Jamie Davidson 0:02
Maybe back in like 2015, you didn't even think about hiring a dedicated customer service manager until like Series B or something like that. It was just not something that you did. And that's gradually gotten earlier and earlier as the years have passed, and now we've we've had customers on on Vitally using Vinally without actually paying customers.
Taylor Kenerson 0:23
Welcome to the Hyperengage podcast. We are so happy to have you along our journey. Here, we uncover bits of knowledge from some of the greatest minds in tech. We unearth, the hows, whys, and whats that drive the tech of today. Welcome to the movement.
Adil Saleh 0:42
Hey, greetings, everybody. This is Adil from Hyperengage podcast, I have my co host Taylor kenerson. And a really special guest, Jamie from Vitally he's the CEO and co founder of Vitally, I would say it's one of the emerging platforms in the recent era, more towards customer success team, their productivity, for the reporting visibility, we're going to be exploring more of on to where they're heading these days. And, you know, first of all, thank you very much, Jamie, for taking the time.
Jamie Davidson 1:11
Thank you for having me.
Adil Saleh 1:13
love that. Okay, so Jimmy, I was just looking deep in to where you came from, like you were more of a technical software engineer, like from an engineering background, and you sort of transitioned into customer facing role that leadership role as a customer, you know, Chief Customer Officer, one of the sales platforms, and in the past, and now finding the scene at widely back in 2017, slash 18. Could you walk us through your entire journey, especially the mindshare, because engineering, and then, you know, customer facing and then building a platform for customer facing teams, specifically for success teams?
Jamie Davidson 1:54
Yeah, for sure. I'd like to think I'm one of probably single digit numbers of people in the world that have done both CTO and Chief Customer Officer, it's not a conventional journey. I've been the CTO of two companies before this one of those I was a co founder up. And three years into my last startup, where a CTO, I basically literally walked in one day CTO, Walker Chief Customer Officer, the long story short, was that we just had a lot of things needed to be solved. On the personal side of the business, we were pretty small company at the time, I think we were like, like 25 people. And I, you know, my engineering skills, I think, have made me a pretty good problem solver. And so even though it was not a problem I was overly familiar with, it was a problem I thought I could solve. And so you know, me, I also thought as like my job is like, co founder, like, there's only two co founders of the company, it's my job as governor to solve any problem, not just you know, ones that work directly underneath, like the technical the product umbrella. And so I kind of decided to jump into it and practically solve the problem myself, I appointed myself to Customer Officer at that company. And yeah, rebuilt customer success from scratch the next day, which was an interesting undertaking for sure, we were a big, we sold like a big enterprises like pretty much the fortune 500 exclusively. And, you know, building customer success for like, the literally the largest company in the world, like Walmart was a customer of ours was, you know, it was going to take him but it you know, got me introduced to customers and stuff, but problems that customer success has to solve. And also, of course, the landscape for software out there to help customer success, that landscape was different in 2016 than it is now. But as you know, 16, I thought it was pretty bare. There were only a handful of players in the space. I didn't think that the players really nailed the platform, the especially with my technical mindset, like I was wearing more clothes more opinionated about like product analytics, and either from rotations and better UI and UX and these things that like I wasn't seeing from the market. And so at some point, I was like, I can raise the bar here, I can build a better platform. And after nine months of being Yeah, the the chief customer officer, that last startup I left started Vitally, and here we are.
Adil Saleh 4:17
Wonderful, very inspiring. And I like the fact that you mentioned about the problem solving. And a lot of these specialty CEOs that we get to meet they are more towards, you know, the marketing side business operations. All of these co founders and CEOs have more from the technical side. But again, as opposed to someone that is not so technical, on the ground level, because at the end of the day in the SAS world in a subscription based economy, you gotta make sure how you're solving problems via technology, and giving it a SAS experience and read there. It gives you an edge if you have an engineering background. And a lot of these Y Combinator startups that we get to meet their most of their founding teams are technical they always prefer because so they have an ability to do to iterate and pivot in quick succession having someone on the leader support that technical. So now talking but slightly about your journey and writing, like how you guys initiated they were tools like wildly against it more so than towards enterprise, these legacy, you know, I would say, customer segment, you can say enterprise large scale enterprise. And then there were some clients success, some in the SMB and mid market segment as well. So, how do you guys think from a business standpoint? You know, positioning your product once you figured out okay, this is the problem, the gap that we have faced, that we have navigated there's a good addressable market. So how are we going to position it, so just talk us through that part of your journey?
