In this episode of The Revenue Engine Podcast, Abhijeet Vijayvergiya, the CEO and Co-Founder of Nektar, joins Rosalyn to discuss best practices for connecting your systems, connecting your data, and driving better productivity and visibility across your revenue team.

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The opinions expressed in this episode are the speaker's own and do not purport to reflect the opinions or views of Sales IQ or any sponsors.

I always say that revenue operations is responsible for aligning people. Process technology and data across the customer journey. It's about building the infrastructure to support that end to end journey and a big part of that is the data having the right data at the right time available to the right people.

But with the explosion of technology, this has been increasingly difficult, really to unify data across all of the disparate systems.

So welcome, and thank you so much for joining me. I. So excited to learn just more about your career and your journey.

I initially worked in clean technology space before, even like Tesla was a thing. So I was a management trainee at a very large corporation back in India in mum. This was a play, a company called Larson and Tubo. It's a multibillion dollar conglomerate. And I worked on a solution here in the hydrogen energy space.

So that was like kind of a formation of my entrepreneurial roots. So I played a role of entrepreneurial and residence there worked, worked on that product from scratch. So learned something to build in a blue. Market something from scratch something more forward looking sort of very amazing experience there.

Then I got pulled into like B2B SA. So after spending three years at Las tube, bro I was like noticing things moving very fast in the technology space. And that's when capillary, which was actually started by one of my colleagues senior. Back at I they reached out to me. They were building their go to market team.

I knew nothing about go to market. But they they wanted to have like people they trust on board. So they reached out to me and I joined them in the go-to market function. This was like a seed stage company. So you're doning, multiple hats. Doing various things. And as you notice in my LinkedIn background as well, like I've been into like various roles, so done customer success then was the first account executive in the company after the founder.

So literally like transition from that founder led sales to building a, a predictable revenue engine through a. To a sales team then became a sales manager, hired the first few reps and trained and coached them to success. Became a vice president of sales there, then a managing director and board member as well.

So I went through like different roles of scaling the organization as it grew to multimillion dollar business. And we had built up business across 18 different countries at like 50. Member go to market team reporting to me. And I started living through the problem myself, like problem around disconnected data, distributed teams, like missing CRM information and then obviously productivity, which just like top of the mind.

Right. So I literally started living through the problem and I lived through it for a very long time before I decided to solve that problem. So that's been like the, the, the founding journey of sorts.

There was some kind of problem that they were trying to solve. So was this, so the case for you and your co-founder, you know, and if so, you know, what was that kind of original problem in more depth and then maybe what was the original vision for the company?

Almost 10 years. I, I, I basically went at grassroots and like, so sold like the bottoms of, and like before I started setting up a team and I go to market engine and started selling. Right. So, but all the levels that like I was operating I was like trying to be more productive as an individual and trying to like drive productivity for my team.

But the fundamental trigger, I mean, for every founder there is like that tipping point or like that moment of leap, right. That you like to take. I mean, for me, it was like firing sales people. Like I absolutely hated firing sales people but unfortunately, I mean, you have to be practical. I mean, it's part and parcel of the business and you have to meet quarters and you can't go like beyond two quarters.

Missing numbers. Right. So I think there are phases where I think we'll like, go back, look at what went wrong, how we can fix the next quarter, how we can drive productivity up, how we can get a better yield out of like go to market team. And then how do you like make it more scalable? I mean, how do you like draw leverage in the business as you scale your B2B SA because that definitely.

Obviously impacts your growth as well as cross margins. So in order for like doing that, like one of the important things that I found was the reps that we were like laying off. I mean, it was not just their problem. I mean, there's also a problem around enablement their problem around coaching systems automation and processes, like what it takes a village to like close a deal.

It takes like. The whole company to like, support a team. Right. So just felt that there's a lot more, the organization can do to support these sales people. So it started like brewing in my mind that okay, what can be done to like, avoid like fir these sales people? How can. Like reps meet their numbers.

Miss their numbers. Right. And I think on an average, like for the last five years, the average drop in like rep productivity as to the extent of 42%, whereas like the spend on sales tools have, has gone up seven X in the same period. Right. So it's like amazing how, how they are like completely not correlated.

