Rethinking the Retention Touchpoint: How Leading CS Teams Are Rebuilding the Customer Journey

[Speaker 3]
Thank you so much for joining us this afternoon and for an incredible couple of days together. As James mentioned, I'm Taylor. I lead our global customer success team here at Gainsight, and I'm joined by three superstars this afternoon, and today is all about rethinking and rebuilding the customer journey.

The lights are bright, but can I get a show of hands? Who's rethinking the customer journey at this moment? Yeah, just a few of us?

Okay, perfect. So we're gonna explore that, but today is all about real decisions, real trade-offs, and the lessons along the way. So we're gonna ground it in reality and how these folks have explored rethinking retention in this new world.

But before we jump in, I'd love to walk down the line here and do some introductions. So for each of our speakers, I would love to hear your role, the organization that you work at, tell us a little bit about your team, and to keep it fun and on theme this year, tell us about your favorite kind of treasure hunt. You want to start us off, Pablo?

[Speaker 1]
Okay, so I'm Pablo. I'm Vice President Customer Value at Spryker Systems. We are a platform provider and software vendor for digital commerce solutions, Berlin-based in Germany, as you can hear.

And yeah, my favorite treasure hunt is bringing something back from vacation with me. So this year we went to Thailand with my family, I have five kids, and I was joking when we arrived and I said, like, I love this palm trees here and let's take a palm tree with us back home. And they were like, yeah, sure.

So actually the day before we left, I was swimming in the ocean and there was a coconut coming towards me in the water, like this big, I'm not joking, and there was a little green leaf coming out of it. And I said to my wife, so I'm going to bring that coconut back home to Germany. And she said, yeah, you will be arrested, we're not going to do that.

So I did some research with the help of AI and found out that coconuts are one of the rare fruits you can bring back home, if you use them as food. But yeah, so I was hiding a little bit the green leaf in the plastic bag and passed the security all the way to Germany, and now the palm tree is growing. So it's like this big already.

Yeah, it worked out.

[Speaker 3]
Real treasure.

[Speaker 4]
Yeah, I'm Jessica. I sit on the CS strategy team at Genesis. I'm responsible for onboarding new customers and scaling CS motions, really, for all customers and particularly the long tail.

And we work with CSMs globally, so a large team. See, my current favorite treasure hunt would be around foraging for chicken of the woods or morel mushrooms. So I like to get outside and see if I can find that treasure.

[Speaker 3]
What is the season for morels?

[Speaker 4]
It's very short. In the States, it's about three weeks, it could extend a little bit. It's very sensitive to weather in April.

No one will ever tell you the secret spots. A rare treasure. Yeah.

[Speaker 2]
Hi, everyone. I'm Shannon. I work at Arian UK.

We are across the UK, and then we have our sister companies over in Europe. I look after customer success, customer support and professional services, so everything post sales. And my foraging, so this actually goes back to when I was a kid.

I grew up in South Africa, literally in the middle of a game reserve, so a safari park. And I used to forage for creepy crawlies. Notable findings was once I found a snake and I caught it and I took it to school in a shoebox.

That didn't go down well. And then another time I found a baboon spider, which is kind of like a tarantula, a dead one. I took it home and I froze it.

And I put it in my stepdad's drink that night. So I didn't like him very much, to be fair. That wasn't just a fun prank.

[Speaker 3]
Three very different treasure hunts. All nature related. True.

So that's great. Well, for each of you, as you think about now the treasure hunt of figuring out how do we rebuild the playbook? How do we make sure that we shore up retention in this new age?

You know, as we think about the old, old, a couple years ago, CS playbook, it's on notice. So what is one thing that you've had to unlearn in the last 18 months to think about continuing to be effective in retaining customers? Pablo, you want to start?

[Speaker 1]
Yeah, I mean, just by having role definition doesn't mean that roles are fixed. And we heard it yesterday and today, everywhere. Roles are evolving, especially in the field of customer success with AI.

We need to have curious people who are not shying away looking into automation, AI stuff, technical things, and also commercials. So I think this is something which really needs to change while the constancy is working against the outcomes and customer value creating customer value in the end.

[Speaker 3]
So the rigidity of role specificity?

[Speaker 1]
Right.

[Speaker 3]
Great. Jessica, how about you?

[Speaker 4]
Yeah, I think we've had or I've had to unlearn the idea that every renewal needs a CSM touchpoint at that moment, or the moment of renewal. Really, with all the capabilities and AI tools out there, getting the signals early, and being able to act when you get the signal has an impact on renewal. And that's very important to start doing early.

[Speaker 3]
What's one signal maybe you're listening to now that is new to the team?

[Speaker 4]
Oh, good question. There's been a lot of talk around online resource hubs. And so we're starting to plug into that more actively.