Jamie Davidson 5:45
I mean, it's evolved. Yeah, for sure. I'm it's evolved a lot over the years. When we first got started, like, we were really laser focused on solving kind of the product analytics side of the business, but certainly is biased by my CTO experience. And the actual, which very few people know, the actual first iteration of the Vitally platform was actually product analytics for customer success. It wasn't a full fledged, like customer success platform. It was purely aimed at like providing customer service, even better insights into how customers were using the product. We launched it in like a private like beta with some early kind of customers and learn that it was solving a problem but not a compelling enough problem, to warn people to actually pay you money. And so we really needed to bake it into a larger customer success platform that could provide all the capabilities that customer service teams need, specifically around like, acting on that data. So like taking those creating tasks to like be proactive about the the insights that we were providing, we were kind of relying on them to like go and use other tools like you learn from our data. But you'll have to take action elsewhere, we need to figure out a way to kind of bring that together. And so we kind of got our first scenario, our first iteration was a customer service platform that was very focused on product analytics and product insights. That's of course evolved over the years that was kind of next, that evolved into a customer success platform that was very focused on helping teams provide scale customer success, because that was a newer is a newer iteration of customer success. From the traditional, like, high touch white glove, customer stuff model, and the incumbents, the customer has platforms like kinda, you know, the original players in the space, that model didn't exist when they got started. And so they kind of had to try to back into it. And we were able to get the timing right, of focusing on scale customer success through advanced automation, to really scale us into where we're at now. And now we're at another point where we are evolving the messaging, evolving the positioning, to take a more of an aim at Federation, project management help businesses get more work done in our platform, which I'm happy to talk more about. If you want to lead me into that.
Adil Saleh 8:17
Yes, yes, absolutely. We'll definitely talk about the stack, how you're basically helping SMB mid market, even enterprise with the Lifecycle Management post sales lifecycle entire entirely for the hats, like leaders, leadership, even heads and VPs, more than boarding side, and then Customer Success teams with with, you know, making sure they do more with less. And they had all of their organization pretty much optimized, and then the ops team, that's going to be the big as well, because we've been talking to a lot of your customers too. And we've explored this, some of them are challenges, some of them are something that they're doing pretty seamless. And that is helping them get delivered that the value out of the product. So we'll we'll jump in deep on that, too. Now, so talking about the initial journey, product validation, that's fine, you hand it over to some of the customers that give you the feedback, you then realize, okay, there's still a gap, we need to make sure that we don't make our customers to use like three or four different Tech Tech stacks on one prong, why don't we just live in their systems, and then try some of the solutions that actually fit in with their workflows. So what kind of solutions that we thought are one is product analytics, that's fine. When it comes to data point set on the billing side, you know, one of one of these economic events like Retention and Expansion, you know, that happened in the Customer Success lifecycle. So how did you guys realize that, okay, we need to make sure we give some sort of billing metrics, analytics of the billing side as well as the communication site when it comes to the CRM and analytics. A lot of customers are using Salesforce as a CRM. So they have the customer objects and all they all want it inside the customer success platform that you used for the customer process or person, so they wanted a source of truth for them. So how do we do guys? At what point did you guys realized that this is the solution? We need to make sure the end of it?
Jamie Davidson 10:11
Yeah, it I mean, a lot of was just talking to customers early on, but it was also a lot of it kind of educated by our, like renewed focus towards scale customer success a few years into our journey, because like looking at like the, you know, anybody doing scale customer success is like, typically a high growth b2b SaaS company. And the tech stack of those, at least when it comes to revenue, and communications and things like that, it's pretty standard, you know, especially back in like, 2018, it was Stripe, we're currently Aarthi. And that was maybe it. And, again, like the the narrative we kept hearing from customer success was, we need to bring everything into one place, like we need to be efficient, we need to be proactive with our customers. And the more that we have to go and bounce into another tab into another platform to get a sense of who's the customers next renewal and what's you know, the potential like contract value of that renewal, or having to balance it's like an intercom, like, what was the last time I talked to the customer, the harder we were making the job of a customer service manager. And so we kind of sat down and tried to map out, we didn't look at it from like a tool a perspective, we looked at it from like a data set perspective, like what are the key datasets, customer says needs to understand the customer, we broke that down into like, product analytics, communications, revenue, information, CRM data, and then like, general feedback, so like NPS data surveys, feedback, maybe from the CSM, and whatnot. So those kind of five categories are still kind of the guiding principles for us today. And whenever we look at like expanding and building a new integration, we basically say which one of the five categories and datasets that we're trying to bring into the platform does it fit into, and if it doesn't fit into that workhorse of mind, and and what's for like adding the integration, but we're still pretty, you know, we're pretty adamant like those are the top five is the key data sets, you need to understand as a customer success manager, and it's our job to pull all that data into one place so that you can just continue to be as productive as possible.
