
Customer onboarding is often where good intentions often end up with less-than-stellar execution. Delays, confusion, and misalignment derail even the most promising new relationships. Why is onboarding still broken in so many organizations, and how is...
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Greg Kilstrom
Welcome to the B2B Agility Podcast where we look at the factors that drive success in B2B marketing with a focus on the people, processes, data and platforms that make B2B brands stand out and thrive in a competitive marketplace. I'm your host Greg Kilstrom as advising Fortune 1000 brands on MarTech marketing operations and CX best selling author and speaker. Now let's get onto the show.
Customer onboarding is often where good intentions end up with less than stellar execution delays. Confusion and misalignment derail even the most promising new relationships. Why is onboarding still broken in so many organizations and how is AI finally changing that? Today I'm joined by Sri Krishnan Ganesan, Founder and CEO of rocketlane, a platform that's redefining customer onboarding and project delivery. From AI driven tools to cross functional collaboration, rocketlane is helping teams implement faster, operate smarter, and retain customers better. Sri Krishnan is here to talk about the future of onboarding operations and the role of technology in scaling both customer satisfaction and internal success. Sri Krishnan, welcome to the show.
Sri Krishnan Ganesan
Hey Greg, thanks for having me on today.
Greg Kilstrom
Yeah, yeah. Looking forward to talking about this with you. Before we dive in, why don't we start with you giving a little background on yourself and your role at Rocketlane?
Sri Krishnan Ganesan
Yeah, sure. I'm the founder and CEO of Rocketlane. This is my second SaaS startup venture previously did one from 2012 to 2015, got acquired by a company called Freshworks. Spent four and a half years there learning how SaaS company can scale really, really well. Freshworks eventually went IPO, inspired by that journey, came out with the same two co founders to start Rocket Lane.
Greg Kilstrom
Great, great. So, yeah, we're going to talk about a few things here, but I want to start with just talking about customer onboarding. And I know I've certainly been through some of the pains of the onboarding process and things, so why don't you talk a little bit about what inspired you to tackle customer onboarding as the problem that Rocket Lane solves?
Sri Krishnan Ganesan
Sure. I would rephrase it in a way to say probably customer onboarding was the starting point of what we started to solve. But we always saw this as a bigger area that we can eventually focus on. So the problem stems from looking back at our previous journey and seeing what felt broken. And we identified a bunch of things. One of those was when we looked at our own internal implementation and professional services team at freshworks where we got acquired and we were running our business unit within freshworks. I felt this was an area where it was really crucial that we get things right because our customers, whether they continue to work with us, expand their partnership with us, or they look to churn at the first opportunity they get, it really felt like that depended on how we cemented their belief about the partnership. And another founder recently told me this interesting thing that they look at implementation or onboarding as the second sale that you're doing. So you first sold, you signed a contract, but you need to sell again in a way this time you're not selling your product, but you're in a way selling what it's like to work with you. You're selling the partnership experience, saying, hey, here's how it feels to work with our company, so do more business with us, expand your partnership. And we felt this was critical enough for Most tech and SaaS companies and even for services companies that do implementation type work, et cetera, and looked at the category, we saw that people were using spreadsheets, you know, horizontal project management tools, a category of tools called PSA Professional services automation to track their efforts, project profitability, et cetera. We felt if we create something that is a lot more all in one and start with a focus on onboarding or implementation teams, and expand into every kind of professional services team that runs project based services, then we have a huge market and we have a real problem to solve, which is how do we make these services, you know, consistent in how they're delivered, how do we help ensure that leadership inside the company is always on top of things? That gets proactive alerts, proactive governance versus reactive. We felt there's a lot of problems to solve so we picked this space.
Greg Kilstrom
Yeah. So can you talk a little bit about the component of this, you know, how are AI driven tools helping to transform some of some of the things that you're talking about and you know, what impact are you seeing on implementation speed, retention rates, all of that in relation to adding AI into the mix?
Sri Krishnan Ganesan
Right. I think there's many areas where you can apply AI within this world that we're talking about. Right. One is, I would say the low hanging fruit is there is work around work. How do I, you know, and I'm going to, you know, broaden this from just AI to AI and automation because I feel what is of essence today is how can we get teams to radical efficiency. Whether it's, you know, AI at the core of IT or automation or a mix of both, doesn't matter.
Greg Kilstrom
Sure.
