Vaarrun Bimbhat
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jeff: [00:00:00] in less than a year, we were able to drive more than like $26 million in gross profit just through this experimentation. A lot of that plan packaging and pricing was driven by this experimentation platform, So had we not had this scaffolding of the platform, we would not have been able to launch these preamp plans with these prices. 

Welcome to Launch Pod, the show from Log Rocket, where we sit down with top product and digital leaders. Today we're talking with Varun Bimbo, head of product@jiffy.com, an online seller of customizable clothing.

jeff: In this episode, Varun talks about humanizing the sale of high commit items like furniture at Wayfair, and how that led to $50 million in additional revenue. How he built a repeatable process at Shopify to expand into new countries, adding almost a hundred thousand new merchants and $50 million in additional revenue in India in the first year alone.

And why developing a billing experimentation platform at Shopify drove over $26 million in gross profit annually. So here's our conversation with Varun Bibo.

Hey, Varun. Good to have you on, man. It's, we've talked a whole bunch of times but nice to have you actually join the show. How you doing?

vaarrun: [00:01:00] I am doing great, Jeff. Thank you so much for having me. I'm really excited to talk to you today.

jeff: This gonna be, this will be a lot of fun. I just came, I just flew in literally last night from shop Talk out in Vegas. I am in the e-commerce mindset. Which is great because, your history is like just dead on here, right? Wayfair, Shopify. You've done just so much in the kind of like online selling space, and then even now, you're, head of product@jiffy.com. I'm locked in man. So let's just kick it off, right? I think Wayfair is one of those companies that know nationally, in Boston is just like. A pillar of the tech community. And we can start here because, I think you spent some time there and ran into a whole bunch of interesting problems. But the first one kind of comes around what I've always viewed as a really tough problem and one that I've still wondered how it got solved.

So I'm, extra eager to dive in here. Selling things like furniture online or the traditional, like bigger things that you want to go and see in person. You rolled into Wayfair and that was one of the things you took on. But you had a big win. You drove like 50 million bucks around making this better.

[00:02:00] So can you maybe walk us through like, why is, I guess first of all, like, why is this so difficult of a channel? And then let's talk through what you did and how were successful here. 

vaarrun: So let me start off by saying that Wayfair was an amazing company to work at. I learned so much. It was such a exciting and challenging space. And Wayfair is in a market where it really competes with the behemoths of the world, right? So like you can think of Walmart and Home Depot and Amazon all of these really major players who've done a really good job at scaling their operations and scaling e-commerce generally.

So when I was at Wayfair, we were in this really exciting phase where we were trying to learn more about how customers shop online for furniture. we realized just organically by virtue of the nature of certain categories, customers actually much rather prefer to touch and feel something before they buy it.

What adds to the complexity sometimes is there are a lot of categories that are far more technical, right? So if you walked into a Home Depot, you'll see people shopping for these categories a lot, where customers really want to figure out the [00:03:00] dimensions. They have questions about the aesthetic. They have questions about how it goes with everything else that they have in their, say, bathroom, how it goes in there, like flooring.

And all of those questions just add complexity to solving that problem at scale. So when I joined for Wayfair, I realized that we were trying to grow the footprint for certain categories where it was just really hard for customers to make that purchase decision online. And we tried to address that by essentially improving our PDB, giving them a wealth of information on our product detail pages.

And we realized no one loves to read information. Everyone, just someone

jeff: Yeah.

vaarrun: right in this incredibly like. Online world, I think people crave for that human connection. Someone who could just guide them on what the right purchase for them could be. And if you really focus on building that connection, it builds more lifetime value.

It builds more long lasting relationships between you and the customer. And so that's essentially the unlock for me. When I joined Wayfair after [00:04:00] having made a ton of iterations to our PDB, we realized that because of the nature of these questions. We needed to connect these customers to some kind of help where they could help, just drive their purchase making decision.

And we did a lot of research to figure out what kinds of questions they were. We had a great group of catalog experts at Wayfair, and essentially the bridge that we created was. Connecting these catalog experts to these customers on the site where they were already shopping. The pattern that we'd observed previously was that a lot of these customers would be shopping for these categories on site.