Adil Saleh 12:22
Hmm, very interesting. Very interesting. So talking about a bit on the on the product side, let's say you have like on one side, we get to meet a lot of startups that think that they need to do a lot of change money, when it comes to incorporating it to like wildly to tango, find success, you know, again, sided, don't look too much about it. Because that's more on the enterprise side. So how do you see it as from a view of a startup because they want to grow their customer, they want to unlock the growth, expanding customer, make sure they increase the lifetime value of the customer. That's the biggest challenge that they come up with in the first one to one and a half to two years. At the same time, they're choosing product market fit. So they need to make sure all the installed base that they have the expanded retain it and expand it. So how do you see it fits in the view of startup, high growth startup, you can see it starting precede not precede C or SUSE? Let's talk about that.
Jamie Davidson 13:22
Yes, it's a great question. I mean, customer success has kind of evolved in the ways that the platform's have evolved it. And by that, I mean, it may be back in like 2015, you didn't even think about hiring a dedicated customer service manager until like Series B or something like that. Like it was just not something that you did, and that's gradually gotten earlier and earlier, as the years have passed. And now we've we've had customers on on vitally using finally, without actually ending paying customers, which would have been unheard of five years ago for a customer service platform for like, you know, have a customer that doesn't have paying customers. What was the point? Well, the point is to just understand your customers from day one, well, I used to term customers to kind of lightly your users from from day one. And but you know, even in 2000, like PathGather, for example, in my last company where a few Customer Officer, we were series A we were 25 people when I went to look at the market for customer service platforms, and there wasn't an option for us, because everyone was telling us it was going to take minimum three, maybe up to nine months to get the product implemented. And that time the value was insane. For me, I was like I have a customer service team starting next week, like I need provide value and a platform for them, like next week, and I can't write you, you know, 10s of $1,000 a check to like hope that I'm gonna get value and like, the next year. And so, you know, Customer Success teams that are now at early stage companies back into the changes were kind of like us so it did have an option. we started from day one, kind of, you know, saying we're gonna we're gonna sell early stage company, we're going to be the first customer SAS platform that you can use for ECC series A a stage. And we built like our integrations, we build everything. With that in mind, we were even selfserv. Like, you could go and go to Vitally.io
, start a free trial, put in a credit card and pay like three years ago, we've strategically put it down since for valid reasons, but we built the products so that you could implement and onboard yourself and get your, you know, provide value to your FCS team, you know, as soon as it's humanly possible within minutes and not months. And it's been good to see kind of the evolution of that over the years, like, we've certainly have some competitors that have done a good job of also lowering that onboarding implementation timeframe. But the change management isn't such a huge undertaking, so that a C stage customer success team can actually choose a tool that exists a platform, and providing, you know, it will take it on with minimal sort of like effort, minimal change management. And it's been good to see kind of like Customer Success evolve in that way as well, where it's being, you know, implemented earlier and earlier. Companies.
Taylor Kenerson 16:22
I'm, I'm super glad you jumped into that, Jamie, it's really important that you know, you as a startup, you don't have to be funded or have that accelerated growth to begin thinking about customer success, just like you said, it starts at day one. So let's paint a like a picture for startups. When you're just starting off, maybe you have a few like a few people on your team, what are some of these elements or tools and tactics that you could begin to implement? Or think about that you can reach that scaled ces model when you're, you know, your product is aligned with that, but what are some of this? What are some of these tools and tactics that you need to think about really early on to set yourself up for this, you know, better future?