Sri Krishnan Ganesan
But how do we ensure that the follow ups, the nudges are happening in the most efficient way to ensure projects are on track? How do we surface problems sooner so that leadership is not waiting for someone to raise the hand and say, hey, I have a problem in this account? Which, you know, doesn't happen often. People try to be the hero and solve the problem on their own. But if a system says, hey, there is a problem here, leader, you need to pay attention. And this can be, hey, you're burning budget on this project faster than you should. It could be there is a schedule or timeline issue with this onboarding. It could be a scope issue where once you start onboarding, sometimes customers start giving you more and more requirements that need to be fulfilled and that process doesn't stop. It could be customer sentiment issues that implementation manager, onboarding manager may not even be aware of that know they're not being perceived as being on top of things or they're not being perceived as giving a great experience to the customer. But if the system detects this, pushes the information to the leader to say, hey, we need your intervention here, let's escalate the partnership quickly and solve problems. That's a huge area where I think AI and automation can play a big role in bringing those early warnings and, you know, governance automations into play. Yeah. There's also a lot of work that happens in any implementation project. Right. So you're looking at people getting on tons of meetings, creating documents after those meetings, crafting Various kinds of deliverables, configuring systems based on what solutions were agreed upon, communicating constantly to the customer as we're saying, hey, here's the progress we've made, here's what's coming up next, here's what we need from you. And I think there's a lot of scope for what AI is able to do in all of these areas. It used to be, till a few months ago I would have said there is certain areas where AI can play a role, which is more the repeat tasks, the mundane, etc. But now it feels like AI can play a role even in the most intelligent task that you need to do, where you can partner with an agent to do that work. And that's what we are enabling, right? We are bringing this sort of AI workforce for implementation teams, PS teams for being co workers alongside your team to get part of the work done. Starting with, I would say the biggest thing we've done we launched so far is like a AI scribe that is listening into the calls that you're on with customers. And there's a lot of post call busy work, whether it's creating a document, drafting an email, et cetera. And what you need to pull from different kinds of meetings is different requirements meeting versus a solutioning meeting versus a pre go live meeting. The takeaways, the granularity at which you need to document things, what you need to send as an email, all of that is different. And we are allowing people to use that level of templating to say, here's what I need to glean from different kinds of calls. Automate that whole process.
Greg Kilstrom
Well, yeah, and a key part of that is you mentioned like the partnership or the working alongside. So it's not AI completely replaced. I think it's AI may be replacing some of the parts of the work that humans don't do well or it's inefficient for them to do. But there's this partnership component which can do a lot of things, a lot of good things. But one of those is just helping operations to scale. Right. So I mean when you have AI that is able to do that, but also keeping humans in the loop, you're able to kind of balance the two. Right? You, you kind of get the best of both worlds. Can you, can you talk a little bit about, you know, how, how you've seen that done well, you know, do streamlining and optimizing without losing the good human, you know, human part of that?
Sri Krishnan Ganesan
Yeah, I think humans bring the deep context and knowledge that is needed to do a job. And when they're able to share that knowledge with AI, when they're able to document more, when they're able to teach AI more, I think it's able to pick on more of the work that you need to do. At the same time, you're able to be that human in the loop that's checking, verifying, hey, did, did AI get it right? Thereby, in a way, shrinking timelines, right? Because the same work for a human to do versus for an agent to do, an AI agent to do, probably the AI agent will do things faster. And that gives you the opportunity to say, okay, let me review what's been done, let me iterate on it. Sometimes, maybe you need to iterate on it a few times to get it right, but once you start getting it right, once you start figuring out, hey, here's how I need to automate this part of the work here is how I'm going to teach AI to do this role better, then it's going to take away from it and really start doing a better job from the next time. And I think that partnership where human is playing the role of I'm checking, I'm teaching, I'm documenting, and then AI is speaking on the actual doing of the work is a good partnership. And I don't think this stops in saying, okay, now AI knows everything. It's always there's opportunity for incremental, how can we do things better? So I think the more we as humans learn to learn how best to work with AI, are all of our team members trying out new things? Are all of our team members learning how to prompt better, learning how to provide better context, learning how to build new systems using all of the new tools that are coming out in the market. I think that's going to lead to more innovation, more, I would say, crunching off timelines to deliver on something for a customer and thereby I think better results for the company. Because what we've seen is when you get to that radical efficiency, when you start shrinking timelines for the customer, the appetite for the work that you're doing goes up. So it's not necessary that here's the pie of work and part of it is done by AI, part of it done by humans. So number of humans needed is less. Instead the spy of work itself is going to grow. Because if you, if you say the cost of doing this work is lesser or the time that you need to, you know, deliver on this project became one third, there's so many more companies that are going to say, hey, I want this too, because you're able to deliver fast, my risk is reduced. I have the appetite for this project now. Yeah, yeah.
