Women in Customer Success Podcast

[WiCS PowerUp Masterclass S2:E2] AI as Your CS Co-Pilot: How CS Teams Are Driving Real Impact

• Marija Skobe-Pilley

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Welcome to another Women in Customer Success limited edition episode, where we bring you an exclusive PowerUp Masterclass in partnership with our friends at Gainsight. In today’s conversation, we tackle AI's biggest myths, explore practical use cases, and discuss how leading CS teams are already leveraging AI to mitigate risk, personalize at scale, and drive revenue growth.

You’ll hear lots of practical examples of the daily use of AI in customer success. Buckle up and tune in.

Featuring

Eduardo Amorim, VP of Customer Success, Sendcloud

Kate Neal, Senior Director of Customer Success, Gainsight

Marija Skobe-Pilley, Founder of Women In CS



👉 Follow Eduardo on LinkedIn: https://www.linkedin.com/in/eduardo-a-b4468459/

👉 Follow Kate on LinkedIn: https://www.linkedin.com/in/katemneal/

👉 Learn more about Gainsight: https://www.gainsight.com/



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About Women in Customer Success Podcast:

Women in Customer Success Podcast is the first women-only podcast for Customer Success professionals, where remarkable ladies of Customer Success connect, inspire and champion each other.


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Host Marija Skobe-Pilley


NEW - Women in Customer Success Courses:

  • Thriving as a First-Time People Leader - https://womenincs.co/thriving-as-a-first-time-people-leader
  • The Revenue CSM - https://womenincs.co/the-revenue-csm



Speaker 1:

Welcome to another Women in Customer Success limited edition episode, where we bring an exclusive power-up masterclass in partnership with our friends at Gainsight. We bring a conversation with Eduardo Amorim, the VP of Customer Success at ZenCloud, and Kate Neal, senior Director of Customer Success at Gainsight, to tackle AI's biggest myths, explore practical use cases and discuss how leading CS teams are already leveraging AI to mitigate risk, personalize its scale and drive revenue growth. You are going to hear loads of practical examples of the daily use of AI in customer success. Buckle up and tune in, okay, everybody welcome to our Power Up Masterclass.

Speaker 2:

I'm Maria Tzkova-Pile, the founder of Women in Customer Success, and this is already the second season that we are partnering with GameSight in delivering a really interesting conversation to upskill all of us and get us into the latest trends. So today we really have a very exciting topic and, especially given the context of what's happening in the world and how the world can just shut down for a few hours with electricity and, on the other hand, we are talking about AI and what AI can do for us. I can see some synergies here, so I would like to welcome our panelists, kate.

Speaker 2:

Kate Neal is currently a senior director of customer success at Gainsight, but she has so much experience in customer success, building different programs and joining different startups building different programs and joining different startups. Now she's been in Staircase AI since 2021 as an employee number five, and you probably know that recently or last year, gainsight acquired Staircase AI and since then, kate is part of Gainsight team. So I'm really excited that Kate is joining us, because she is an absolute expert in AI technology and everything that AI can do for us. Really, kate, welcome to this masterclass. Would you like to introduce yourself and just tell us very briefly about. How did you get into Staircase AI? What were some of the few pivotal moments in your career that led you to where you are today?

Speaker 3:

Yeah, thank you so much, Maria. I appreciate you having me here today and hello everybody. Thanks for your time. So, as Maria said, I have a pretty extensive background in customer success. I've made my career by joining early to mid-stage startups and building the customer success function and team from the ground floor. And so, in kind of early to mid-2021 or so, I was connected to Ori, the CEO and co-founder of Staircase, by somebody that we had in common in our work history, who wanted to connect us because Ori was starting out building this company and looking for a strong CS leader. So Ori and I had a conversation and he showed me the MVP of Staircase, which looks vastly different than it was, than it does look today.

Speaker 3:

But I just remember the whole time we were on the phone thinking, man, if I would have had this tool and this technology for the last 10 plus years, I would have been unstoppable at my job. Like it really excited me. You know, cs, I think, has always had this uphill battle of proving value and kind of this argument of are we a cost center or are we a revenue generator, and what I'd found as I started digging into customer success was a lot of what we were doing was super time consuming and not impactful, and that's what excites me the most about AI is I think it will help flip that on its head for us by having us be very impactful without as much of the manual input or analysis. And so, yeah, looking forward to talking about all of that with you today.