Jamie Davidson 17:05
Data, cleanliness is like the first thing that comes to mind. Because that's the hardest thing to fix. Later on. It's like, you just have data scattered all over the place. And you're not like really consistently sharing like unique identifiers about who your customers are, and all these places. And like, there's like one weird representation of the customer in the CRM that doesn't align with what the product analytics tool has, and whatnot, you're only going to make it tougher to take on a tool later on that helps you organize your customer data set and database and understand your customers in depth. And thankfully, there has been, you know, advancements in tooling to really help with that with data warehouses becoming more popular and reverse ETL is helping you get data in various systems and whatnot. So I mean, I think just having a very clear understanding and opinionated, like, kind of just an opinion about this is what a customer looks like to us, here's how we're going to identify the customer moving forward, and just being responsible with how you rack that customer in your various systems is going to just make future decisions, future tooling choices easier. The, you know, the earlier, you can just have a centralized understanding of the customer, the better. It doesn't have to be a customer set platform, you can invest in your CRM early on and ensure that like the CRM has as much understanding of the customer as possible. But you know, if you're going if you're, you know, you're scanning your data and all these tools, and you're requiring your CEO to go and bounce around these tools, you're making them that person, you know, less productive. And so ensuring that you have some understanding of that is important, from like an early stage tooling perspective. Like there's, you know, I think probably most teams these days are probably starting with like some work OS kind of like platform that exists. And I think it's definitely the right way to go like a notion or click up or a Monday or something like that. And, you know, sort of done interesting things to try to get some customer data into the platform to help educate teams that are trying to work more proactively on top of the customer. But it's kind of not a great, it's a lot of us manually copying and pasting the data around. Yeah. And that's that leads that leads us to where we're at now is we're trying to kind of bring the Bork OS kind of mentalities into Vitally so that you can work backed by that unified data set better.
Adil Saleh 19:36
Absolutely. Just one thing before you jump in so now the biggest thing also why they need a bigger change management two years down the road, incorporating tools like Atlas widely, all these tools that do whatever they see fit, because they've been not investing into data. Since day one. We spoke to team at Gong, senior leadership this at six years back, we were way more smaller than what we are now, even then we have same operating principles in terms of product stack, leadership, all of these, and we are investing into data at all levels. So that's why we also need to, you know, think that why, why these startups growing up need chain management, the the need to connect the data team with the catalyst, right, these team and do the onboarding for three, six long months, because they have been not monitoring the product activities, user activities, they've not been staying on top of data, that data is not centralized, as we talk about data Centricity that and it comes down and as you mentioned, which is quite right, that you need to do it right in the first place, because it gets harder as you grow.
Jamie Davidson 20:46
Yeah, you're definitely you asked about like your technical founders and non technical founders, like technical founders typically will have an eye for this problem early on and put in the best practices and the protections in place to limit the data sort of messiness issue that exists like later on non technical founders are the ones that like, an often overlooked the importance of this and just kind of like, put it in the backburner, like, we'll figure it out later. And I mean, I get that because, you know, early stage company just want to generate revenue and get as much customers as possible. But you also have to understand and think about like, Well, what happens if you do succeed? Because you know, things get more and more complicated. And if you do succeed, I understand the reason I understand being like, well, it's a problem for later that we'll solve later, it's only going to be it's not that what's once not that complicated to solve it early on. And to it's going to be way more complicated to solve it, the bigger your dataset gets. And, yes, and so it's, it's make sense to invest in it early on.
Taylor Kenerson 21:50
I mean, and at the core of it, and makes sense to you, as a you, as a founder of any company, you have to do multiple things almost at once, you have to push multiple balls at almost the same time. If you're, you know, so worried about building your team, scaling your team getting product market fit, and you're not focused on all of the insights in the data that you're collecting through those conversations and how you're organizing that, how you're mapping it, how it's translating into making decisions, like you need to early on the earlier the better start understanding how much data and these insights can play a role in guiding your product and guiding where you're going if you actually put value on where this what this data can do. So kind of diving a little bit into, you know, some that you recently got funded, amazing. Congratulations. But diving into a little bit of these investor conversations, as a startup, you know, a startup founder, how do you help? Maybe the non technical founders realize this value that data Centricity data insights can play in the longer term goal of your company?
