Evolving Industry:

A no BS podcast about business leaders who are successfully weaving technology into their company DNA to forge a better path forward

Break Glass in Case of Growth: Leveraging Data to Scale in Real-Time

George Jagodzinski (00:00):
Our guest today is a builder, a leader that drives growth at every organization he touches. From Oracle to Amazon, Zendesk, and Bright Data. I'm joined by Chief Revenue Officer Gunja Gargeshwari. He explains how he drives growth, how he figures out when to break glass or not, and, more importantly, he shares some stories that should inspire us all to just get our heads out of our own data lakes, stop drowning, and look at the big wide world of data all around us. Please, welcome Gunja.

Announcer (00:27):
You're listening to C-Suite Blueprint, the show for C-Suite leaders. Here we discuss no-BS approaches to organizational readiness and digital transformation. Let's start the show.

George Jagodzinski (00:40):
Gunja, thanks so much for being here.

Gunja Gargeshwari (00:43):
George, it's a pleasure.

George Jagodzinski (00:44):
You've got a fantastic career. You've gone through a lot of personal growth, a lot of corporate growth, and I thought it'd be exciting to discuss that concept of: how do you drive growth? How do you manage the change that comes with that? What are some of the most rewarding things or the things that you're most proud of that you've grown in your career?

Gunja Gargeshwari (01:06):
Thanks, George. And as you mentioned, I mean, my career has spanned a variety of companies, and I have spent a long time at Oracle at the beginning of my career, followed by a great time to be at AWS when they were just looking into growing their business, and then followed by Zendesk. But if you look at a common theme across all of these three companies that would characterize what I've done, it is really in each one of these companies, I've gotten the chance to challenge myself with building businesses within these companies, and that has been kind of the common thread across all of these jobs that I've had over the years. At Zendesk, I was building two different businesses from scratch. We didn't have a platform business when I started, and we also had done an acquisition for a Salesforce automation tool, which was largely geared at the SMB and mid-market segment, and got to build those from scratch over four years into almost a hundred million-plus businesses, which was amazing to do that from scratch.

At AWS, I had the fortunate opportunity to join just as the digital native segment was taking on. So really, managing the North America segment. And today, you would recognize the customer sets that we grew as the “who's who” of the industry for everybody from Databricks to Snowflake to Slack, and everybody that you would recognize were all companies, which were very small and were all part of the segment. So watching those companies and helping them grow, and bringing them through the transformation phase for what they are today from a platform vendor perspective was a tremendously rewarding experience.

And before that, even at Oracle, I've helped grow the retail and financial services businesses. And I've even spent a stint where Oracle had a startup with McKinsey, which was a complete spinoff where I ran product for it. So really fortunate in all of these companies to have had a variety of roles that has really been rewarding, but each one has given me the experience to take something which is an idea, take something which is a concept, and really take that and turn that into reality as a business and with actual revenue, meaningful revenue.

That has been the highlight of what I've been doing over the past few years. And that's exactly why I joined Bright Data as well. I see the opportunity for Bright Data to be the premier leading data provider for what people need, all the way from data collection to analysis to insights, and that's the journey that we are on, and I'm excited to be there.

George Jagodzinski (03:30):
That's fantastic. You're really a builder. What drives you to be such a builder and grow these things?

Gunja Gargeshwari (03:37):
At the end of the day, it's customer delight. It's really, at the end of the day, when you go to a customer, and you're able to offer a set of services that really makes a difference in their day-to-day operations, it helps them move the needle on how efficiently they operate. It helps them move the needle on how they're able to drive more value for their own customers. And that customer delight, when you walk into a meeting, and I'll never forget this, that walking into a customer when I was at AWS, you walk in and… this was a healthcare startup in Miami, and in their lobby, they had a big board on which they had “Welcome AWS” with our names on it. And the CEO walked out and gave us a tour of their entire operation. That was how happy he was with the services that we were providing, with the products we were using, and how well we are structured the relationship. So that sheer customer delight, when you know you've made a difference and the customer is happy to meet you and doesn't view you as a vendor, but views you as a true partner in their business, that keeps me going every day. That feeling is amazing.

George Jagodzinski (04:40):
That's so interesting because, when I was looking at your full career, you were a delivery guy at the beginning, and that is such the mindset of a delivery person is just that customer satisfaction, the surprise, and delight. I love it. So you've obviously got a great track record on building these things, and so what I'm curious about now is: how do you choose? How do you see the potential in the idea, the thing that you want to grow? Do you have a mental model on how you figure that out?