They would exhibit signs of confusion. They would often end up just exiting or bouncing, and a bulk of these would just be lost customers. So it's like lost value, lost chance to make that relationship connection between Wayfair and them for the few that called us. It just seemed like a very disconnected experience because we were forcing them to pick up their phone and call us,

So we wanted to replicate that experience that we were able to deliver to them on the phone, on the site [00:05:00] itself so that it's just a seamless shopping experience for these customers.

jeff: Nice. So you kind of identified like what is the real world? Behavior here, what do people expect when they're buying this class of items? Because it's one thing to if I'm buying a clock online. It's not that big a deal, right? I'll go anywhere. It's easy, it's pretty low, low commitment, I can return it.

But buying a couch you gotta know like, is it really that long? , is it, very overfilled. The picture's a one thing, you always have a million questions and it's a much higher commitment. 

vaarrun: one of our learnings in the process was that as customers were actually shopping for these categories, they were often working on projects, so they were renovating their bathroom or renovating their bedroom, and so everything you're saying makes perfect sense because the customers really cared about.

How would this go with every other choice that they're making in that project. And so we had to get really specific on how to guide them, how to help them sometimes build the entire project on Wayfair, if that was an option. So that was a great unlock for us.

jeff: , you identified this [00:06:00] need of people wanted to talk, they wanted to, I know when we've bought furniture, it's not a thing you do all the time either. This is not something people are intrinsically trained in. 

You maybe buy a couch maybe every few years? Probably less than that. I think I've bought a couch maybe twice in 20 years. So it's not something people are necessarily super skilled at either. They wanna be guided a little bit and this all makes sense. So 

how do you build that human kind of experience into it? You have the hypothesis, right? People want human interaction, they wanna be guided a little bit more. What's the next step to getting it? Into some kind of actionable, testable state or like figuring out the right way to implement.

'cause I could see like you said, phone was the wrong way to do it. No one wants to pick up the phone, divest himself from this experience, go over here into this experience. , how do you make it seamless like it is in a store? A clerk just comes up, talks to you. I'm assuming you didn't have.

A chat bot. Just ask 55 times, Hey, do you need help? Hey, do you need help? Hey, do you need help? Because the benefit there is a chat. Bot's not fighting for commission though.

vaarrun: You're absolutely right. I think the thing that really helped [00:07:00] us was I. Tying the qualitative research that we were doing with our users, with the quantitative number of the kind of impact this could unlock for both the customers as well as for Wayfair.

Let's start off with the user piece first. We did a lot of research to figure out how customers are making these decisions online.

What is the nature of the help that they need? What are the different kinds of questions they ask? And that allowed us to almost build a repository on our end. So that we could collectively answer all these questions and have them make the right purchase decision.

As we built out that repository, obviously we were making a lot of attritions to the website itself. But we wanted to think about how to make that more usable. I. Even as customers called us or connected with us over a different medium. So the next sort of decision we had to make was what are the different ways in which we can expose this information to the customer?

I really hope we had chat GPD then 'cause we would've been really able to just crawl through this database and expose a lot of answers and like results [00:08:00] to que for our customers.

jeff: , I'm always amazed at what people were able to build before the LLMs came into play. There was a lot of really good stuff that was built that, it was a little harder, it is always interesting to see how people kinda solve these problems Before you could just throw an L LM at it and train it a little bit.

vaarrun: Yeah, and I'll talk through some of the AI experiments we ran as well, but I agree with you, it was a lot harder back then, and today it seems like you can do it within a day, which is just amazing.

We did the research with the users. We created this repository of information. The next unlock for us was how do we expose this to our users?

And we experiment with a few different channels. We thought about channels like SMS, phone, email chat. To my point earlier, we essentially realized that chat is the most intuitive channel. It is the channel that is in context for the customer and the way we could position it was almost like a virtual sales assistant, right?

We didn't want to be that intrusive. [00:09:00] Assistant who's bothering you. Instead, we wanted to compliment the onset experience. And so just nailing that user experience was really important. And figuring out like where this button would be placed, how it would interact with the customers in what cases would it be proactive as opposed to reactive.

Nailing down all of those specifics. Took a lot of user research and design iteration. The third thing that we had to think about was the technical challenges, right? Because back in 2018, implementing a chat bot was really not that easy, and there were a lot of real time decisions we had to make around what customers to engage with.

How do we route these customers to the right category agents, how to deliver the best experience on both ends, both to the customer as well as to the agent. So we did a lot of work on identifying different vendors running a bunch of POCs with different solutions, eventually landing on one that worked extremely well for us.