So now I just went very deep into like solving this problem. So I then like was looking. Initially that, okay. Let's start something in the sales enablement. So that was like my calling that, okay, we have to fix this problem around quota attainment. We need to democratize it. So that's what like was my calling.

Okay. No more firing reps. Let's just solve this problem. Can, can we drive productivity up? So with that thought, I like went to my co-founder back then, like urban. RS. So he was like at Zendesk, he was doing quite well. He's also like from, I, we know each other for 22 years. He's also like a student at IM the bot.

So he did his MBA as well. So he, he went, he started more than me and then, and he's also like more experienced for being an entrepreneur. So he's done two startups before, but then let later on, like, he was like working at send desk and I went to him like with this problem that, Hey, do I, I want to like.

This big problem around productivity. And what do you think is the cause? Right. So we both brainstormed and we thought about like, and we went through this five Y process, like, okay, you keep going deeper into a question and ask like wifi times and on the fifth response you'll know the root cause.

So for us, that root cause came out to be data, right? I mean, in order to do anything, I need data to get the insight insight can drive action and action can drive outcome. So that was like a clear thing that came out. So that was very foundational to building Nektar. Arwin came on board and like Fe of 20, 20 we both decided to solve this like big revenue data problem.

And that's how Nektar was born.

We're always, we talk about, you know, I always preach about how we're, we're tasked with aligning people, process tech and data, right across this customer journey. It's all about building that infrastructure to support that end to end journey and a big part of that is data. right. Having the right data at the right time available to the right people.

And I saw on the Nektar page that you talked about disconnected systems leading to disconnected data. Leading to disconnected people. So, so, so incredibly true, right. The disconnected systems that then becomes disconnected data and then disconnected people. So what are your thoughts here on disconnected systems?

Like what do you see you know, organizations really doing right. And, you know, obviously what are they doing wrong also when it comes to this?

We had like a free flow of capital. And obviously a lot of decisions got taken up. Right? I mean, a lot of platforms was well procured. There's this growth at all cost mindset which basically drove a huge surge and consumption. Tools in the tech space. So consumption in terms of like expense, but not in terms of.

So the big reality that we, we found, like when, as founders, we started doing our own research and spoke to a lot of rev, ops people, lot of users I mean we realized that more than half the tools were not even getting used, they were taken up and they're like lying on their tech stack and leaving basically the rev op team to deal with like the, the tool mess, right.

An enablement team to like, basically look at adoption of those and for a rev op team to like look at where. A data is going in. Right? So when I talk about disconnected systems, it's about like different silos being created. So the marketing team has gone ahead and bought like 10 different tools that they need.

The SDR team has bought like five different tools that they they want to use. Then your AE team is using like three different tools of their choice. There's obviously a CRM system, which, which Isla glad that it's one system . And then like you got customer success team using like their own system.

They might. Use CRM as well. They might be using a customer success software. There's a pre-sales team who, who don't have a system who would be like operating out of like different tools. So we just realized that like the entire revenue cycle is is scattered and siloed. They have their own tools, which don't talk to each other.

CRM is supposed to be the system of record, but it's, it's not doing that job with no fault of its own. Right. I mean, and CRM in itself has like a big adoption issue with its own core users, right? The sales reps, they don't give, give data back to CRM. So this basically, I mean, through a, a, a big problem to the rev op people, right?

So not just like a missing data or incomplete data. but also like disconnected systems, which are like, just augmenting this problem. Right? So that's, that's what we saw wrong. And once you have like disconnected systems that, that obviously reach to disconnected data and then disconnected teams. So it won't give you like the insights you need to like drive the outcomes.

Right. So it actually gave, also came out from our five Y that was like talking about earlier. That's what we put, decided to put it on our website.

And like create this whole community around revenue, operations, bringing best practices. Recently, we, we released this, our rev ops roadmap ebook as well, where we published like insights. 16 different rev, op professionals, practitioners who shared their best practices on like 1 0 1 around how you create a rev ops roadmap.

So things like those, right? So when, when you come at solving this problem around disconnected data or disconnected systems, I think the first thing, and again, I think leaning onto one of the things that you shared, which I quite appreciate. And on the same page pages, like mapping the customer life cycle, right.