Gunja Gargeshwari (05:10):
Yeah, I think one of the things that you really do to be able to understand what is the next thing you want to pick that you want to grow is really listen to customers. So in each one of these interactions that you have with customers, when you're talking to customers, partners, and the entire ecosystem, you're constantly looking for what you call as opportunities or gaps in the landscape. You're looking for what is beyond what just you bring to the table from a product perspective. What are the real business challenges? Where do the gaps exist? Where are they really looking to make improvements within their own model? So that really gives you a sense for where the gaps are in the market.

And the best example is, when I joined AWS from Oracle, AWS was a customer. They were buying a financial services software. I was selling that to them. And AWS was deploying financial services globally at a rapid pace. But when you looked at the business and when you looked at the model at which they were growing, you could clearly see that the digital native segment was going to take off, and you could clearly see that they needed a structured approach in which to grow these customers and retain these customers so that they don't go to the next available cloud vendor. And building that whole approach, we didn't even have a concept, George, of a committed contract at AWS when I joined. Just think about that for a second.

George Jagodzinski (06:30):
That's Crazy.

Gunja Gargeshwari (06:31):
There was no committed contract. So the basic mechanisms weren't there, and then they had this rapid growth with customers. So at the end of the day, I saw the opportunity there to say, “This is a technology that's got an adoption rate that's great, but you need to put the processes in place for you to be able to handle that customer demand to make sure that they're using your technology the right way and make sure that the adoption curves are correct and optimal.” That is the opportunity that I saw that we could move the needle when I joined AWS.

And when I joined Zendesk, the gap really was customer service was an isolated island, and there was the need for a platform to be able to plug it into the ecosystem of all the other systems that exist from a customer touchpoint perspective. Everything from marketing systems to systems of engagement, which were Slack and, in some geographies, even WhatsApp and SMS and email. So you needed a real place where that could be done. So those opportunities is what I look for when I'm talking to customers is those real gaps where you can move the needle and make a difference, and that's kind of how I pick where I want to be next from a perspective of building businesses.

George Jagodzinski (07:40):
Interesting. And you've also managed to grow businesses-within-a-business, but then also you're growing just the business on its own at Bright Data. I'm curious, what do you see as the pros and cons of either? It's never perfect, but I'm curious, how do you compare the two business-within-a-business versus a business on its own?

Gunja Gargeshwari (08:02):
It is different by company. If you look at a company such as Amazon, which is inherently built for innovation, that business-within-a-business happens every day. Whether it's Amazon Business, Amazon Fresh, any one of those things, all of their businesses are grown like that. They've got an incubation mechanism, which is very strong, and they kind of have the methodology in place. So those places, it's much easier to do those. Places like Zendesk, you got to break some glass to be able to do that. It's not easy. Not everybody wants to move in the same direction. So there is internal selling that has to happen that becomes as important as your external customer-facing mechanisms that you're building, and you're constantly in that internal selling mode to make sure everybody understands what the value proposition is of what you're taking out to market. So that, I think, is the fundamental difference based on how companies are structured.

At Bright Data is a whole different ballgame from that perspective. At Bright, it's not as much as building a business-within-a-business or building a business within a scratch. The potential for Bright Data is so huge, and the segment that we play in is so small right now. It's one of those things where it's really you're taking the business and scaling it rather than doing anything else and getting into adjusted segments and fully realizing our potential across the data landscape. And that is a completely different motion than what I've done before. It takes some of the same principles, but really, in this case, I believe that we've barely scratched the surface of what we can do.

George Jagodzinski (09:41):
And in exploring that topic, I'd love to poke into the breaking glass part of it because I've become obsessed with stages of growth, both in how we're growing our company and then when we're working with our clients, helping them grow. It seems that there are these very distinct stages of growth, and there's these transitions between them. And some of these transitions, you need to really throw out a lot of stuff that you've been doing before and reimagine what you're doing. And it seems to be this constant pendulum back and forth where it's like you really feel like you've got everything working well, and then everything has to change again. There's a lot of friction, and then you have to move through it. And I'd love to hear maybe even some stories from the trenches on how do you push through those breaking-glass stages of growth? And I'd love any tips and tricks personally, selfishly for myself, but of course for the audience as well.