And then creating an MVP around a time that just allowed us to gather a ton of learnings [00:10:00] and a rate on that solution. So I think the technical challenge, identifying the right sort of integration, the right vendor. Then exposing that on site to a really large audience that's shopping for 14 million skews on a daily basis was just, it was an incredible technical challenge.

jeff: That's one thing that like if you're a small, Hey, Wayfair done this, back in the beginning that'd be, one thing be a great innovation, not that many excuse to handle. But you guys took this on at a point where you were already a really massive company.

So like you said, it's not a small undertaking, just the number of skews to cover and the amount of knowledge. People had to have to be able to do the, the support end of it is incredible. So yeah, it was not a small feat.

vaarrun: Yeah. And then I think once we unlocked the sort of technical integration side of it the other piece we wanted to focus on was how do we train our category experts so as to give these nuggets of like information and knowledge to our customers that were shopping online. 'cause everyone wanted information in a very concise way, [00:11:00] but they wanted information that's addressing their queries.

'cause if we didn't do that, it would just be like, it wouldn't be as successful as we wanted it to be. So thinking through that user experience training our agents, leveraging AI in the process of real time guidance a lot of those things really allowed us to uplevel that experience. And so I think in terms of the strategic pillars, these were like the four areas that we really honed in on and we leveraged a lot of the user research around these different aspects of the experience along with the impact that we could try for these different categories.

And that really allowed us to make the case for it, get buy-in and actually develop this over period of a few months.

jeff: I love the idea because we had a guy named Mikel Lewis on recently. He's at Whole Foods now, but he was at Nordstrom for a while and retail me not, he had this idea of, he called it ethical cheating. And it's basically, there's just so many problems that have been solved already.

Probably your problem is not that novel. So look to other industries or other verticals or other experiences to see, what the solve was. And like [00:12:00] in this case there's already a pretty decent experience where at the store you can go, you can ask live questions, you have an expert there.

If you could just provide the positive ends of that and maybe take out, the kind of pushy, commission driven end of it, you'd be in a really great experience. And that's exactly what you did, which is great to kinda see this, parallels of maybe you didn't approach it from thinking about is ethical cheating.

But I think it's a good framework of looking to other areas where there is a good experience around this concept and how you port in those ideas. One question I have for you is. Like we've all, I think, experienced the online chat experiences where you ask a question and it takes five minutes to get an answer.

And that may as well be saying a million deep bajillion D hours to me at least, like I'm not sticking around for five minutes for an answer. If you get me to stick around for 45 seconds, like I really want the thing that I'm talking about now, that means how did you like ensure that kinda those you had SLAs that were gonna be met and that, this is not a furniture store with. 15 models on the floor. This is Wayfair how did you ensure that people were able to kinda get the answers people wanted quick enough [00:13:00] and still be accurate and like you said, concise and quick.

vaarrun: Yeah, so that's an incredible question and this is where AI came in really handy for us. I.

jeff: Yeah.

vaarrun: In addition to a lot of other technical innovations, we built into our tech stack,

As we were surfacing this chat experience for our customers. So I'll talk about two things that we did that really helped.

The first one was in real time, we wanted to gauge how many customers we have who are actively shopping on the website. And we were trying to figure out like where they are in their purchase journey.

So the further along they were where they essentially have an I item to it in their cart, and they just wanna make a decision, but they have say a pending question that's preventing them from making that purchase for those customers.

We wanted to make sure that we can give them help as soon as possible. So the immediacy of the help, to your point, was something we determined based on the intent of the customer and where they were in their purchasing journey. And we did a lot of real time analytics. We had some really sophisticated data science models that [00:14:00] allowed us to gauge that and deliver that compelling experience to these users, which just power to make a purchase.

For other users. We created some AI experiences that allowed us to just gauge where the user was in their journey and how we could provide the right help to them on site before we connected them to an agent. So we weren't able to actually offering them the catalog expertise we had, but we thought if there was a better way to serve the same question or need on the site, we could do that.

'cause to the point I made earlier. We didn't have chat GBD at the time. A lot of this was just crawling a really large database of information and making it accessible to these customers. And so we were essentially acting as like nger, nudgers and pointers to the right locations on the website that could help these customers make the right decision.

