMEs, which we all know is a huge opportunity in Aian and Asia specifically. Yes. It's all about the cost, right?

But can you get that cost down to a point where it functions very much like a high volume, low price point product? I think so. It's possible for sure. Kind of like what we saw with Telcos, right? Where they just decided that the internet and 5G and all this were going to be free in India, especially with geo and stuff. So like if you do the Math of it, it could work. It's just about finding the right product and problem and user persona. I've seen some interesting things. I'm sure you guys have seen some interesting things. For example, Fintech had a huge moment in Southeast Asia, and now I can see it evolving into SaaS, like Fintech SaaS, right? And you're still catering to a lot of those people who have started using your payment gateways and payment rails, and now you're building like very simple SaaS functionality to help them track their budget and expenses and other components of their business and just like elevating the maturity of business at the most, kind of the most federated level of the economy. Think like farmers and like down to the bottom of the overall supply pyramid for any product that we might end up consuming. So yeah, I'm cautiously optimistic that it's possible.

Jeremy Au: (31:42)

That's fair that I think that's a mismatch. I think, as you said, I think it's possible to build B2B SaaS, but you said to design it for a price point that is lower than what you read online on Substack, right? Or SaaStr. Yeah, then if you do that way, you got to build like it's very product led or you got to be very cost-efficient. I think you got to be sure about your unit economics. I think there are so many SaaS companies that I have met and I'm redoing their lifetime value and the customer acquisition cost because, I think they tend to underestimate the lifetime. I think of the companies that they have, and they tend to overestimate the margins because they don't load in customer support and sales time and all these other things. So, I don't know. It's just I think that's the big problem. I think there's a window.

Bhavik Vashi: (32:35)

I think there's also an opportunity, so if you think about an Asian company, right? Any SaaS company generally, again, broad strokes, 50 to 70% of their costs will be people's costs. It's the beauty of the business model. Everything else is like pretty controllable, and so if you're building in Asia, yes, you're serving perhaps consumers, and businesses at a lower price point, but you're also paying at a lower price point. So again, like you're kind of affecting both the top and the bottom together. Right. Like I think running a company out of the west trying to serve the east is probably a failing proposition, but if you're running in the east, serving the east, then you've brought both down. And then I do think that we’ve yet to see the full commoditization of cloud computing.

Those big boys are still making a lot of money. That's not going to last forever. That's just, every economy works that way, that eventually more people come in, and they lower the price for everyone. That part becomes commoditized. Other things become value added and so that should help. That should help every software company because a lot of times people, right now, startups that I talk to, one of the biggest issues is like, yeah, they wanted to be quick and they moved with AWS, GCP, Azure. I'm not being specific, I'm just saying any of them and then all of a sudden they're bill sticker shock, especially if they're storing law computing a lot and so I think that plus the people costs being at the right point will enable something that's much more high volume as a business.

Jeremy Au: (34:03)

On that note, could you share a time that you have been brave?

Bhavik Vashi: (34:08)

Sure. So my bravery pales in comparison to anyone who's exhibited real bravery in terms of frontline, medical staff, soldiers or a long list of other people. But I think for me my personal, probably bravest moment was just leaving behind kind of everything that I had ever known or built in the US and just kind of relocating to Asia by myself. I ended a very long relationship on the personal side to do it. I left a pretty high-performing team with a healthy kind of overall compensation situation, everything kind of, for the challenge of doing something different. Experiencing something different, learning more, growing more as a person in my personal life and just relocating to a country that I had never even visited before, which was Singapore. Luckily, it's amazing and it's very easy.

So in retrospect, it was less brave than it was at the moment. In the moment, in the absence of information, it was a brave decision. Now that I've done it, I could say it wasn't that brave. It was quite easy. But I remember thinking quite long and hard about that decision and wondering whether it was the right thing to do. But I did it and was super happy about it. It's one of the best decisions I ever made.

Jeremy Au: (35:26)

What was the hardest part about that decision? Was it like, letting go of family and friends or was it going to be the team? What was the hardest part of that decision from your recollection?

Bhavik Vashi: (35:34)

To be honest with you, personally it was my community of loved ones, friends and family. So, I'm born and raised in the US. I've always lived there. My brothers were there, my family, my parents were there, my friends, all my friends were there. Berkeley, right? Like that whole community, just everything. Everything I knew was there. So that was on the personal side. I think I was able to mitigate that, knowing that it may not be permanent. Like at least in my head it was like, okay, you can always come back. So that kind of mitigating risk in your own head? I think the one that was less reversible in my mind was professional because, you're in San Francisco, you're in the headquarters of a company that has just done its series E, I think at the time, D or B, we're on, we're on the path. I'm pretty relevant internally, like, executives know me.

I'm working on the biggest accounts and, really in the thick of things and things are going well, and so I think that was the thing of like, okay, will I become out of sight, out of mind? I'm going to the Asia Pacific, it's less than 5% of our business. Who cares? I'm going to come here and do a great job. Will it be a bad move professionally when it's all said and done? That was, I think, the harder part because I felt like it was less reversible if I came here and did two years. It's not like you can just waltz back. Your friends and family, they'll take you back. If they're good friends and family, but the, company may have moved and may not be available. There are so many risk factors. They always say it's all about timing. So that was, I think for me, that was probably the thing I thought about more.

Jeremy Au: (37:07)

On that note, thank you so much for sharing. I'd like to summarize the three big takeaways to go from this. First, of course, thank you so much for sharing about B2B SaaS. I think there are so many perspectives on obviously what makes good SaaS, but also what your learnings were, what were the surprises and why. The kind of errors that people have when you think about it, or even when they start building it. So it was really interesting to hear about how you go about coaching founders and working with the teams to make things happen and I think that's very valuable to kind of go through that process.

The second is about AI. I think you did great job hunting, I don't know, what's the word? Spitballing and brainstorming me about how it is like you said, we're both probably horribly wrong we gave it a shot, and we took a stand. We did, we wouldn't like wishy-washy. We were like, ah, it works for everybody, but I thought it was just a fun kind of like speculation, but also I think some hypotheses around what we thought could happen in terms of it benefiting those proprietary data sets and how it could be a good opportunity and tailwind for startups to kind of like have a growth story play out using AI.

Lastly, this was brief, of course. I appreciated you sharing a little bit about your moments of bravery in terms of moving to Southeast Asia in Singapore. I thought that was a nice moment to talk about how some parts are reversible. In other words, your family can accept you back again, but, professionally it was a big jump for you. So thank you so much for coming on the show.

Bhavik Vashi: (38:35)

Thanks for having me.