Gunja Gargeshwari (10:31):
Breaking glass is an interesting thing. So the evolution of most of these growth stories goes like this. You have an idea. You have a very strong concept. You come up with a product that is your core MVP. And you go to market in a broad fashion, and you get, initially, most of these will see product-led growth where you've hit on a certain gap in the market, and there's people interested, and it comes in. There comes a time in the evolution, and then you build for that funnel. We built for hunting the funnel, and you build for product-led growth, and you make that mechanism efficient. Eventually, that comes to a point where you've hit the plateau on the product-led growth, or you're approaching the plateau on it. And the key is to be able to watch for those well in advance. And one of three things needs to happen for you to translate it into the next stage beyond that.

And sometimes, all three things need to happen, but at least one of the kickers need to be there. One, either you find an adjacent space to your core MVP, which is very rich, which if your, how do I call them… Lighthouse customers will probably tell you that the solution you're giving them can easily expand into adjacent domains. They're probably pushing you to go there anyways, and they're some of your largest customers. So that is one piece or one trigger that you look for where you look for it, and you're able to identify it early enough that you're able to pivot into that.

The second thing is really understanding what your go-to market needs to be in, transitioning from the product-led growth to a sales-led growth mechanism. Now, that's where the pendulum happens. The back-and-forth happens a lot because you're not a hundred percent sure on exactly where to place the bets when that happens. And you got to almost build a mechanism which is within your go-to market organization, you are experimenting.

So some of the things that I've done successfully in my career is, for example, even if you look at what we are doing with Bright Data, and we've got us in many different geographies. And now we are looking at expanding into APAC. How do you place your bets in a region which is so wide, so varied in terms of the businesses that are there? So one of the things that you do in these when you do that is, I rely very heavily on an affiliated partner strategy. So we are going to market with partners, and we are going to market with some of our core partners as well, like AWS, and help them navigate through. You start building that six months in advance. So the way you build a plan to launch into a geography is T-minus six months, or T-minus 12 months. You land with partners, you land with affiliates, you land with motions of marketing, and you'd start building the brand presence, and you start looking for lighthouse customers. That kind of guides you where you should be going, and you start building a presence around that. So that is the second mechanism.

So the first mechanism is you look for adjacent areas where you can grow from a product perspective, and then you double down on that. The second mechanism is really you look at a geographical expansion angle, and you can use partners and affiliates, and you build. The key is you have to build that ecosystem early. When you have a product-led growth, companies usually don't think about building a partner ecosystem. They don't think about building the affiliate ecosystem. They don't think about, “We should be on AWS's marketplace,” or, “We should be a ISV partner with these five other companies.” They get very siloed into what they're doing, and then it becomes too late, or there's a delay in pulling some of these triggers where you see the back and forth.

And even there, the last piece of it is, and it's not something that is very obvious to people when you look at it when you start doing this, but the last piece of it is: have you really built the feedback mechanisms from the field back into it? Do you have a customer advocacy board? Do you have the people advising you? Have you brought in the right people who are bringing the right feedback to you from various different channels? A combination of all of those is how I would look at building the key indicators for me to be able to know how to scale these businesses. And that helps you break the glass, because otherwise, your typical mechanism becomes you are going in, you're basing it off whoever is your loudest customer, and you're following that path because they're the ones who are asking for it. And that usually leads you to a dead end. And then, you come back, and that's where the yoyo happens.

George Jagodzinski (15:03):
And then you Frankenstein your product based off that customer, and it becomes a complete mess. Yeah, I've seen it far too many times. So it's very clear when you step into these situations, you've got a pretty good vision of how you want to grow and what that's going to look like. But there are a lot of humans and people involved, and people have emotions and fears and biases. And you recently wrote an article talking about how emotions drive markets based off of the SVB situation. When you step in, how do you bridge that gap between what your vision is and then the people that are there and the emotions, and the biases, and the fears?

Gunja Gargeshwari (15:40):
It's not a point in time. It's a continuous thing that you're going to have to learn to deal with. Because you're always growing, you're bringing in new players into the company, and people are also trading through roles. So you've got to build a mechanism which is basically built on trust. It is basically built on data. And it's basically built on the fact that people can actually relate to what you're saying based on real examples as opposed to just vision. So one of the things that you need to do effectively is making sure when you're going in there you are able to take the key data points and the proof points that you're gaining in the market and that internal selling of bringing that back in, letting data speak for itself, letting the customer’s proof point speak for itself and making that the guiding light for the organization rather than just being your vision, it's probably the differentiator for it.