Speaker 2:

It's already so great to hear your passion about AI and technology, and I really can't wait to hear related insights from you. Eduardo Amorim, I'm coming to you now. You have had a really rich career in customer success as well, starting in project management, a little bit of account management that took you to customer success. So what have been few of the pivotal moments in your career that made you to where you are today VP of Customer Success at SendCloud, to where you are today?

Speaker 4:

VP of Customer Success at Thent Cloud. Hello, maria, and it's great to be joining you today, and Kate as well A little remake from our live conversation at Pulse back in November. So it's great to join you. Yeah, maria.

Speaker 4:

As an introduction, I've been part of customer-facing teams for over 10 years and I think it's a bit corny to say but customers have made part of my career, that obsession for customers and for delivering excellent experiences.

Speaker 4:

I was grateful and I was quite lucky to be also joining startup scale-up companies, especially 10 years ago when I first moved to the Netherlands, and that allowed me to also build the function to be sort of a higher number one, number two in these functions and that helped me to develop the function first in the education technology space, which was an area that I absolutely loved, given all the challenges with the reskilling and the changes that are now being seen throughout the workforce and how it is important to stay, as we used to say, future ready, and that was a great challenge and building for customers and for our partners in that space was definitely amazing for over six years, both in EMEA, where I started out, and then also in North America and APAC region and around four years ago, post-covid, I also had a chance in embarking on a journey with SunCloud in the supply chain and logistics, which has been nothing short and amazing and exciting in a totally different context, but also very exciting and with the same fundament Building, nurturing high-performing teams, which is something that I also particularly like the human side of scaling these organizations while delivering excellent experiences to our customers and partners in the ecosystem.

Speaker 4:

And that's what I've been doing for the past four years now, and it's been quite exciting.

Speaker 2:

And I'm really excited to hear more about those stories, because I have heard a few of those stories previously, which is also the reason why you are here with us today. Probably I haven't told you, but you are an honorary guest today because you are the very first gentleman that ever took part in our Women in Customer Success Power Up Masterclasses. Not that it matters, but just so you know. Okay, before we dig deep into the AI conversation, I would like us to start with a poll, because I would like to hear from everybody what are some of the biggest misconceptions about AI that you've heard. I do believe we are going to have a poll out in a second or few, because I'm really interested in these answers, really interested in these answers. Okay, we don't have Paul at the moment, but this is a question, so please give me your answers. So, what are some of the biggest misconceptions that you heard about AI? We can have a few seconds for it, almost like first associations meet about AI, so feel free to type your answers in the chat.

Speaker 2:

Ai is plug and play and will work immediately. Good one, it's all replaced our jobs. You too. No more human CSMs needed. Is it a good or a bad thing, who knows? Yeah, it's going to take my job. It seemed like we're having a team, but replaced the SCM workforce. Do we have any more misconceptions? I think we had a team. So, eduardo, maybe we start with you. What is your take on the misconceptions that we heard so far and what would be some of the yours misconceptions that you're thinking about? Ai? Is it very different from the team that we are seeing?

Speaker 4:

I think the team actually captures two big let's say schools of thought around AI One that it's going to be the silver bullet that's going to automate it all and make everything work flawlessly, and the other one is that this is the more creamy outlook on our careers, that it's going to replace us all, because everything can be automated and we are going to become redundant.

Speaker 4:

And I think those. I would agree with those two misconceptions. On the one hand, no, it's not going to do it all for us and it requires a lot of data and we talked about this before a lot of the prompting and the preparation for us to make full use of all the capabilities that it has to offer. And, on the other hand, it will not replace our jobs. It will work alongside us and it's going to be an indispensable tool for us to stay up the curve. But we should work with AI as a big ally and not fear AI and not be, let's say, fearful of what it's going to do to our careers, and I think the ones who understand these dynamics better or best will be able to thrive in the course of the future with AI, and that's no longer a question, I would say. But interesting misconceptions, and I would say that they are quite common and I will align with them as well.