Greg Kilstrom
What, what maybe hurdles or even misconceptions. Do you see that? I mean, because, you know, I, I think what you're saying makes, makes a ton of sense. And I think, you know, those that are keeping up with this have probably, you know, are probably on the same page. But yet, you know, they run into hurdles or they, they, they may come into things with the wrong, the wrong ideas or assumptions. You know, what, what would you say to those leaders that, you know, what should they keep in mind that maybe others get wrong at first?
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Sri Krishnan Ganesan
I think a few things I would say one is if, if there is an enterprise wide system and you're constrained by hey that's the only system you should use, then you're probably playing it wrong. You need to battle it out with your IT leadership or whoever to get like a wider playground of tools that you can use. And because I think the strengths of different tools are different and you want to be experimenting with what's out there to see where you can optimize. The second thing I would say is enable your team to run any number of experiments, right? I think if we sequence things the way we used to saying okay, let's pick only this project versus that for this quarter we do only two projects, then I think you're denying yourself the opportunity to learn at a faster pace and evolve as an organization, enable more people to experiment and have clear ways of measuring what's working, what's not. And I would say where it makes sense. Even carve out time for some of the team members who show a lot of inclination towards trying out and testing out new tools and who are good with that sort of thing. Right. So I think if you're always fighting for time, if you're always on the back foot with customers, you're not able to make time for something like this, then maybe even hire an extra individual to take on this sort of effort of putting in AI and automation for the team or borrow a resource from like your IT organization internally to get that going. I would say, you know, people place where people typically I would say go wrong is they're not thinking big enough, they're not thinking, they're thinking more small, incremental things versus how do I create radical efficiency? How do I automate 70% of the work we're doing? That should be the goal. And then when you start thinking with that lens, I think you will find ways to do that if you're constrained, constraining yourself with, okay, here's the mundane repeatable work. Let me automate what is low hanging fruit. Then you'll never get to greatness in what you want to, what you can achieve with the AI.
Greg Kilstrom
Yeah, yeah. So what would you recommend as far as, like, how do you measure the, you know, how do you measure success here? Like what's the, either the metrics or how should leaders be looking at roi? When, when we were talking about, I mean a lot of this is, is better collaboration better, you know, whether it's onboarding, project delivery, all of that kind of stuff. Like what's a, what's a good way to think about measurement? And in that.
Sri Krishnan Ganesan
Yeah, the way I would look at it is one, the obvious one is time saving, right. Like document how much time it took to do something manually. And now with AI, how you're able to shrink that effort that's spent. Two is duration shrinkage. So time saving is like the effort saved. Hey, it took someone three hours versus now it's done in five minutes. The other part, duration is more of. It took us three weeks to do this versus now it's happening in one week. Like overall project timeline shrinkage. The other aspect I would say is what are the things that you weren't able to do that you're now able to do or you were doing it only for, let's say for onboarding a team. I mean, for an onboarding team, if you were running projects a certain way, checking things a certain way for your top five projects, but you weren't able to have the bandwidth to do that for the next hundred, are you with AI able to do things that you weren't enabled to do before? And what is the impact of that? Right? If I have the right governance for all my projects, then does that increase on time delivery by X percentage? Does it increase customer satisfaction by X percentage? So those are the things you may want to measure.
Greg Kilstrom
Got it, Got it. Well, thanks so much for joining today. As we wrap up here, I've got one last question for you that I like to ask everybody here. What do you do to stay agile in your role and how do you find a way to do it consistently?
Sri Krishnan Ganesan
I think for me it's about connecting with other founders. Sometimes founders who are at around the same, you know, revenue scale org scale as us. Sometimes it's founders that have seen a different scale already and sometimes it's also founders who aren't at your scale yet but are doing things differently. I, you know, look, look at I follow a bunch of people on LinkedIn, but I also try to connect, live wherever possible, meet people in person and learn from their experiences. What do I want to borrow as an idea that someone else is doing well and then take it to our org? I also consider a few people as mentors, so I do connect with some of them from time to time to share what I'm up to, have them challenge me a little about how we are doing things and see where we can get better.
Greg Kilstrom
Yeah, love it. Well again I'd like to thank Sri Krishna Ganesan, co founder and CEO of Rocket Lane, for joining the show. You can learn more about Sri Krishnan and Rocket Lane by following the links in the show notes.
Sri Krishnan Ganesan
Thanks Rick.
Greg Kilstrom
Thanks again for listening to the B2B Agility podcast. If you enjoyed the show, please take a minute to subscribe. Subscribe and leave us a rating so that others can find the show more easily. You can access more episodes of the show at www.b2bagility.com. That's B2B agility.com while you're there, check out my series of best selling agile brand guides covering a wide variety of marketing technology topics. Or you can search for Greg Kilstrom on Amazon. Until next time, stay focused and stay agile.