George Jagodzinski (16:39):
It's funny, there's so many times both in talking about how you choose the idea was based off of what the market is saying, the sentiment, and the way that you get your team aligned is based off of the sentiment, and also in the strategy and growing the product and all of that as well. I guess it's not surprising that you ended up at Bright Data. It makes a lot of sense now talking with you now.

Gunja Gargeshwari (17:03):
It does. The first few months at Bright Data, I wanted to meet customers. So I've been almost around the world meeting customers. And I've seen sports companies who are basically… Credit Investments is a sports investment company, which basically looks at upcoming players and they match them with people who want to invest in these players how to map the trajectories for these players, how they advise their customers on what the potential return on investment could be. It's all based off of data. So it's one of the most interesting cases that you see out there. This is a traditional industry of sports management. And even there, data plays a critical role. So financial services is a huge place where it plays a role. Then you take e-commerce and retail, and it just becomes indispensable.

I was overseas, and one of the big things that's happening everywhere, including here, is fresh grocery delivery. Well, grocery prices, and most people don't realize this, change three times a day. So you've got fresh groceries in the morning, that is a different price point. They change it once in the afternoon, and they change it once in the evening. But it's all based on a lot of different factors, including whether your competitors' inventory went down during the day - these are for perishables - whether your own perishables, which you've got, are reaching a point where they've got to move it out the same day. So the amount of data that goes into deciding what that price of the perishable should be by 5:00 PM in the evening is amazing. And this is all in the online grocery market, which by the way, when you go to APAC countries and stuff, it's exploding. They've got huge populations, and now it's become the way of life.

So data plays an important role in all of this. And with our Bright Initiative, this is the other reason why I was excited to join Bright Data, is also what we do with our Bright Initiative. We are helping various different government agencies to figure out everything from signals for human trafficking, figure out early signals of, potentially, people doing things like what we see in the US, with the gun attacks and people go in and shooting incidents and so on and so forth. So there's a lot that we can do, not only to help businesses, but just help the general wellbeing of people. So I think it's an amazing place to be, and there's a lot to be done, but we are excited.

George Jagodzinski (19:37):
That is very exciting. And I feel like I should connect you with Love146. They're one of my other guests on the podcast and someone that we commit to quite a bit. They're an anti-sex trafficking organization. I think that that's a fantastic fight to invest in. As a consultant, I get to go inside the walls of a lot of organizations, and I get to see the dirty underbelly of what's really happening. And I'd say on a scale of one to 10, there's not a lot of organizations that are at even above eight in how they're leveraging data. A lot of them are really low on that scale. And I'd be curious, what do you think is preventing companies from being better at leveraging data for those decisions because it just doesn't seem great?

Gunja Gargeshwari (20:21):
There's a few factors, but I think the most prevalent factor is, at the end of the day, organizations are used to looking at their own internal data to make decisions. You look at your own sales forecast. You look at your own product roadmap. You look at your own marketing data. You look at all of those, and that's how, traditionally, companies have made decisions. And where now there is an active interest in being, because they all have web presence, they've got social media presence, they've got different ways of reaching their customer, there is an active interest in understanding the output of that investments that they're making in reaching the customer, but it still hasn't made its way into marrying itself with the traditional data to be driving the insights to be able to make decisions. That's a change for them. It's a change in the way they think. And they almost don't want to believe that data. That is more for them a way of improving customer engagement, but most companies are still getting used to the fact that those indicators are probably equally important, if not stronger than their own internal indicators to be able to make the decision.

So that, I think, is a transformation that's happening. But every single incident that happens, like Silicon Valley Bank or every single incident that happens where they realize they could have done better, I think, is improving that. And there is also stories if you look at, for example, how Zara does their supply chain, which is “just in time,” and they're able to supply it to their stores exactly what's needed, and they're one of the most profitable companies when it comes to how they run their operation. People are looking at those and now starting to realize that they could use the data they've got the capability now to have that market data is validated purely based on in-store traffic when they started.

They started years ago. They didn't even have any of this information to be able to do it. But you are a retailer today, you know exactly what's going on in your store, and you know what's going on on your web properties. And a combination of that is a very powerful indicator, which can help you optimize your entire business. And I think they're coming to the realization that today the mechanisms exist for them to be able to do that. So I see the change accelerating, George, and I think it's going to continue to accelerate over the coming years.