Speaker 2:

And I like to hear your optimistic view. How? No? No, they are not taking our jobs. They are just going to make them, or our jobs and our careers, even better with all the tools that we have available. In the meanwhile, we had one more misconception AI is a data concern, as it breaches our and customers' privacy. Kate, coming to you, Are these misconceptions coming as a surprise to you? What are your immediate thoughts?

Speaker 3:

Yeah, definitely not a surprise. We've all been hearing these things over the past year, year and a half. The most recent call out on the data concern and privacy is a very interesting conversation and something that at Stoke News and now Stoke News is doing. The most recent call out on the data concern and privacy is a very interesting conversation and something that at Staircase and now Staircase by Gainsight, we deal with quite a bit, and early in our journey at Staircase, you know, we would go in and be selling and having to explain AI and really start from a very base level. And now we're getting into conversations with leaders who are saying, hey, our board has come to us and said what's the AI strategy, right? So now we're kind of seeing this flick of this expectation from boards of AI, kind of from the top down, and we're also starting to see customers expecting, you know, AI driven solutions, which is really exciting, right. And so a lot of customers are spinning up like AI councils and you know, creating or navigating processes to assess technology and make sure that it's safe and secure. We're very well-versed in that here. I'm sure other companies that have AI-driven technologies are kind of doing the same thing. So, as with anything right. Even pre-AI, we had worries about security breaches with SaaS tools and all of that, so that's not going to change. We just need to make sure that we're, you know, following the procedures and kind of people making AI technology or staying on top of those things.

Speaker 3:

I do want to just I have a little bit of a different point of view on the AI will take our jobs conversation.

Speaker 3:

I think that in its current state today, we don't have anything to worry about, but AI is advancing incredibly fast and agentic AI is something that I think we'll start seeing.

Speaker 3:

We're already seeing it, but I think we'll start seeing more and more of that pop up. We'll start seeing that technology get more and more advanced, and so I do think there's an aspect of AI where it will replace some job. I think that if you want to weather that storm or prepare against it as a CSM particularly the future that I see with AI of keeping a human in the loop as a CSM are for the things that AI has a tough time replacing right, which will be like the human relationship element, and so CSMs who over-index on being technical product experts and also are commercially proficient will, I think, see a future of being an AI-empowered CSM doing their job. But those who are hesitant to adopt AI or slow to adopt it and don't take on, you know, becoming technologically a product expert and commercially proficient, in a few years we may see those types of jobs being replaced. So that's my suggestion to those CSMs on the call is to start thinking through those things and educating yourself.

Speaker 2:

That is such a wonderful advice because, if we are thinking through maybe just the last five years or more of customer success, we were in a stage where CSMs were focusing a lot on adoption or usage metrics and then very much relationship management, and now, most recently, we are obviously focusing very much on revenue and all commercial skills. So it seems that we are going to so many different directions, but I like how you're stating how commercial skills and those technical or, let's say, product expertise field or product use case field are the ones to stay. So, no matter where we are today in our CS maturity, it's a great advice to start upskilling into those skills, because AI can boost those skills and performance, but it's not going to replace. I really love that approach. Okay, shifting gears a little bit.

Speaker 2:

We are going to have a poll now because, thinking about AI and how are we actually using it every day, I really want to hear from you all how many of you have used AI in your role within the past 24 hours. And, eduardo, we know your answer, so you don't need to. You didn't have any electricity to use it. Let us hear the answers, okay. Fifth Okay, we are still not done. I'll give you a few more seconds. You're changing your mind. The poll is shifting percentages. This is interesting. Okay, thinking of the last 24 hours, how many of you have used AI in your role? And we see the results 64% yes, 36%, no. Kate, is it a good thing, a bad thing? Are you surprised? Did you expect different numbers?

Speaker 3:

You know, I do expect a little bit higher number. I mean, I know this is a smaller sample size, but I also think that this is common. Right, A lot of people are feeling analysis paralysis with AI. Right, I mentioned, when we started Staircase, we were like the only people talking about AI. We would go to conferences and our booth was the only thing with AI even mentioned.