Jamie Davidson 22:56
Mmm, that's a great question. I mean, you can tie it back to venture like, I mean, most companies these days are not bootstrapped. They are venture backed, I mean, maybe a little less so in this trying marketized at the moment, but you know, like, if you do have an aim to, let's say that your non technical founder and you think more along the lines of dollars versus data, eventually, you're probably going to want to raise a large round of funding. Any mature venture firm is going to want to dig into your data. And if you send them a data room that is messy, that shows a lack of sophistication on your APIs and your metrics, if you aren't able to, you know, adequately answer questions about, you know, the actual problem you're solving for customers, and do you have data that showcases the value in writing your customers, you're not going to get funded by the very least like a tier one or tier two investor, you might be able to get offended somebody on the vision themselves, but you're not convinced like the heavy hitters and venture to fund you if you don't show some sophistication on on data understanding and data maturity. And so, you know, if you really want to, you know, if you're not technical founder, you want to put $1. to it. It's just from that perspective, it's, again, it's the problem only gets more complicated to solve, the longer you go, and the more the more customers you get. And venture is going to be able to understand if you've given it adequate thought and and it's been able to adequately hire because again, the role of CEO is to also hire for weaknesses and gaps that you have. If you haven't, given a venture firm the confidence that you're seeing these gaps and you're able to, you know, hire people for those gaps. You're going to struggle with funding for sure.
Taylor Kenerson 24:48
And that's, I love how you said, data to dollars. Jamie, that's really critical. I mean, as an early founder, maybe sometimes you're not thinking of this data as it eventually translating to dollars. If you build that strong foundation, then the rest of the house can kind of be built properly. On one, one end, while you're, you know, at the from day one, you're almost collecting data, whether you're having conversations with friends or potential customers. So all of these insights and data need to be organized and manage and properly leveraged to guide where you're gonna go in the future. And you're gonna get tested on that in the future, whether that's by investors or potential team members that you're trying to recruit. And that's a really key element to, you know, getting ahead and thinking almost scaled CS from the very early days.
Jamie Davidson 25:37
Taylor Kenerson 25:39
So let's dive a little bit into, you know, the post sales journey of Vitally. What is what are some of the onboarding processes and systems look like? Especially when it comes to, you know, we talk so much about data and information getting lost in translation, through the handoff of, you know, the CES operations and the function? So can you walk us through a little bit about what the post sales journey looks like in that onboarding process, some of the tools, especially for
Adil Saleh 26:06
especially for these customer success leaders, because I'm sure you have segments, you know, it's pretty critical for the heads and VPs to you know, first know what kind of data points they need to integrate from the product side like segment Mixpanel, amplitude, all of these then from the CRM side, as well as connecting with with the data ops team. How does the onboarding look like for customers?
Jamie Davidson 26:30
Yeah. We're onboarding as new customer to us are onboarding in our platform itself. An onboarding to platform onboarding? Oh, yes. Actual new customers of ours? Yes. Okay. Cool. Yeah, I was about to ask you to have that answered more generically. I, so step one for any CS leader is definitely to understand how to get access to the data to the tools that you need to plug into a unified data store, which is, you know, what we are at his earliest stages, just a unified dataset, of course, there's a lot more complexity a lot more to it than that. So step one is just getting the data into one place. A CS leader needs to understand, you know, what are they have access to what are they not have access to? How do they align resources to the CRM to the communications tool to the revenue tools to you know, be able to hook up the integrations to the things, of course, GDPR has complicated things a lot these days. And so you also have to ensure that you go through the responsible process of, you know, adding us or whatever tool you're using as like a sub processor, and ensuring you're talking to legal, it's, it's good that we're all getting better on privacy. But you know, as a business leader, it's also a little frustrating that it complicates the onboarding process to get up and running from from that perspective, but they just need to ensure that they're talking to their individual tool admins, and to their you know, privacy, security, legal things, whatever it is, around getting data into one system from another system. But everything's pretty at that point least in our platform was pretty plug and play like you know, you can put a few switches map a few data points together and then the data is like organizing and unifying it and Vitally in your in your kind of off to the races from from there, which give it you know, once the data is in Vitaliy, we pivot then to helping ensure that you get as quick a value on back of that data as possible. Because, you know, we are, you know, this is where we differ from pretty much, you know, product analytics tools, even from CRM, and like, our mission is not only to give you the data, but is to help you take the right actions on top of that data. And to try to, you know, ensure ces leaders understand what are some of those initial quick wins, they can get to be proactive backed by that data is important for our we have like an implementation specialist that do this. It's important for them to kind of showcase like, you know, maybe here's a key insight that you don't understand that you didn't know about your customers that brings two datasets together and provides all into like one dashboard, where it's an automated workflow, you can implement switches, that allows you to save a couple of hours a week of manual work now you can just automate it entirely. And so we really try to find this because when early on, yeah, there's a lot more to it than that. But