So I think the combination of those two things where we ran AI experiments for customers who were very early on in their journey, and then paired that with some real time analytics and data science. To offer more immediacy and help for the high intent customer. [00:15:00] I think that's what really allowed us to solve that problem, and it allowed us to just scale that experience to a lot more categories as well on Wayfair.

So we became really deliberate on what are the categories that need this kind of help, and what are categories that are better served by just the website alone.

jeff: Yeah, not everything needs the heavy handed, super intensive. Support. Some things are, lower commit and if someone doesn't like it, it's easy enough to return it, or the monetary commit is not that high, but you're buying, a couch that's, a couple grand.

I wanna know what I'm getting first. I wanna ask a few questions. I want someone to pay a little attention to me. I we met when you came to one of our dinners in Boston. And, a whole bunch of great product leaders who joined us there.

Back to your point about, the kind of mimicking the in-person experience in person, and how do we kinda drive that kind of thing. Really helped us meet there. But you brought one thing there that I wanna touch on that I had no idea about before. This is there's a pretty large end of Wayfair that is B2B as well.

And as much time as you spent on cool prompts like this that were very, like B2C focused, you also spent a good bit of your time there on this B2B end, which I am so curious to hear more about. 'cause I have [00:16:00] gotten like just the slightest of slight teasers and it sounds really cool and. I'm interested to hear more.

So can we dive into this a little bit and just explain what is the B2B end of Wayfair and how'd you fit in there?

vaarrun: Yeah, so let me start out by saying I did not anticipate it being as much fun as it was.

I have a theory that almost anything can become fun if you get deep enough into it and like you can find those little fulfilling challenges, 

I completely agree with you. I think when I joined B2B, I just looked back at that experience very fondly. I really cherish that experience because I learned a lot, and honestly, we were just scratching the surface. There's so much opportunity in that area.

jeff: Yeah.

vaarrun: So just to give you context, I think Wayfair had a percentage of the market share, and that was a loan, a $2 billion entity.

So we are a $200 billion market and it's really exciting to see how customers in the enterprise space actually make furniture decisions, right? So you could think of someone like a hiat that wants to order sofas or beds for their entire hotel. And if you do a really good job.

[00:17:00] On nailing not just the furniture, but also the specifics and the the externalities around that. It can help you build that relationship with a chain like that. And essentially, you could end up, ordering furniture for multiple locations around the world and around the country. So the thing that I learned in my B2B experience was just how different the buying journey was for B2C and B2B customers.

B2B customers were driven a lot by the price, and they were driven a lot by availability of those products within a specific timeframe. They were also really motivated by services like assembly, consolidated delivery, things of that nature. So a lot of the work I did in B2B was package and price optimization.

And again, I really enjoyed using machine learning for this. It was so interesting to figure out all of the different criteria that drove the purchase decision and tie them into how we price those [00:18:00] products and how we recommend those products for different B two P customers. And we did so many creations on these machine learning models that we got really good.

With the experience that we deliver to the customer as well as the conversion that we drove in turn for that line of business. So for me, that was a very enriching experience. We drove a ton of value. I think in the two years that I was there, we drove more than a hundred million dollars in revenue.

So it was definitely a very ambitious and exciting part of my career. And I learned a lot about technologies like machine learning. I also learned a lot about just a difference in how people purchase online, depending on whether they're B2C and B2B. The host of tools that you can leverage both from a sales tools perspective as well as just from the perspective of expediting that decision making process.

'cause it's usually longer for B2B than it is for B2C. So I learned a lot about how we can run these experiments to expedite that and just drive more purchases online and build a longer lifetime value for these customers on Wayfair.

jeff: [00:19:00] Now, was this kinda stuff, was it kinda off the shelf furniture you were selling or was there customization that would be involved here or I.

vaarrun: Yeah, so most of this was the same SKUs that already existed on Wayfair. The thing that we had to play around with was how do you package a hundred SKUs into something that's more compelling for the B2B customer.

jeff: Ah,

vaarrun: do you price it? How do you give them all of these services? Also how do you give them credit sometimes?