Speaker 3:

And now you go to trade show conferences or any website of almost any SaaS provider and AI is everywhere. And so I think there is an element where people feel intimidated because they aren't sure it's new technology. They feel overwhelmed with the options and the easiest thing to do is to not start. So I'm not surprised by that, and I think we'll talk a little bit later about some strategies that those of you who are kind of feeling like you might be in that boat, things that you can do to kind of dip your toe in the water. But I think that if you fell into that no bucket, you really should make a goal for yourself to start to incrementally get to know and use AI, because you know, as I said before, humans that aren't able to leverage AI you'll have a hard time in the future fitting into this industry.

Speaker 2:

And if anyone would want to kind of provide a bit of more context, I'm happy for you to type your answers in the chat because I wonder for all of the yeses like what is the type of AI tool or technology that you are using?

Speaker 2:

Answers in the chat, because I wondered for all of the yeses, like what is the type of AI tool or technology that you are using, because I do believe that sometimes we are not even sure yet about what do we mean by AI. Does it mean, oh, I just go to chat, gpt and ask it to you know, put some prompts into, redo this email to the customer or write media, linkedin post or anything else that people seem to be commonly using chat, gpt or any other AI technology. So I wonder for all of the yeses. When it comes to really your everyday work, what are some of the technologies where you are using it at, living it at? And, eduardo, I would like to move on to you and ask really, how is it in your team and in your Kafton Success organization? What are the ways that your team is leveraging AI at the moment?

Speaker 4:

I think I will echo what Kate mentioned before as well the fact.

Speaker 4:

So if we want to go head-to-head with AI and try to to out, out, compete them or outsmart it in terms of the uh, the heavy, the uh, heavy, intense, intensity type of tasks, we are not gonna come on top, come out on top.

Speaker 4:

But I see a comment from Angeline here saying that note taking the ability to basically, after an interaction with the customer, having all the notes, having everything synced into the timeline and having access to those notes without having to go through that additional work I think everyone in the call will recognize how oftentimes we block those 30 minutes after a QBR, after a customer interaction, for gathering thoughts and to put everything in place.

Speaker 4:

And those are things that, for example, my teams we are simply able to automate, even if you record a call, having access to a brief of the conversation, and make it readily available for the rest of the teams or for other stakeholders to have access immediately. That's a game changer and that's one specific example where we are already leveraging that to our benefit and that, as Kate said as well, that is leaving us more time to what truly matters, to focus on our ability to storytell, to create engagement in different ways, in a more humane way, to remain creative and to have different ways of interacting with the customers and showing that value. And I think that's the valuable part and how we should be focusing and spending our time, with this great help and aid from AI, doing, let's say, the back office work for us.

Speaker 2:

That's really great, eduardo, and some really valuable example how simple tools such as recording calls and gathering feedback is incredibly useful and can save us time, if nothing else. But also those tools are just so useful to prepare the nodes in such a nice and structured way that it's pretty much better than what we would typically do and spend 30 minutes or so. I remember as a CSM, sometimes the hardest task seemed to be those follow-up to all the customer laughter calls, because it is something you are leaving at the end of the day, because you're constantly back-to-back, etc. I'm sure everybody can relate to that. And now, moving on to Kate to hear her thoughts on it, I wonder, for everybody who responded no, if you could also leave a comment.

Speaker 2:

Just give me a bit of an idea. Why not? Are you not having at your disposal tools with AI, or they are not switched on for the tools that already have it but not in your organization? I would just like to note it because for a few customers that I'm typically supporting, I've also seen how they typically have all the tools and all of those tools already have AI today in place, but they are not using it because of different reasons. They are not sure what could happen with it, from security, lots of things that we've already spoken about. So the array of AI tools is there, but there is a wall between people and actually using and leveraging that technology. Kate, how are you seeing, especially in context of customer success teams, how are you seeing, them using AI and leveraging them every day, maybe even from the perspective of managers and leaders, but then also individual contributors?

Speaker 3:

managers and leaders, but then also individual contributors. I see that so that the obvious, what we just talked about, which in my mind now is table stakes for AI right, the ability to, you know, take notes, for you to automate manual data entry those are all things that are kind of the base level of AI. I think what you know we've found success with, both internally at Gainsight and with our customers, is leveraging AI to start to drive desired behaviors from either your ICs or your customers, and so an example of that could be, you know, one of the things that we want to do, especially with our, you know, customers that are on the higher end of our tiering structure, is make sure that we're driving EVRs, because we have data that shows that customers that receive EVRs are two times more likely to renew than customers who don't. But, as we know, csms are oftentimes underwater. They're overloaded To your point. They're moving back to back from calls EVR is taking a bit of time to stay on top of, and so a lot of us kind of free AI.