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Podcast Title: B2B Agility™ with Greg Kihlström
Host: Greg Kilstrom
Guest: Srikrishnan Ganesan, Founder and CEO of Rocketlane
Release Date: June 3, 2025
In Episode #46 of B2B Agility™, Greg Kilstrom delves into the critical topic of customer onboarding and operations within the B2B landscape. Joining him is Srikrishnan Ganesan, the Founder and CEO of Rocketlane, a platform revolutionizing customer onboarding and project delivery through AI-driven tools and automation. The discussion centers around how AI can transform onboarding processes, enhance operational efficiency, and drive customer retention.
Greg Kilstrom opens the conversation by highlighting the common pitfalls in customer onboarding—delays, confusion, and misalignment that can derail new client relationships. He poses the central question: "Why is onboarding still broken in so many organizations and how is AI finally changing that?"
Srikrishnan Ganesan responds by reflecting on his journey with Rocketlane, emphasizing that effective onboarding is pivotal in solidifying customer partnerships. He states:
"Implementation or onboarding is the second sale you're doing. You're selling the partnership experience, saying, 'Here's how it feels to work with our company.'"
[03:27] Srikrishnan Ganesan
He underscores the importance of moving beyond traditional tools like spreadsheets and fragmented project management systems to adopt an all-in-one solution tailored for onboarding and professional services teams.
The conversation shifts to how AI and automation are pivotal in redefining onboarding processes. Greg asks about the specific impacts of AI on implementation speed and retention rates.
Srikrishnan Ganesan elaborates on various applications of AI within onboarding:
"How do we ensure that follow-ups and nudges are happening in the most efficient way to keep projects on track?"
[06:39] Srikrishnan Ganesan
He highlights AI's capability to provide proactive alerts and governance automations, enabling leadership to address issues promptly—ranging from budget overruns to scope creep and customer sentiment problems. Additionally, he introduces Rocketlane's AI scribe, which automates post-call tasks such as drafting emails and creating documentation based on different types of meetings.
A key topic is the partnership between human teams and AI. Greg emphasizes the importance of not losing the human element while scaling operations.
Srikrishnan Ganesan agrees, stating:
"Humans bring the deep context and knowledge needed to do a job. When they share that with AI, they enable the AI to take on more of the work."
[10:32] Srikrishnan Ganesan
He explains that AI can handle repetitive and time-consuming tasks, allowing humans to focus on verification, teaching the AI, and iterating processes. This collaboration leads to radical efficiency, where project timelines are significantly reduced, thereby increasing the capacity to take on more clients without compromising quality.
Greg inquires about common hurdles and misconceptions leaders face when integrating AI into onboarding processes.
Srikrishnan Ganesan offers strategic advice:
"If you're constrained by enterprise-wide systems dictating the only tools you can use, you're likely limiting your potential. Experiment with a wider range of tools to find optimal solutions."
[14:57] Srikrishnan Ganesan
He advocates for fostering a culture of experimentation within teams, enabling multiple projects to adopt AI and automation simultaneously. Additionally, he suggests allocating resources or hiring dedicated personnel to spearhead AI initiatives, ensuring that the organization can pursue radical efficiency rather than settling for small, incremental improvements.
The discussion turns to metrics and ROI for AI-enhanced onboarding.
Srikrishnan Ganesan outlines key performance indicators:
Time Saving:
"Document how much time it took to do something manually versus with AI."
[17:37]
Duration Shrinkage:
"Compare the overall project timelines before and after AI implementation."
[17:37]
Increased Capacity:
"Evaluate the additional projects or clients you can handle due to increased efficiency."
[17:37]
Customer Satisfaction:
"Measure improvements in customer satisfaction scores as a result of streamlined onboarding processes."
[17:37]
These metrics provide a comprehensive view of how AI contributes to both operational efficiency and enhanced customer experiences.
As the episode concludes, Greg asks Srikrishnan about maintaining agility in his role.
Srikrishnan Ganesan shares his approach:
"Connecting with other founders, learning from their experiences, and continuously experimenting with new tools are key to staying agile."
[19:07] Srikrishnan Ganesan
He emphasizes the value of mentorship and collaborative learning, which help him and his team stay ahead in a rapidly evolving technological landscape.
Episode #46 of B2B Agility™ offers insightful perspectives on leveraging AI to transform customer onboarding and operations. Srikrishnan Ganesan of Rocketlane provides practical strategies for integrating AI into onboarding processes, balancing human expertise with technological efficiency, and measuring success through clear metrics. This episode serves as a valuable resource for B2B marketers and leaders seeking to enhance their onboarding strategies and drive business growth through innovation.
For more insights and episodes, visit www.b2bagility.com.