Adil Saleh 29:20
yes, I certainly know there's lot more. So now, I mean, you know, kind of connecting it back to the Startup motion. Like they're monitoring the product and index for short. A lot of them be technical, non technical. They are recording the data and the CRM, they're recording the data using Stripe and all these payment gateways. So the biggest problem for them is once they are trying to hire the first customer facing team member, initially, they can do it in first six months, even if they are bootstrapping. So the biggest challenge for them is not making sure that they are already recording. Make sure that data is driving action for the customer. It is is translatable? It is in one place translatable, and that is driving corrective actions, that of course that drive conversations, communications. So how do you see it happening in a startup motion? These all of this integration, like is it a best, best fit, when it comes to wildly? I see contango Gainsight a lot of these platforms, they're not so great and they don't prefer. So I'm just trying to explore why not writing. So they have a customer facing team, they're serving 150 200 customers in the first year. And now they have all the tools that you integrate them, and they can, you can absolutely unify all of that data. GDPR compliance, that's not going to be so big a problem, I'm sure with the startups, they don't ask you to have a sock to compliance or all of that. So they get their shit in one place, and they can do the corrective action. So how do you see startup motion?
Jamie Davidson 30:57
So how do I see why a new startup motion 5200. I see. Um, I mean, the initial there's, there's, there's certainly two, you know, large cat like to kind of broad ranging category. So the value we're going to provide, sort of, but also anybody in general, and that's when a better understanding of your customers so that you can better, you know, just ensure that you're implementing the right methods, methodologies with them, having more educated meetings, have more educated conversations with them, but then to is just helping you be more proactive back by that that's not a problem that's unique to startups for late stage, it's something that, you know, even if you do have 50 customers, and you're trying to get to 75, better understanding those customers, and then more intelligently working on top of that data is important to do, even if you don't have a dedicated customer success team, like the CEOs, probably typically handling a lot of the customer conditions early on, and they're going to want to be more productive with that, of course, you know, early on, and at an early stage company, you've certainly you don't want to, you can get a total overload, right, you can invest in like a lot of tools that do a lot like, you know, point solutions that do like very precise things that maybe just pasta, you know, 10s of dollars a month. And some, you know, startups may be a little hesitant take on what they would traditionally see as like a kind of a more robust, mature platform is vitally early on. That's where we are now trying to and are currently at the moment like bringing a lot of the capabilities that you're using, from your point solutions into one place. And that's our sort of like future vision is like, let's, let's, you know, if you're using a little solution just to help onboard customers, like the first couple of months, let's look at that functionality. Let's figure out how we get it into Vitally. So that the narrative, the journey is as pleasing as possible. And as starts that data like tracking and the actions that you're doing started early on in one platform, and you can evolve the customer relationship in that platform as well. And so for a startup, it's a you know, our pitch is often consolidating your tools and consolidating the things that you're using into one place, because we do very much provide you a lot of those capabilities that these individual points solutions are doing. And the benefit is, it's all sinking back into one centralized data source, what's the profile of the customer?
Adil Saleh 33:30
Now, because I mean, at the end of the day, even as a startup, you want your customers to be wildly successful. And that's not possible without sitting on top of the data points sitting on top of their behaviors, pet rooms, and then making, you know, making these decisions, conversations and engagements, all of that. So it's super important. So I recently got a news from my team that you recently pivoted around. Documentation is like more on the collaboration side as well. So could you tell us why did you make this what was the core reason behind that pivot and riggers added now as a product, and then touch about January they are because there's a lot going on like teams like Salesforce Grammarly all these folks standing up after the chipping GPT For update. So yeah.