Speaker 3:

Our EVR was more reacting right. We were using it as like a save player. We thought a renewal wasn't going to trend well, or if we really wanted to sell, a big upseller, expansion or cross sell, kind of using it either from a defensive position to go and improve your value or to use it just as a commercial lever. And I think what AI allows us to do is, you know, stay on top of our desired EVR cadence by giving the team, you know reminders, right. So, hey, we've got you know tier one we want a quarterly EVR so we can drive that behavior with AI by surfacing that to them when it's time to schedule the next EVR, evr.

Speaker 3:

We can use AI to start to quickly compile content for EVRs and really be able to kind of use AI to move us in that from reactive to proactive. And I think that there's a lot of things that we do in CS, right EVRs, we do cadence calls, we do roadmap reviews, all of these things that we can really start to lean into AI to drive the behavior from a team perspective. And then from a customer perspective, we can start to drive behavior using AI, like in product, for example, so we can set up, you know AI logic or you know, put into a prompt. These are the things that we need customers doing in the tool that let us know that things are successful and sticky and then drive them to those behaviors in the product. And so you know, the automating stuff is really great, but I think that we need to fill that space by doing some of these other things that leverage AI to kind of make a broader impact on the business.

Speaker 2:

I'm really excited about that part because, also, as a CSN back in the day, trying to think what customer is thinking, how they're behaving, what parts of the product they're using the most, and how to actually translate that into the actions, into the next steps, into the playbooks, it's always kind of a black hole. You don't know even where to start from and trying to gather different data points from different places. I'm really excited that technology is there to really help us, help customers of us, leaders and CSMs to start adopting it and track better behaviors of customers. I've seen some comments how people are using it so far and I see some comments where you know that has to change in a way if you haven't adopted AI yet for leadership tasks, et cetera. So I'm glad to hear from both of you, eduardo and Kate, how, from one hand, we can leverage it so well for product behavior and different prompts and tasks From leadership perspective, tracking the activities that we are doing towards customers and how they are impacting their customers and the relationship and ROI, et cetera.

Speaker 2:

There might be a bit of a fear of missing out on AI if we haven't jumped yet on that bandwagon Because, on one hand, we are now speaking about very nice sophisticated AI that can help us with all of those complex, like product tasks, et cetera. On another hand, we have teams who don't even record calls yet to kind of capture that basic data and use AI in that basic level. So if you are maybe on that side and haven't adopted it yet, well, eduardo and Kate, I wonder what is your advice to those CS leaders? What would you say are some strategies and tips that they can start using by staying ahead, even if they, you know, haven't jumped on that bandwagon yet, or they're thinking, oh my gosh, there is so much more we can do and we are at a very, very basic level. Kate, what would you say?

Speaker 3:

Yeah, I mean. One thing I'll say is that even the people knee deep in AI every day, working in AI, like building an AI native platform we struggle to stay on top of AI technology because it is changing at an incredibly rapid pace, right, even sometimes day by day pace right, even sometimes day by day. And so what's interesting to me about AI and looking into the future is that what we're doing today is probably going to be different from what we're doing next month, which is going to be vastly different from what we're doing a year from now, and so I think, as CS leaders, we're uniquely positioned to shape what the future of CS looks like, empowered by AI, and that's an incredibly exciting opportunity. I think that we can really start to to ship the narrative around customer success again from the cost center to the revenue generator, because of we're using AI to uncover blind spots, to mitigate risks, to capitalize on opportunity, and able to do that at scale, and not just able to do it at scale, but able to do a lot more with fewer people. That's going to increase your profitability, right, and all of the good things that we know that make a business successful is what AI is going to empower us to do so.