So like the financial aspect of it so that the smaller B2B customers can still make a purchase on Wayfair and have a longer lead time to pay for it.

jeff: Yeah. Whole, we have a whole episode just about B2B a Wayfair, I feel like is, there's a whole area that I didn't know really was a thing at all, and I think probably is true for law people. But it seems like there's a whole depth here. But I said super interesting. But I do wanna make sure we cover, time. Like I said I was just over at Shop Talk literally yesterday at this time. I was on the floor at Shop Talk talking to a bunch of e-commerce people. But really like almost [00:20:00] adjacent to our booth was the Shopify booth.

And so I just kept thinking about how we were talking today because I could just see this booth right there. It was slammed by the way. They were busy the whole time. But you spent. A good amount of time over the past few years at Shopify as well. Doing all sorts of stuff, doing, payments and working on the billing and some experiment stuff.

So let's dive in here 'cause I think there's some cool stories. Can you maybe just give a quick overview, , you were at Wayfair, Shopify came a call, hard to turn down Shopify, like there, that's a compelling story going on at that company. And then you land there. But maybe walk us through, like what was the role you walked into?

vaarrun: So while I was at Wayfair, I think until that point I'd worked a lot in e-commerce and I'd done a fair bit in FinTech. And so what was really interesting about the Shopify opportunity was it married the tools for me, I got this amazing opportunity to work in a division of Shopify, which is then called Money.

And as the word recommends, it was essentially the FinTech arm of Shopify. And the interesting thing about this experience was it also tapped [00:21:00] into a lot of the B2B experience that I'd built. So we were thinking about problems like how do we make it easy for business owners to manage their costs as they're running their business in Shopify.

And in that process, as they scale their business, how can we aid them so that they're never like financially strapped, right? They have credit available to them. They have good analytics so that they can make right financial decisions. And most importantly, how can we like, have the right technical partners that we can integrate with.

To scale our offering across the world. So just the nature and the ambition of that challenge was really exciting for me. I thought I had the right experience, the right sort of building blocks to drive a lot of impact. And boy, we delivered a ton of impact for the two and a half years that I was there.

It was a game changing experience for me. I learned a lot. It was also very empowering place to work for a product manager. So I just totally enjoyed that experience and yeah, it's definitely been a game changer in e-commerce as well.

jeff: Yeah, 'cause we're talking [00:22:00] about the last two and a half years here have been a. Incredibly important time for Shopify because it started off as a platform for SMBs to spin up a, D two c e-commerce portal real quick and has just evolved so much. But now there's all sorts of enterprise brands using Shopify.

Some were grown from those, smaller upstarts and now have turned into just large success stories. But I talked to, companies at Shop Talk that are big, big name brands that anyone in America is gonna know who are moving to Shopify and Shopify checkout and all these things.

But I have to imagine like some of these tools you were building, played a park here. So what were some of the problems you're trying to solve and like how do you support kinda these people as they go from, maybe a mom and a pop to. Thousands of employees and doing, tens of millions if not more in revenue.

vaarrun: I think the reason I was hired to solve that exact problem, because I believe that we've been going through this interesting journey over the last two and a half years where we've had a lot of upstarts like Allbirds, which have grown into really like large organization on the

jeff: now. 

vaarrun: And in [00:23:00] that process, I think we've had a front row seat to see how this. These companies scale and we've also learned the challenges, the experience, and how those challenges vary as they grow from an SMB to more of an enterprise. So I think the thing that I was essentially hired to do was for starters, scale our billing and payments on the merchant side so that regardless of whatever country you operate in, you have the right set of payment methods.

You have the right, admin functionality so that you can understand how much you're paying Shopify for all of the different services we provide to you. So it was really a trust and confidence billing exercise as well as e growth exercise. 'cause I enabled Shopify to expand to India, to a few countries in Southeast Asia and Europe.

And every time we expanded to a new market, I learned so much about. How customers shop in that region and how their payment needs can be like real game changers in terms of how it drives the lead to customer conversion on the website. So I think that was a great learning journey. In that process.

I also partnered a [00:24:00] lot with different payment processes around the world, like Stripe and PayPal and raise a bay in Southeast Asia. And that also allowed me to learn more about the payment ecosystem in each of these countries. So that was amazing. The next thing that we focused on was essentially the customer experience.

So as companies evolve. They wanna operate in different markets around the world. They have stores which are both retail as well as online. They also wanna manage different inventory in different parts of the world. There are a ton of complexities that develop in their operations, and we wanted to give them a way to visualize that on Shopify.