And AKA the buyer journey. So, I mean the first and foremost thing we have seen some of. Rev op teams do is chart that down from a lead to cash cycle. Right? Draw the entire sales process against. From awareness to closure to expansion and then like documenting the tech stack against this.

Right. In terms of what tools are you getting used or what do you have in your like tech stack? Used is a, is, is a second question. Of course, but what tools you have against like the sales process at different stages and across your buying journey. And then basically audit it. Right. I mean, audit is very important.

And then it'll give you like an understanding of where are, where is the process breaking? Where are the data gaps where are the like leakages with respect to productivity or revenue or, or data in general. And. I think nine or 10 cases we have typically seen, like there's a lot of missing data to even answer some of these gaps.

Right. So that's why like, something like Nektar comes in and we do a scan and like help them first get that data to understand the gaps and then use that to like obviously solve the problem. Right. But yeah, I think we would recommend to like go through a process like this, do a full audit and.

Then start for by fixing one source. So once you, you fix one source followed by one tool and one system at a time and then branch out from there. So go, go small to go big go slow to go to move fast later. I think that's the approach we advise because unfortunately I think rev ops is an after.

For most businesses. Right? I mean, you and I are a big proponent of like having rev ups from day one. But I think a lot of automations don't invest in it for a very long time. Right. And then it's like too late. I mean, you've got like a Bemo of data and like clutter of tools and processes to deal with. So it's something which cannot be solved, but it's obviously a long heavier lift at that point in time.

You know, when we talk about data, you know, I mentioned earlier kind of, I, I always think about everything starts and ends with data, right. We all know that we need data. We want more data. We want better data. But the real question I always ask people is what are you going to do with the data, right?

How do you make the data actionable and then make decisions, right? To really improve your business outcomes with that data. And one aspect of this is context, right? You have to have the right context around the data. And I know that Nektar helps with this contextual. Sorting. And I saw this as well about your business.

So maybe, can you share more about this? I mean, this is super interesting to me. You know, what does this mean to you and then why do you see this as important?

So we are like, I met him at one of the events and we are talking about it. And we're discussing about tech stack revenue operations, and like business growth. And obviously, I mean, for fortune 500 companies, productivity is as important as, as growth. I mean, cause the market punishes you, if you're not like hitting your number, right.

I mean it's out there in public, so you need to meet your number each quarter, every quarter. Right. So one thing that he mentioned that stood out is like he said that like for my. To run predictably. I need insights. I need insights every minute. And he said that I have got like hundreds of reports.

I got like dozens of tools, hundreds, hundreds of reports, but I have very few insights. So that thing stuck with me when he shared that. And I mean, just took that as a, as a, as a piece of information for us to work deeper as we started building Nektar. So you're right. I mean, there's no dirt of data out there, right?

And the whole digital data workload increased we are all like communicating a lot more digitally than we used to do. Just a couple of years back and that's like generating even more data. Right. So, so how do, how do you handle all of this information? In fact, like systems like CRMs are not even designed to handle like this kind of modern digital data workload.

So. That's where I think a lot of these integrations don't exist or they're like broken or they're superficial in nature. And that results into the data leakage. And I think CRM is, if you look at something like Salesforce, right, it's fundamentally structured around four objects lead contacts, accounts, and opportunities.

I mean, there are obviously much more to it, but the fundamental building blocks are like these core four objects. And you need like to sort your data. Neatly into these objects, right? You need to like, be able to figure out the right activity that's happening across your buyer journey, across your sales cycle across your revenue facing team and the right activity against the right contact.

In your buying committee that needs to be there in your CRM at the right place. So that's like a, a great example, very simple, but a fundamental example of like contextual, right. And you'd be surprised to see like and you being like a ops leader all your life, and you'd probably resonate.

This will resonate with you. It's, it's surprising to see what percent of the data is missing or it. Mess in the CRM, right? I mean, we spoke to our 140 rev op folks across the last two years. And not even one said that, okay. My CRM is like pristine. And I have like all the data rightfully stored in all the objects that I, I need them to.

So that that's where we, we started building this contextual sorting and that's where the whole AI and machine learning models come in, where you go through through this all digital communication channels and systems. And the data that you have from like, not just now to future, but also historically the communications that have taken place right across your revenue facing team with their buyers.