Speaker 3:

I think if you haven't made the leap yet, one, it's okay, take a deep breath. And two, just start. Right, I know that it can be overwhelming. Chat GPT is a really great entryway, right, and don't use it like you're using Google, right? Don't just use it as a glorified search engine, but really start to converse with it. Right, give it your role, give it some email examples and say, hey, can you start to help me craft responses in my style? Just start there. That's super simple. It's a very low-hanging fruit use of AI, but it'll start you exercising that muscle, and the more reps you put in with AI, the more advanced that you'll start to get. And so don't boil the ocean, so to speak. I would say pick one problem that you're dealing with in your work life and use one of the many free AI tools that are out there to see if you can use it to solve that problem, and then, once you do that, I think it'll sort of start this snowball effect where you'll be like what else can?

Speaker 2:

I use AI for.

Speaker 3:

Right.

Speaker 2:

I love, firstly, the optimism that no matter where we are at the moment you're fine there's always a place to start, and this is a great place to start, even by using all the simple and free tools. And then moving on, eduardo, I wonder what works for you, and especially if we are thinking of CS leader level or individual contributor, or even on the flip side, what works for you? You know tactically, day to day, but then also thinking on strategic level from the leader, because we can see a bit of different use cases of how CSN versus CS leaders could start using some of those different tools that we have available.

Speaker 4:

Yeah, I think and to address the topic of the leadership conversation, that is always the narrative of the business impact and that is highly contextual and really depends on what you're trying your business is trying to achieve, whether it's a fast growth and you really need to cater to more customers and to kind of increase your footprint and using AI to that end and to that goal. That really depends on what you're trying to achieve. What I think people can already start and what I see commonly is and Kate mentioned this as well is your opportunity to start. Working with AI will expose and will help you improve also the way you reason, the way you think about the things that are important, and I think that is such an entry level of a skill to have in both in IC level but also at leadership levels, to help you have that conversation, to really reduce the noise on all the things that we are juggling in this industry and in SaaS space as CSMs and account managers and trying to filter the essential and that should always come down to the business impact and being able to articulate that business impact to our leadership teams. And that's where the buy-in comes from and that's where the buying comes from and that's where the visibility comes from.

Speaker 4:

In some cases, it's really about seats and driving adoption and CSET and NPS and all of those metrics that are important.

Speaker 4:

In other cases, such my case, commercial footprint making sure that we are becoming more efficient, managing the customer base and making sure that we are, with the right level of personalization, proposing and showcasing solutions that work for the business of our merchants and our customer base.

Speaker 4:

That's highly important for us and AI is helping us achieve that.

Speaker 4:

We are able, more than ever, to plot in the infographics and behavior elements that usually will take us a huge QBR team, a huge team of data analysts, and now, at ease, we can actually create some of these filter, some of these dynamics and then be able to be much more targeted, much more personal in selling into increasing our footprint with the existing base, and that's one of the uses that we are doing. Footprint with the existing base and that's one of the uses that we are doing. But again, I think the secret lies on not not having the foam or not trying to be ahead of the curve, but just being in the game and trying, starting from the beginning uh, how we prompt and how we think about the problems that we have on our on our day-to-day lives, and that's a very interesting use case for me and for my teams as well. Both if you are an IC or a leader, are you thinking with simplicity and are you translating those things into the language of business and impact, and that's for me a great place to start.

Speaker 2:

I'll come back to you, eduardo, just in a second, but to let you all know, please feel free to start typing your questions. We will be trying to answer all of your questions. You can use the Q&A button, but you can also type the question directly in the chat and you'll make sure that we can answer any of the questions. I kind of have a few, you know, for Eduardo and Kate, but also for your audience. But, eduardo, I'm coming back to you because I remember a few months ago you were sharing a very interesting story about how your team members were able to, because of AI, be a bit more free and do some very nice and interesting personalized touches for your customers, and that's something that really excites me. Let the AI do the admin work, the all the mundane work, and then CSMs can really do something cool. What was that and how would you inspire other leaders to try something similar?