So one of the game changing experiences that we launched, which was actually showcased as part of Shopify editions in 23, was this organization's experience where you can essentially map how you operate as an entity on Shopify, and you can visualize the entire management of your stores from a billing and payment standpoint, from a user standpoint, from the entire sort of emos e-commerce operation standpoint.

On the Shopify admin itself, [00:25:00] right? So again, it goes back to that point I made at Wayfair where we mimic how the user operates in the real world on the platform itself. And the closer you're able to replicate that, the easier and more intuitive it is. For these business owners to manage their business on Shopify.

So you're taking a lot of the pain away from them and the more the pain that you take away from them, the more it unlocks these differentiating capabilities that you can build for them. So after building out , that customer experience, one sort of core differentiation we built into our platform was we realized there is a ton of value in how we price our plans, in how we offer different capabilities from these plans.

Both for our SMBs as well as for our enterprise. So the third thing that I actually did was creating this platform, which is called the billing platform. And essentially it was a combination of a stripe and an AB testing platform like Optimizely, except that it was a differentiated version of those two for Shopify.

So I built [00:26:00] that out and enabled the company to run a lot of experiments on pricing, on payments, on billing. Just expose a richer feature set through a wider variety of plans to our customers. So I think those three things in like in sequence really allowed us to unlock a ton of value for the company and a ton of value across different markets around the world.

jeff: So it was definitely a great learning experience for me. 

So digging into, some of the billing stuff, for instance, like going into India is a giant market, but it's not as easy as just saying, great, you can have a Shopify store.

jeff: In India now , there is a matter of how do you collect fees from Indian merchants? How do you, not just from a standpoint of like financially, but how do you build trust? How do you make it so that they feel like they're gonna work with you? How do you give them the things that they need?

But there are all sorts of projects just in that one thing of expanding into that one country. And you guys expanded into a ton of countries at this time. Accepting , Indian currency. Because what there was the central Bank of India made a rule [00:27:00] that all recurring bills had to be paid with a payment method from India.

vaarrun: Like right? There is a complexity that, a lot of companies aren't gonna be able to handle. So how did you attack those problems? What did that look like? Going country, by country and dealing with each one's regulatory environment and specifics. 

So we spent roughly about eight to 12 months. In the process of scaling in India, and the hypothesis was twofold. The hypothesis was primarily that there are a ton of budding entrepreneurs in the country. We were seeing very high lead to customer conversion rates.

vaarrun: And it's a matter of just giving them the right platform and unlocking it at the right price point for these customers to scale their businesses in India. So that was the two-prong hypothesis that really pushed us to expand Shopify in India. Now as we did that, we learned that the pyramid ecosystem in India was actually quite sophisticated, but it was also quite fragmented, right?

So there were multiple players in the loop and overarching goal of [00:28:00] the government there was to protect people from scamster. So that's why there was a lot of regulation compliance that was built in over the last two to five years. And a lot of the changes we made were driven by. What are the payment methods that customers use most frequently?

So there's a payment method called UPI, which is used ubiquitously by almost everyone in India. And so if you don't have that payment method as an offering, you're essentially not gonna capture a lot of your customer base. So that was an unlock for us. But then I think the CBI, the Central Bank of India, they came calling and they made a regulation where.

They wanted to ensure that anyone who's paying for recurring transactions in India, and this is both for e-commerce as well as for something like a Netflix or a Facebook they would all have to go through payment processes that were in India. They would have to pay using payment methods that only accepted local currency.

And there were also a ton of requirements around tokenization and such. So that was really interesting [00:29:00] because we had to partner with. One of the local payment processors that is a behemoth in Southeast Asia, it's called Raise Bay. And we worked with them to build out these payment integrations, building out the right customer experience, ensuring it works with more than 50 banks.

That was just. Such a complex and such an interesting part of the process. And then just ensuring that these Indian merchants can pay for these bills on a recurring basis. They can understand the costs that are incurring, they're incurring on a monthly basis, and also just unlock cheaper plans for them so that they can operate their business in India.

So it was really a large sort of complex project, and it was an interesting journey 'cause. Every time we did something, it unlocked something new and the Central Bank of India came up with some new regulation. So there was a lot of excitement as well as a lot of like complexity in scaling that operation.

jeff: But it seems like a positive thing to have gone through and take the time to really build a system around going into a country and figuring out all [00:30:00] the things and what does it look like to fully enable, a country of merchants. A because just, I. On the first point, like you guys added something like 85,000 merchants to the list by doing this, which is, like you said, there's just a ton of upcoming merchants there.