So our system goes and like analyzes all of these communications and contacts and the activities with these. And we are able to contextually sort them in the right lead account opportunity and the contact. Right. So if we don't find an opportunity. Or even a lead, we show it as like a, a, a suspect.

That you can probably look at it, right. Or if you have, like, we noticed a rep was moved on. But there are no contacts against the opportunity. Even in the past, we were able to bring all of those contacts the rep was speaking with, but they're not in CRM. So we fixed this historical data with a very high degree of accuracy, as well as on.

All of these like data sources are connected and all the data automatically flows into CRM. And all of this happens to like API connections with like modern ML, AI models with like no touch no adoption needed with the users and it just works like a clockwork. Right. So the big believe there is like drive automation using AI and generate the insights that the business needs without like the reps or users to do the hard work that they need to give this data back and do that contextually.

So that's where like the whole contextual sorting plays out.

Yeah. Or digital transformation. There's a lot of these kind of terms. That mean a lot of things to different people. But I mean, I think it'd definitely be useful if it's used appropriately. Right. So, you know, you talked a little bit about leveraging AI to kind of remove some of that human, you know, needs to go do manual work.

You. Can you maybe talk a little bit more about that or maybe share, you know, what your perspective is on in terms of, you know, how should people be thinking about how to leverage AI, right. For revenue?

Right. I mean, everybody has like a keen interest on what AI can do. But they're also like cautious on like what it can do. Right. Yeah. So I think an important thing to note is like AI while it, it basically can scare people off by let's say replacing jobs, but there are different jobs that can get created.

Right. I mean, in fact, AI will like give time back or like can potentially unlock time for people to become more strategic. Right. So just one example, when you look at go to market teams, right? I mean, there's so much of work that happens where like it's still manual or semi-automated which, which can be actually that work can be replaced by AI.

It can actually drive, drive people to focus more on strategic aspects because they have that time available. Then just two, like day to day mundane jobs right now, if you look at Gartner as well. I mean, I think just the other day, like probably last week where I think Gartner published a report around how AI is going to change game for 20, 22 and beyond.

And they, they mentioned one of the. Important use cases or like they call it a perfect job for AI is like CRM data entry. It just came out in their recent reports. I mean, so the role of AI, I mean, in an nutshell should be to make the job of go to market team easier. Right? Whether it's like automating the workflows or like capturing the data, which is so painful to be captured all like surfacing insights after.

Clutter of like systems and tools and like historical data. And, and give that at the right time to the right people who need to like take those actions, right? So that people can focus on like strategic aspects of their jobs in taking those core decisions, which can drive phenomenal outcomes rather than like firefighting or dealing with like tactical.

Right. So that's where I see like AI playing a role in like driving, go to market function up. Yeah. Yep.

And now, now everybody acknowledges that it's a default. Right. People know that, like it just helps them to be safer when they're driving. So I think it, it happens with anything new that comes in. Like there's obviously. That, that aspect. Yeah.

So either, maybe. A couple of things, maybe the top two or three things that you think, you know, all CEOs or maybe revenue leaders should really be thinking about today to really help accelerate revenue growth. Yeah.

So if like COVID was not enough. We, we are dealing with a lot of like different global issues, macro issues. And obviously it's, it's had a big impact on business, right? I mean, so I think the most successful companies in past are like the successful companies that are going to be in future. I think one thing is pretty common is like a relentless focus on productivity.

And if you like if you would have heard about Google as this as well recently, I think sun, which I just talked about, like focusing on productivity, right? I. Oration at Google scale. I mean, they've got like piles of cash that they're sitting on. Right. I mean, they don't need to be worried about like productivity and nothing will happen for like decade, 15 years or so.

But they are thinking about productivity all the time. Right? I mean, that's why they stay competitive. Like apple thinks about productivity. So all, all a great businesses. And automations, they are hyper focused on productivity. So that's what this crisis is like throwing at us. Right. I mean, going back to the basis looking at driving sustainable business, building sustainable business looking at productivity at all cost as compared to growth at all cost.