Speaker 4:

In our space, and I remember the quote I used back then was that we are trying to standardize the routine and humanize the exception, and that's exactly how we are trying to leverage AI In our space. When we buy something online and whenever the package doesn't arrive in the ETA that you were informed about, you go into the spiral of wanting to know the so-called where is my order spiral that no one in e-commerce wants to face, and that's a very inefficient spiral because you're not adding any value or just basically going down the value chain asking for an update about the status of your order. Oftentimes the tracking ID is outdated. Then you have an additional tracking ID that you were not aware and you were not informed about it. So all of these interactions that are often highly time consuming and also a big predictor of bad experiences in terms of the reviews that customers and the repeat purchase of some of these customers in e-commerce, we are trying to get rid of all of that and that's one exciting area.

Speaker 4:

We are trying to automate both with LLMs trying to fetch the information from emails and the automatic replies both from carriers and online commerce businesses, and we are trying to really free up time for CS teams, for support agents and for customers to focus on what matters and to kind of spare them from this pain of having to chase an order and trying to have way more proactive updates and things like if we have a high degree of confidence that the order or the package will not arrive on time, then what are the alternatives? Can we have a restock? Can we have all of these automations underneath in the backend to make sure that the experience becomes positive and out of a seemingly bad experience we turn it around into a positive experience? Its own already changes the nature of the interaction between our teams and our e-commerce customers and their end consumers, which, at the end of the day, is also critically important in a B2C environment or B2B2C environment, and that's one of the, let's say, the most important use cases that we are investing a lot of time with support automation, with what we call AVA, the Advanced Virtual Agent, and this is all powered by AI and something that we are quite excited it's now been announced as well, and it's one of the areas of focus at 10Cloud, and we are quite excited about that one.

Speaker 2:

This is really really good example and use case of how those agents can spend time on something that can really bring a bit of a joy to customers as well and make the whole experience so much nicer. Everybody. If you have questions, please, this is the time to put them in the chat. I don't have a few, but I wonder for you, kate, as you are talking to customers who are leveraging AI technology day in and day out, and I can presume you will mostly be talking to, you know, customer success teams, which is why we want to get more insight into it. What are some of those interesting wow moments, or those special, maybe surprises that they have seen that they can now do things differently, or they are seeing amazing results or very different results where they haven't seen previously. What are some of those moments that it's almost like the harm moment and they are seeing oh, it is so good that we started using AI for this particular thing.

Speaker 3:

Yeah, a couple of things come to mind. The first is AI's ability to do what we call uncover a blind spot, and so we're very familiar in CS. If you've got a book of business, usually it's what the squeaky wheel gets. The grease is what we call it right. Generally, in our book of business we've got this slice of the business that's very involved, very engaged, very sometimes needy and demanding of your attention, and without an AI system, it's very easy, as the IC of that book, to be focusing your attention there, kind of forget everybody else, and so AI is able to take a look at that sort of forgotten cohort and give us signals, right? So a lot of times that disengagement or quietness from a customer can be an early indicator that they are potentially going to churn at renewal or that things aren't going well. When we plug new customers into Staircase, they immediately get a dashboard of all of the churn risks or revenue risks that our system has identified, and almost always there's several surprises in there for them, right, they know about the ones that are kind of already fires, but they don't know about the ones that are like the burning embers, just kind of waiting to spark, and so AI can really help give us what some of our customers call x-ray vision, to make sure that you're really not missing anything. And the other thing that came to mind was and this is I think this is what I'm most excited about with AI is as a leader a lot of times. Let me just take an example of I'm a CS leader. Product puts out a new feature and support is inundated. Csms are inundated with customer complaints. Something isn't working, they don't like it, it's not helpful. Whatever the case might be Pre-AI, we as a CSM would go to the product team and say, hey, this is a problem.

Speaker 3:

Like, please help, this isn't working out. A lot of times we would get something from the product team back. That's something like well, show us the data. It's like, well, I can't forward you every support ticket or email or add you to every call where this is coming up, and so a lot of it was like on this gut feeling or anecdotal. And now, with AI, we can ingest all of your customer communications and understand at scale what are the common things that your customers are talking.

Speaker 3:

So if we go back to this example, if we open up in Staircase, we call this the topics report and it shows, you know, product or feature XYZ at the top of you know the most high volume topics in that time period and it's related to a red or negative sentiment.

Speaker 3:

Now I can use that AI data to say, hey, product team, you know, 65% of our customer base has reached out to us about this topic in the past 30 days.