So it's a fantastic thing to be able just acquire that made customers. But also then, you went from spending, what you said almost a year on India, but then after that it was like several countries per year you were able to expand into. 'cause you had built this muscle to do this.

vaarrun: Yep. I agree with you. I think launching in India was so sophisticated and complex that it helped us create a playbook that we could leverage then to expand every year to a new country. And it was so exciting because a lot of the needs are similar, even between different regions, like in terms of like payment methods.

The payment methods themselves are different, but they're such huge unlocks for merchants in different parts of the world. So it's only a question of offering them and offering them in the right way that delivers the right sort of customer [00:31:00] experience. And if you do that, it just unlocks a world of opportunity for these customers.

And it also, unlocks the world of opportunity for us. 'cause it allows us to learn about other interesting things like fraud and such. So you just keep building better models and better playbook for expansion around the world.

jeff: then one more thing I wanna make sure we touch on here. 'cause it's. Similar idea right around the payments and the ecosystem there and focusing on the merchants themselves as the customers of Shopify is. Did you say that there wasn't a pricing experimentation platform before that?

So you, that was a zero to one change was you built, your team built this ability for Spotify Shopify to drive these pricing experiments.

vaarrun: Yeah, so

jeff: wild that late is when it came in.

vaarrun: Yeah, I was just gonna say the same thing. It was wild because I feel like the company had expanded so rapidly 

jeff: Yeah. 

vaarrun: that a lot of,

jeff: up so fast

vaarrun: yeah, I would say like maybe 50% of the company was actually hired after I was hired. So I saw that happening [00:32:00] live in front of me, and I just realized that we didn't have the time to build a lot of these foundational platforms early on.

And so what that manifested in was we had 20 different product teams. Running experiments, which are quite similar, and each of them were building out their own capabilities to do that. And as I realized that in my very first year at Shopify, I immediately recognized this need for us to expose a lot of this through a single platform that could both unlock speed as well as unlock some of the decision making around how to run these pricing experiments.

So for me, I think we looked at platforms like Stripe. We were very inspired by how great a product they've built and we analyzed the needs of the different product teams within the company to figure out what are those unlocks that can help us drive. I. Customer impact and drive revenue for the company, and how can we expose them through a very intuitive platform that functions [00:33:00] a lot like Stripe, except that it's something that you can leverage within the company for the differentiated needs that the company has.

So I think that was, again, a great learning experience for us. We drove a ton of value. We locked so many experiments that collectively just in less than a year, we were able to drive more than like $26 million in gross profit just through this experimentation.

jeff: , maybe it's all secret, but is there an example one you can talk about that went well?

vaarrun: I actually give you two examples.

jeff: Awesome. Even better. That's twice as good.

vaarrun: yeah, so the first example was that we unlocked a ton of new plans last year. And new pricing around different plans new capabilities for different kinds of merchants. And a lot of that plan packaging and pricing was driven by this experimentation platform, right?

So had we not had this platform or this scaffolding of the platform, we would not have been able to launch these preamp plans with these prices. So that was one big unlock because we tapped into. A new area of the market. And we also made it easier for the existing market to [00:34:00] have more capabilities in their plans.

The second example is we ran a lot of promos and there wasn't really a great way for Shopify. I. To provide discounts and promotions to our customers. So we did a lot of work on how can we just improve discounting capabilities and promotional capabilities so that we can run different kinds of offers for different customers.

And this was also a very important thing because every time we expanded to a new region, learning about how to price your plan in that new region required a lot of experimentation and iteration. And so I feel like because of this platform that we built out, we were able to unlock those learnings.

Offer a minute of functionalities around discounting to our customers and just arrive on the right package and the right offering for different regions and different customers in these regions.

jeff: Yeah , moving into, like you said, the pace you guys were expanding into new countries, being able to figure out and lock in and speed to getting that fit of the pricing model [00:35:00] to the region. The faster you can do that, the faster you can, onboard the region and be good to go.