Jamie Davidson 34:18
So for sure, I mean, sort of transparently the main instigation for the pivot and I you put an air quotes because if you let people say pivots are bad, but for us, it's like more of a refocusing, I guess, was actually my plans to raise our series B. Which initially started, you know, I started planning on that runway April of last year. But in doing that, like I knew, I need to be a bigger round because we just raised a Series A from Andreessen, like one of the best investors in the world and we needed to make a splash with our series B and ensure that we We're also you know, keeping up with competition and all that. But you know, had to sit down and ask like, well, what does adventure what would compel venture to do a series B, especially at that point, like, you know, we're looking at, potentially, like, there's rumblings of a recession rumblings of the downturn, and then that came through natural reality, like literally just like six weeks later. But I knew that it was like, it needed to be a compelling narrative. And I'd always kind of, you know, I always kind of thought, eventually, Vitally would, would would bring a lot of these point solutions together into one platform, but I didn't really have a great unifying narrative around what it would be like it was just kind of like a thought of like, oh, there's this thing that could definitely make it into our platform, there's a thing we didn't think of, in our platform. And as we sit down and try to ask yourself the question, well, if I had to build a customer success platform in 2022, at the time, and I did not have the bias of the last six years didn't have the bias of any of the competition if I just didn't believe the competition existed, like, what would a net new customer service platform look like in 2022? And that was an interesting thought experiment. It is a tough one, because you're trying to, again, you're trying to strip away a lot of bias. But the answer was staring me in the face. Because I'm an Asana power user, I can't live without Asana, I was reviewed, I had a note that a task in my Asana to get ready for this podcast today, and my notes are gonna sign up for the podcast, I have I have, it's not attached to one of my plants, like it literally tells me what to do any given day. And I wanted to take that, that sort of like that feeling I had with like, I can't live without this tool, and baking into the platform. Eventually, in trying to figure out like, what is like, these worthless tools, sauna clickup notion are fundamentally changed. The way that people that people are working is fundamentally changing the way that teams are working is making them more productive is given this unlocking creative, like solutions and use cases that have not been able to be solved by other platforms. And I couldn't help but think that like our markets, and our competition have not, they've not kept up to that. Because the word capabilities and a traditional customer says Papa are very rigid. It's just like one line of text. And there's a check mark next to it, and you check it off, and then you go to the next thing, and you check that off. And it's not as nearly as robust as flexible, as you see from the click event in Asana. So I wanted to take a step back into like, Okay, how do I actually bring the entirety of not only the data, but the work that a team needs to do? The customer service team needs to do it into a platform. And especially if I operate under the assumption that they're using these work OS tools that are fundamental to the way that they work, or they want to see from like a customer success platform that was built with like these capabilities in mind. And I started thinking about, well, the exact mutation. For example, if you're implementing your onboarding journey in your customer success platform through automation, and through task management, you typically need a document what that is, what that onboarding journey is, for CSMs. Whenever they join your company, right? Well, you can't actually do that in your customer success platform. It's not a knowledge base center. And so you go to like a notion, and you link back to Vitaliy about, like here's what the onboarding is, go look at this playbook and vitally go look at this, like project and vitally, but you're using a different tool to curate what you're doing in a different platform. And so I was like, we can bring all this together, like we can tackle the documentation, tackle the curation, tackle the day to day strategic needs of a customer service team, just in a platform that provides them immediate access to also their customer data set. And that's an interesting, I couldn't help but think that that's probably what a 2023 version of a customer's talking looks like. And I said, you're gonna change the company to kind of bring these two worlds together. Yeah, that's right, razor. Beibei. And yeah, younger, we are.
Adil Saleh 39:00
Great, great. You know, a lot of them like, I see clan head is also trying to tap into this. And this is a big enough use case, you got to you got to work with your customers work, you got to make it all in one place, put them as much as possible. You mean as much as you can make it an ecosystem for your customers, you'll have better product stickiness. And at the end of the day, it's all about product stickiness, you you know, you kind of choose product led growth and community led growth. That's where it's heading to now. Generative AI, what's your thoughts how customer success is gonna impact with this huge turnaround? Evolution? You can say? Sure, I would say in my lifetime of 28 or nine years, I haven't seen this big of a technology initiative taken by my company. As much as I have grown and learn technology. The now what's your take on it?
Jamie Davidson 39:55
I think it will calm down. It's an initial thing. I think right now. It's super hot, right? And it's super exciting. And everybody's finding new use cases for chat GPT. And you know everything right. But I think in six months time, it will like, you'll look back on this and be like, remember when we were like, really going crazy about all these capabilities? I think that will be because one is just the way that human nature works like it'll get to be kind of old news, we'll get used to it. But do a thing on the organically baked into certain platforms, in more additive ways than ways that would replace capabilities.