Speaker 3:

The average sentiment is 18 out of 100, right, it's very red and here's some snapshots of what customers are saying. But now it empowers me as a CSM to go to the leader and say, hey, I'm not really getting anywhere with the product team. Now I, as a leader, can go to the product team and have a data-driven conversation and I can point to specific customers, I can point to specific feedback and show the volume, show the revenue impact, and usually that's what we need to do to kind of get some movement and collaboration from product is. You know, show the business impact and tie it to revenue and then we can get that done, those things upstream to see better results downstream, rather than working in one customer account at a time and making an impact. I think that's how we as CS leaders are going to shine in leveraging AI is doing fewer activities, but ones that massively move the needle on the business.

Speaker 2:

I'm feeling incredibly excited about it because I didn't know which examples you were going to use and I feel so empowered. I may be a hero tomorrow, because I just got a few of those questions today about how do we work with a product, because they can't prioritize, etc. Now I have an answer, which is also and churn oh my gosh. Like there is no company that is not concerned about churn. Who doesn't? And churn oh my gosh. Like there is no company that is not concerned about churn. Who doesn't have surprise churn? So just plug it in and see what happens and see some of those surprises. I mean, those are some really incredible use cases.

Speaker 2:

I'm really excited about what we heard so far. I think we already heard lots of practical examples of how we can start leveraging it day to day, very low hanging fruit with something very simple, and how, on another hand, there is such a beautiful and sophisticated technology to help us properly combat churn and get some proper data and insights and work with products. As we are wrapping up, I would just like it to be very, very quick fire. Was there anything that we haven't mentioned yet today, any really good tips or tricks of how we can start effectively using AI today in our roles, no matter where we are on the scale of using it. Like what are things that will get us some really quick wins? Things that we should start immediately. If we haven't already, eduardo, shall we start with you?

Speaker 4:

Yeah, for me, the tip is to front-load the impact and not ask for budget for more data, for more analysis and for a lot of different tools. I think with the tools that we already have readily available, we can already make that impact. The way to get that buy-in and to kind of scale those efforts is to just start to be very intentional about what you're trying to do and which problem, whatever small it might be, that you're trying to solve. Show that you can use and leverage AI to solve that problem and what the opportunity will be if you could scale that effort. And that's where we should start. Instead of building the whole empire from the get-go and having to go through funding and through business case presentations, I think my advice would be to start small, to start with the tools that you have. Everyone has AI clients accessible to them and that's a good place to start and to start now and to have impact pretty much tomorrow. So that will be my tip.

Speaker 2:

What a good advice, especially given some misconceptions at the beginning, how AI can obviously resolve and solve all of our problems. So, instead of thinking that, focus on one thing that you want to see resolve and just build the concept Perfect. We do have a question for Kate. What was the tool Kate mentioned about acquiring data for conversations with product on customer complaints? Their case AI? Maybe their case AI, maybe Staircase?

Speaker 3:

AI. You too, Yep Recently acquired last year by Gainsight, which is how we've moseyed on over to this team. But yeah, staircase was the first customer intelligence AI native platform on the market, and so that's what we've come to market to is the AI solution. I do have one additional comment that may not make me super popular, but I think it's a truth that we need to come to grips with, which is AI is only as good as the data that we put into it, and so, before you even start using AI, I would really do some data sanity and make sure that the data that you're feeding into any AI system is accurate and up to date, because bad data in, bad AI out, and so that's kind of a precursor to really getting into AI is making sure that your data set is in a good place.

Speaker 2:

Kate, you just got us with our bold Well, just when we thought that everything will be resolved and beautiful, you reminded us of the data, but I think this is just a wonderful reminder of, yes, not everything will be solved and resolved and done instead of us. So data hygiene on the first place, and then thinking about what problem we want to solve and then going after it. I think we have a lot of super great tips how to start small and how to build that empire of having an amazing AI organization. This was incredible. Thank you so much for your insights, kate and Eduardo. Thank you for coming today. Thank you so much for your insights, kate and Eduardo. Thank you for coming today. Thank you for joining us on this conversation, and you will also receive invite for our next Power Up Masterclass in the coming weeks. Thank you all for today and have a wonderful rest of your day. Thanks, though.