Gunja Gargeshwari Podcast Transcript
Gunja Gargeshwari joins host Brian Thomas on The Digital Executive Podcast.
Welcome to Coruzant Technologies, home of The Digital Executive Podcast.
Brian Thomas: Welcome to The Digital Executive. Today’s guest is Gunja Gargeshwari. Gunja Gargeshwari is the Chief Revenue Officer at Bright Data. Proud to be at the forefront of tech security, Gunja has tenured experience at both a human and business development level, with over 25 years’ experience in sales and marketing at leading tech companies such as Oracle, AWS, and Zendesk.
Gargeshwari is part of the executive leadership team at Bright Data and oversees all global go to market operations. Gargeshwari leads the company’s extensive business development and sales teams, focusing on elevating Bright Data’s valuable customer base. Gargeshwari holds an impressive track record of business leadership roles in IT services and SaaS at leading tech companies, while also expanding the company’s market reach to new data territories.
Most recently, Gargeshwari served as Global Vice President of Platform Sales at Zendesk, where he led go to market for multiple product lines and drove Zendesk’s enterprise growth. Prior to Zendesk, Gargeshwari managed go to market operations at AWS, working with leading customers in the digital, native, and ISV space.
He also spent 18 years at Oracle where he held various leadership positions.
Well, good afternoon, Gunja. Welcome to the show!
Gunja Gargeshwari: Good afternoon. Thanks for having me.
Brian Thomas: Absolutely. This is so fun. I really do appreciate making the time to sit behind a microphone no matter where we’re located in the world to have a great conversation on what our guests are doing these days.
So, I appreciate that. And we’re going to jump right into the questions here. Talk about your career in technology as a program manager, product development, sales director. Now you’re the chief revenue officer at Bright Data. Yeah. Could you share with our audience the secret to your career growth and what inspires you?
Gunja Gargeshwari: Yeah it’s been a, it’s been a very rewarding journey and I’m lucky to have had the opportunity to have roles across different aspects of any given company’s organization and the one common theme that I’ve Kind of stuck to all along is I started my career initially in services, actually working at customers, working with them to implement some of their complex projects and so on and so forth.
And the thing that gave me the most. Encouragement to keep going down this path and to keep doing it and the thing that delighted me the most that customers were when you look at when they adopt the technology, when a project goes live and. Everybody’s life becomes better because of what you’ve put in place and that initial feeling that I got in the beginning of my career that if you want to call it that that kind of high that you get when you’re with your customer and you see the success of what you’re, what you’ve been talking to them all about and when they see that actually come to fruition, that is really what keeps me inspired day over day.
So that customer obsession That making sure that you’re always focused on the value that you bring to your customer and seeing that value being realized, not just from a perspective of going and pitching the value, but seeing the value come to fruition and being that lifelong partner for a customer.
That’s been the common theme that’s gotten me through my career and. That’s something that I try to instill with my teams today, even to basically focus on the customer, always obsess about the customer success and make sure that you’re always with them through the journey, not just at the beginning, but through the journey of when they realize value from what you’re talking to them about.
Brian Thomas: I love that. And again, it’s serving others, and we get not only fulfillment. And it provides purpose for us, but we are actually helping others. And when customers see that you will, you and I both know this, we’ve been in this business a long time. It makes all the difference in the world. And that’s where you build a lot of loyalty with your customers.
So I appreciate your share on that Gunja. And it’s no small feat Gunja. Working with the world’s largest data collection platform from a strategic standpoint. What are some of your big goals for 2024 and beyond?
Gunja Gargeshwari: We are in a bright data is in a very unique space. Data collection or public web data is just one aspect of what you see.
But the reality is companies are moving from just relying on their own internal data to make strategic decisions to actually harnessing the power of All of the external data that’s out there, whether it’s customer sentiment data, whether it’s market share data, whether it’s real time economic data, a variety of data that today is available to them via the Internet, which wasn’t available to them many years ago, and that is becoming the world’s biggest library.
Right. And when what we want to do in 2024 is really educate our customers on the power of that data, because it’s not very well understood on the benefits of using the data and the potential of using that data for almost real time business decisions, along with strategic decisions, make it a part of their enterprise planning process and make it something that derives the value of what they’re actually pouring into the market. They can see the value and the returns coming back from that from the market almost instantaneously. So, the goal for 2024 really for us is to be able to build that awareness in the market of what this opportunity is, whether it’s collecting data for.
Simple planning purposes are you really collecting data for even putting things like AI, where you’re training your internal models with the data that you’re collecting? And how do you leverage the value from that? So that’s really the big goal for us for 2024 and beyond, right? We don’t think we can do that in a short period of time.
It’s a shift, a mindset shift in the way companies think. And I think it’s going to take us quite some time to get there fully, but We want to accelerate that as much as we can.
Brian Thomas: Thank you. I appreciate sharing your vision, your goals, and your strategy around this. And you’re right. The Internet, I think some people say it was like, the 4th industrial revolution when that big boom came about.
And of course, the right data and you are taking. Advantage of this. And I think it’s important that you know, you share some of your strategic vision with our audience so they can understand more about how you are helping companies around the world provide insights on this data and if we could, if you don’t mind, let’s talk about your tactics on collected data via web scraping and other methods.