And if that takes a long time at each of them and is high and is a ton of friction for you guys, you're not gonna be able to expand nearly as fast. So that's a great insight. I didn't even think about that. Awesome. Yeah, I think kinda looking across this, there's a lot of ground covered here between, how do you build, environments where you can buy maybe high friction items and how do you kinda mimic real life environments to make online settings more palatable?

Like when you're, selling maybe furniture online all the way to, how do you take a behemoth. Shopify and continue just enable growth at such a high level that they've been seeing that there's all these things that you run into where you realize we haven't done this yet, and this is seems fundamental, but just because of the pace of growth they've gone undergone basically since the beginning is it's, I.

It was probably one of those decisions, like a billing experimentation platform. I would bet that's something that was talked about years before and someone went, we'll do it later when we have more time. 'cause you think we'll get more people, we'll have [00:36:00] more time and we'll do it later, and then later comes.

But you're still growing at that speed that, it becomes, we'll do it later. And I've seen this time and time again, right? Like we, you talk about, oh we'll do that when we have more capacity and then that. Supposed time comes and you have more things to do 'cause you're a bigger company and you, again, we'll do it.

We have more capacity at some point, right? It hits the critical juncture where now it's time and we don't have, extra capacity to demand compared to how much we want to do, but we just have to prioritize this. 

vaarrun: Yeah. I feel like at every juncture of growth in any organization, and I'm experiencing this even now in my role, the decision you are faced with is I. What is the impact of a lot of this like opportunity right in front of me versus zooming out and focusing on something else that's more foundational and trying to figure out how much of an impact that could drive.

And I think on a daily basis in product, the trade off we're making is essentially between those two things and figuring out what is the right thing for us to focus on at any point in time.

jeff: that is so true. As is at the heart rate, it's, I have this theory [00:37:00] around the best companies aren't better than average companies because I. They always do more sometimes. Velocity is definitely part of it, but it's not always that they're, that they do more things. It's they pick the couple things at a time that they just need to be absolutely world class at and where to spend their limited time.

'cause you're always time limited. You always are limited by the number of people you have. You can go hire more people, but that's very step function. But at some level, like the stuff you can do at this second is limited by who you have in seat. And so picking. The best way to spend that time, whether you are Shopify and you have just thousands and thousands of employees, or you are a 10 person startup.

It's the same theory. It's just, you have more bets you can take when you have more people, but you're still, the quality of the bets you take and the pro projects you work on is gonna be really key to your success. As much as succeeding at a medium important thing is probably less impactful than doing really well something really big and important.

vaarrun: Yeah, I agree with you, and I think Shopify was exceptional at doing that. We had great intuition and great taste, which I think really helped [00:38:00] the company, as you can see.

jeff: yeah. I think that shows given their, their re inflection up again, where they've had just another, just explosion of growth around being able to, some of the things you've talked to, right? Being able to better serve larger merchants, expanding into more countries, and just how do you continue to build this ecosystem.

And I love that you at the beginning talked back to, the foundational thing was, enabling. People to sell and enabling these merchants. At first it was getting merchants on and enabling them to have a business, and then it became, these businesses are growing, a lot of them.

How do we enable the next level? But by working with things like Allbirds, you're also opening up to all these, like now enterprise retailers. Able to move onto Shopify, whereas before they didn't see it was a possibility. Varun, I could, I could go on about this for probably a whole nother episode or two and like I said, maybe we'll just have to have you back on again.

But I also can't steal too much of your day. I'm already stoked that you sat with us for this long. I appreciate you coming on. This is a blast, man. If people wanna talk e-comm or pick your brain or just. Learn more if they think they have something, maybe something that they could help you.

[00:39:00] Where's the best place to, to get in touch? Is it LinkedIn? Is it somewhere else? What's the best way to kinda reach out and 

vaarrun: Yeah, you?

can reach out to me on LinkedIn. It's my name, Varun Bimba. I'd love to talk shop. Anything that I could do to be useful or, share any tactics and skills that I've learned. Yeah, I'm looking forward to that opportunity.

jeff: Awesome. Yeah, I mean love talking to that. Thank you so much for coming on. We'll definitely stay in touch and yeah, look forward to having you on again. Thank you so much. We love to hear about, how the new gig is going once you're there for a little bit. So

vaarrun: Yep. Sure thing. Thank you so much again, Jeff. It was great talking to you. Really appreciate the opportunity again.

jeff: Yeah. Thank you for coming on. It's good to have you.