Adil Saleh 40:33
And that's more of an approach like it's more of an augmented latest, like seeing just doing randomly HubSpot dating for existing customers. Yeah,
Jamie Davidson 40:43
I think it'll become for customer success. You know, I think there's there's two common applications that people ask about when it comes to this one is the augmented augmented route, which is like, how do I help my CSL teams better communicate with my customers work more strategically, intelligently and do the right things at the right times? That's a great use case, I think for for generative AI, there are the other side of it, which is one of the data sigh, which is like how do I actually use AI to tell the customer that need action that are potentially turn risk and whatnot, that's I think the riskier side an application to it. Because unless you're like a super niche, like point solution, product like they your data set, your platform gets to be so massive, so complex that like there's there's a lot of signal in that data, that is not important to like the actual customer success, almost pure logging and debugging. And it's going to take forever, for like an AI like an animal based system to really train that data set and filter out all the noise that isn't important. And so I think that's the one that's still a little unclear. But I'd like it from an augmented for, like, an additive route for customer success. But yeah, I think, you know, six months, it'll be interesting to see how platforms, you know, like us, maybe even CRM and whatnot baked into the tool. But I also do believe that it will become so ubiquitous, that teams will stop using it. Because they'll get used to, yeah, they'll get used to seeing it. And it'll, like, you know, it's kind of like, you see the same thing over and over again, and it starts to like, not be terribly helpful, you start to like, replace it, you didn't train yourself to overlook it, and to not use it, and I get the feeling that's probably going to be the case with this. And so as six months, so there's going to be a lot of offers that have invested in this. And it's probably not dramatically changing the way that the youth reps are using the product.
Adil Saleh 42:49
Yes, yes. Because everything is always always 100%. It's not 99%. So the thing that you can trust is gonna gotta be 100%. So if something that you cannot trust 100% That becomes strangers, and for your business, whereas it from the user perspective, as well, my entire team uses ChatGPT for ever since, like, we got access with up to three in the initial builders, now we got access just a few days back, dude before as well. But we still think that it's harder to train, it's humanly impossible sometimes, to train that, that big of a data set and that complex of a dataset, because patterns are different. Customers are diverse data points are diverse, they're always changing. So it's hard for a rule based algorithm to make a definition it can see
Jamie Davidson 43:38
these days are circle cyclical in nature, like it's, you know, that excitement, we get excited about it, we try to find a way to take it in there. And then at some point, we sit down, like, you know, months or years later and ask ourselves Am I actually saving time with this thing? Or am I actually spending more time like undoing and tweaking the like, you know, the starting point that this feature this capability gave me and if I am maybe I just need to go back to you know, the old fashioned way of just writing the email or writing the thing yourself. Which I wouldn't be surprised if we get to that point.
Taylor Kenerson 44:16
There is a really interesting study done recently and it was comparing the efficiency of actually using Chachi btw and then the review process like you still have to review everything it spits out and Harrison was does it isn't actually taking you more time to review it than it would have been like created it on your own. And I feel like so many people are always looking for like that quick way to just do something quick and efficient. But when you actually break it down and analyze it you might be becoming more efficient because now you're completely relying on something and you're still reviewing what you would have to review anyways, it just maybe sparking thoughts. So if you use it as a complete like tool, then I feel like that's where you're or you're missing out on like that efficiency of chunky should definitely be more of a crutch and something that you just it's an add on to the things in your everyday life. Sure.
Adil Saleh 45:11
I really appreciate it. Well, I mean, we never know. We never know what the future holds. I was looking at Yeah, whenever.
Jamie Davidson 45:16
Yeah, exactly. I could very well be wrong. Yeah, I think I think I think things will calm down. I think right now it's like, you know, it's as peak as a peak, like, you know, mania, and it's probably, but it will say, yes, yes. Okay,
Adil Saleh 45:34
Jamie, I really appreciate that you give like 15 16 minutes extra. I really appreciate that. Thank you very much for this conversation. It was genuine, practical and powerful. And I'm sure this audience, they look forward to this. As soon as it's up, we'll let you know. Until that time take care of yourself
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