George Jagodzinski (22:48):
Yeah, it's a tough change. It's such a human nature thing to just be blinded from what you're in every day. I like to cook a lot, and I always have the normal ingredients, I have the normal tools I have, but then I'll go to someone else's kitchen, and there'll always be an “aha” moment where I say, "Oh, I didn't know you could do it differently that way." I think one great example I've been witnessing personally and also with some of our work that we're doing is, right now, the automakers, they're trying to figure out how they use the vehicle as a platform and how they can get revenue out of the vehicle. And just this month, I got an alert from my vehicle, I could pay a subscription so that I could hear my engine noise through my speakers. And I was like, “I don't want to do that.” And I think what they're doing, they're looking at, "Hey, we have the data that's in the car. What can we do with that?" versus, “What can we do with all of the data in the world that's out there right now?” And it's tough to get organizations to have that real “aha” moment and see what else they could do. Do you have any great stories of those “aha” moments? Maybe you want to brag about a Bright Data big win or something like that that you guys have done?

Gunja Gargeshwari (23:59):
Look, one of the things was we were working with a hedge fund company in Boston. And it was a very interesting example because they're actually a reference customer, and we've got a video on that as well. But they wanted to invest in a chemical company. They were looking at different investments. And they wanted to invest in a chemical company. Numbers looked really strong, but they were very worried that they didn't know whether this chemical company would sell to various different companies that made end-customer products. How are they going to figure out whether there's the pricing of those products is going to hold over time, whether the trending was right, or whether this was a flash in the pan? And funnily enough, they figured out that the biggest customer that the chemical company had was companies that made bleach out of the market.

George Jagodzinski (24:45):

Gunja Gargeshwari (24:47):
So they went and looked up the price of bleach and the trending of the price of bleach globally. And bleach, believe it or not, the price trends were on the rise for the last few years. And it turned out that there were very few people who actually supply those ingredients for their product. So it's a very productive and growing market. And they were able to make an investment decision. And it was all based on external data to be able to come in and be able to make their critical decisions. So it is really interesting when you go in and when you look at these customers, and you look at what they're able to do with that.

We've got another big e-tailer who, basically, improvement of their entire… They're one of the biggest retailers around, and they sell outdoor summer furniture during the season. And for them to be able to understand how they were comparing to other folks, how they were comparing to especially these large wholesalers who were selling it in bulk, for them to be able to anticipate that demand well in advance, and, on a daily basis, to be able to monitor and see whether the inventory levels of the other retailers were at a certain point so that they knew what products to push, it made such a huge difference. They improved their overall sales by 50 percent for the season.

So it's amazing some of the things that real-time decision-making can really help you do that. We had a battery manufacturer who wanted to know all the products on Amazon where AA batteries are required to optimize their ad spend, and which ones of those were Amazon best sellers. Simple things like that that make a huge difference to them. And that changes daily. So it's not just looking at the data once. It's really being in tune with the data on a daily basis so you can optimize it. You can really micro-optimize your spend and get the maximum results out of it. That's amazing when you see companies being able to do that.

George Jagodzinski (26:42):
I love it. And I also love that you used a simple one because I feel like I see the power with this, especially combined with AI. And I think what people, when they think AI, they think this type of data, they think it's just this big scary thing. And, again, being inside the halls of all these companies, there's an endless list of tactical, simple things that just need to get streamlined and fixed with better data and with AI. I've just been preaching that people need to… they're drowning in their own data lake. They need to pop their head up and look because there's a whole world outside of that data lake that they can be getting a lot of value from.

Gunja, I really appreciate your time here. I always like to end with something a little bit fun, which is, throughout your successful career in life or at work, what's the best advice that you've ever received?

Gunja Gargeshwari (27:34):
That's an interesting question. I've received a lot of pieces of advice. I think the best advice that I've ever received is, “Always keep moving. Don't be stagnant.” Never rest on your laurels. Always keep moving. And that is probably the one thing that I strive to do every day is to make sure that you're always moving. You're moving from a mental model perspective, you're moving from perspective of thinking about what should be next, and you're always thinking about what is the next thing that you need to change in order to be in a model of continuous improvement. So I think that's probably the best advice I've received all my life.

George Jagodzinski (28:11):
I love it. I'm very antsy, so I very much appreciate that advice as well. Gunja, thank you so much for being here.

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