Without giving away your proprietary methods, could you share maybe some of the successful outcomes with your data gathering methods?
Gunja Gargeshwari: Sure, those are kind of two separate topics, so I’ll give you the short answer on the first one, and then we can talk about the second one a little bit more. So Bright Data’s whole technology platform is built with the purpose of effectively collecting data from the web at scale.
We do not collect data behind logins, or we do not collect any PII or any of that kind of information. So, everything we collect is public data. We are GDPR compliant. We are we have all of the compliance that you need. So, the data that we collect is data that you can use without any hesitation. And that is the really the value of our platform is you can either use our platform to collect the data on your own and we give you simple development environments.
Gosh, there are so many that I can talk about that it’s a, I mean, it’s a broad area of industries that uses everybody from retail to e commerce to financial services, travel and transportation people and every single industry that you can think of uses use bright data. And why do they use bright data?
Right? And if you think of some of the successful, bold. Outcomes that you’re thinking about from this perspective. I’ll give you a couple of examples. Optimizing ad spend for a, let’s say you are a large company and you wanna figure out where you want to advertise on Amazon and eBay and everywhere else, and you have a specific product.
And we had a specific, I’ll give you a spec, even more specific example of a battery manufacturer who came to us and said. We want to advertise on Amazon for AA batteries only, so we want to know every product in Amazon that requires AA batteries, and we want to know exactly where these AA batteries are on their best sellers list so that we can really optimize our ad spend to really put in our ads for those specific products where AA batteries are required and we can spend more on the best sellers versus trying to place it on every single product that requires AA batteries.
So, level of granularity that they can get from that public web data and with changes also on a very frequent basis and the way they are able to control their ad spend on major platforms. That’s a big win for them. So that’s one example. If you look at other online retailers, a lot of them and online brick and mortar slash retailers as well.
They come to us to kind of figure out what the, what are the products that are trending the most in the market? What are some of the prices and promotions that are being run across the market? And they try to be competitive almost on a daily basis. They change their prices, and they change their own promotions and all of those things based on the data that they collect.
So that’s a couple of examples in that arena. And then. In financial services, they’ve got hedge funds and investment banks using it to really collect information about companies that they want to invest in and also to collect information about their companies in their portfolio and how their products are doing in the market.
What are the competitive. S and whether they’re able to maintain their market leadership, whether they’re able to maintain a certain price point, all of those things change on a very frequent basis of financial services companies that are looking for that. And then we’ve got travel and transportation companies who are aggregating data across multiple different airlines and hotels and everything else to be able to offer their customers the best product.
So. Those are just 2 or 3 examples of the use cases, but there is a ton more that we can do. And we also have a lot of nonprofits that uses as well. In the field of education and in the field, many other fields for providing for figuring out how to provide social services. To the end consumer. So, at the end of the day, it’s a very broad set of use cases and data is universal and the value of data exists for every single industry.
Brian Thomas: Thank you and I appreciate you unpacking that. That is awesome. The things that you can do now are just scraping again. I know this is all public record, but you do such an efficient job with this and truly help businesses glean some of that information that makes them provides them that value that they can make either a tactical or a strategic decision on the fly sometimes.
So, thank you again. And Gunja, we are a tech podcast platform and I’m a technologist. We would like to ask every guest if you’re leveraging some of that new and emerging technology in your business, is there anything you might be able to share with us today?
Gunja Gargeshwari: Yeah. I mean, like AI is the new buzzword and everybody’s leveraging AI all across the board.
Now we power AI for our customers because. Customers use the data that we collect to train their AI models and make their models better. So it’s a key portion of what they’re trying to do. But internally, we ourselves are using LLMs at various different stages in our data collection process, right? Our own tools to automatically extract data from a website, create dynamic schemas on the fly, make the validation, do the validation on the data, enrich the data.
Do things like matching. All of these things are possible for us to for now to use a I to make it better to make it smarter and to make it more efficient. So we use it. If you look at our collection process where we create a schema for the data, we actually write the data collection program. We validate the data, we do enrichment of the data, and then we deliver the data.
And we even do insights because we have an insights product as well. So, we deliver insights into data for retail customers. In every stage of the process, we have incorporated LLM so that is powering it to be more accurate, more efficient. And that’s really given us the advantage from a go-to-market perspective.
Brian Thomas: Thank you. Most appreciated. We do talk about AI a lot, of course. And that has really, I think, changed the game just here in 2023. So, again, good. I appreciate you sharing your insights and perspectives from where you sit, and of course from Bright Data’s vantage Point. So, thank you and Gunja, it was such a pleasure having you on today, and I look forward to speaking with you real soon.
Gunja Gargeshwari: Yeah, thank you for having me. And it was a pleasure to be able to share some of the great things we are doing. And we look forward to having a great 2024 and wish you all the best for the new year coming up New Year and have a great rest of your holidays.
Brian Thomas: Bye for now.
Gunja Gargeshwari Podcast Transcript. Listen to the audio on the guest’s podcast page.