Right? I mean, so there's a mind mindset shift that's required. That's that's number one. Number two is like, Be very data driven. Like, I mean, if you're data driven that drives transparency, that drives accountability and that also drives better collab collaboration. Right. So I think that's, that's pretty important.

And yeah, obviously, I mean, the first thing to do is like, if you want to be data driven, you need to have the data. Right. You need to have the right data. So like fix the data leakages that you'd have, which are contributing to like your productivity and revenue leakages. Right. And then yeah. Instead of like duct tap, Or like basically ignoring the leagues across your process.

I mean, solve them structurally, right. I mean it's so unfortunate, like during the, like the sole layoff period where like a lot of like jobs are getting slashed. I mean, I've been seeing people like laying of rev, op people. I mean, that's like the worst thing that you can do in this market.

Right? I mean, the first thing in fact you should do is like, go hire a rev of person. If you don't have. Right. Or like empower your rev ops team. Right? I mean, they can actually come in very handy. Right? I mean like an a goes probably like a quota for that particular a gets impacted, but a rev person goes wrong or, or a missing rev op person, like.

Affects the entire team. Right? So I think most importantly, like invest in rev ops. Like they can come in and like solve some of these problems more structurally. They can solve the upstream problem that's causing like this downstream issues that the business might be facing in the tough market.

Right. So that would be like the second thing. Right. And then like obviously overcommunicate, right? I mean, with your team, with your customers with your investors, with, with all the stakeholders, right. And then obviously focus on sustainability, right? I mean, ignore the quick wins hack. That that was used in past, but like looking at more sustainable way of like running the business.

Cause go to market execution can create such a big difference. And that's where I think rev ops has this like amazing position of leverage. Right? I mean, they have that one vantage point from where they can like make a big or. So thes automations learn it. They'll see the impact. And I think the, some of the most productive Orination and high performing Orination have one thing thing in common.

I mean, they've leveraged rev op in a, in a great way.

Yeah. So I love to learn from any moment from anyone at, at any time where it's like a two month old baby or like a hundred year old person. So I strongly believe in learning. So I think one advice I would have, like for everyone is just especially for entrepreneurs, right? I mean, we go through a lot of.

Learning and unlearning experience. So my advice would be to like keep learning and, and be open to unle unlearning as you go through your entrepreneurship journey.

Yeah. I always tell people that it's like, I've been doing, I feel like I've been doing rev ops, you know, you said all my life, but yeah. Pretty much all my adult life, but at the same time, I'm always learning. Right. Yeah. And if we're not learning, we're not growing, so that's right. Great. Yeah. Well, well, thank you so much for joining me, but as we wrap up and before I let you go, I always ask all my guests two things.

One, what is the one thing about you that others would be surprised to learn? And two, what is the one thing that you really want everyone to know about you? And it could be the same thing. I found that at some guests actually is the same thing, the surprise and the, you know, want to know. Yeah.

So that was like, literally, oh my gosh. Yeah, that, that was a record for me, a personal record. So I've been living out the suitcase for like a very long time being in sales. Like I was managing a business across 20 countries. So I was like always on the, on a, on a flight every time. So. I was taking a flight every second day.

And I've been to like seven countries. Wow. Yeah. Yeah. So that was like one thing, which like a lot of people get surprised. And that's where like, I, I, I even started looking at like, oh, I needed more insights. I needed more data to take decisions because I can't be like With my people all the time.

Right. I mean, I had like this like distributor team and scattered data. So I would say like, in a way, like this whole lecture experience was brewing all through that experience. Right. I mean, as, as they told, telling you about like the solving the problem or living through the problem before solving it one thing which like would like everybody to know about us.

So we actually all ran like virtual. Marathon from like different places. That was amazing. But I'm looking forward to like my, my first marathon this year. So I'm running in the Singapore marathon early December. I'd also like, oh, wow. Or like have a cause. So I'd probably put like, put up a link for like the cause.

Yeah. And yeah, love to like, have people support the cost for which I'll be running. I haven't picked up one yet, but I'll be doing that soon. And yeah, with that, I will also be completing thousand kilometers. For this year.

Thank you so much for being a guest on the podcast. I just, I love all of the, just a lot of good information, lots of good insights shared today. So I really appreciate your time and just super grateful for your you sharing your story.

This episode was digitally transcribed.