So not only who's a member of the community, but are just they logging in? Are they trying to access those resources?

[Speaker 3]
Oh, nice.

[Speaker 4]
So engaging with your brand in another location.

[Speaker 3]
Exactly. Yeah.

[Speaker 2]
Shannon, how about you? I've had to unlearn perfectionism and control. My whole CS career has been about building these processes and customer playbooks that rely on if this then that.

And now that we've brought AI into it, we're letting humans loose a little bit more. We need to be able to become comfortable with not having every single answer and going in with a human curiosity. We're responding to the alerts that are coming from AI.

It's giving us some answers potentially, but we can then take that and speak to customers about the problems that they're facing, challenge those processes. And that doesn't always fit neatly into a box of what I, at the top, designing everything and how I wanted to look. That doesn't fit into that.

So it's been a real personal journey for me also in terms of just really looking at the hiring profile, right? And then having faith in that and stepping back a little bit.

[Speaker 3]
I would imagine this is a common challenge for so many and thinking about the team that you mentioned that you hire, the hiring profile. Is there one thing you have changed in how you assess talent or how you're enabling the team to think in that growth mindset?

[Speaker 2]
Absolutely. So I'm no longer looking for somebody who can follow process. Data analysis is obviously important.

Curiosity remains my top hiring criteria. But I'm looking for somebody who can understand the nuance, right? So AI can look at 100 different data points and identify that there might be a risk.

But only a CSM can sit in a QBR and understand that a customer not engaging with your product is actually down to their fear of technology, the changes that are happening in their own organization. AI can't do that. You need a human to be able to understand what might be impacting the decisions they're making.

And then, again, AI can help in terms of solutions. It can put the deck together and what does that look like? How do we work together?

But they won't be able to deliver something in a way that is emotionally grounded, emotionally intelligent to be able to really get people to change their behaviors. So that's really important to me now. Can I have somebody who can use emotional intelligence to read the room, to really understand how to drive behavior changes?

Because I can't do that with technology.

[Speaker 3]
Yep. And on this point, you've talked about the danger of over-automating, you know, with all these new tools available, with all these signals now available. My goodness, we could just send an email every time a signal changes.

But you've certainly talked about how we can over-rotate in that direction. So maybe talk to us about how you've restructured or reoriented your team that enhances, uses AI to enhance team judgment rather than overriding it.

[Speaker 2]
Sure. So I think anybody, I know there were a couple of hands, I'm not a couple, more than a couple of hands up, but people reimagining their customer success journey and retention touchpoints. It's about starting with the customer journey, right?

So where are you now? And where's your ideal state? Don't think about the technology, don't think about the team that you have in place, but start with that customer journey about them getting to the value.

That's what we're all about, right, is helping the customer to derive value from our products so that they continue to invest. That's essentially what we're trying to do. So what does that journey look like?

And then start to overlay the technical capabilities that you have. And everyone's on a different AI journey. So thinking about what it is that's actually achievable, what can you automate, right?

But where are the real value pieces by having a human in those areas? And then if you found out where the human is valuable, really just focus on making sure you can identify those times really easily. So for example, customer password reset, right?

Coming from a healthy customer is absolutely easy. It goes through an AI bot, answers the question, and off you go. And password reset request coming from somebody who's had three tickets that week and is renewing in the next 90 days, that absolutely needs a person.

And so if you can design your journey around being able to identify those points and then putting your people in the right place, that's certainly how I have approached the structure of my team and having the right people in the right places.

[Speaker 3]
So to get to where you are now, did you find a moment where maybe you went too far, automated too much, and you pulled back? How did you know the sweet spot?

[Speaker 2]
Oh, God. There's a lot of sweet spots. It's context, right?

We have Amber, for example. Amber is our support agent. We built her.

We weren't happy with our support software's in-built agent. And so we built her ourselves. She's fantastic.

She was answering about 60% answer rate, and of that, she had about an 85% resolution rate, so pretty high. But we were doing the wrong things because in the same example I used before, people don't actually want a 30-second answer from Amber because guess what? Then they know it's AI, and they start to question the value they're getting from the product.

They're like, well, if I'm just going to speak to AI every time I contact support, why am I paying these service fees? Where is my investment going? So things like that where we actually had to then scale back and go, actually, do we want Amber dealing with those customers specifically?

Do we want Amber responding within 30 seconds? Actually, we want to pull it back a little bit. So there's a bunch of things where we've had to go, that's brilliant, but is it what our customers want?

So yeah, there have been certainly those lessons.

[Speaker 3]
I love that. Experimentation. Unfortunately, no golden ticket.

No exact answer, but experimenting. We're figuring it out as we go along. I'm pretty sure everyone else is.

Yep. And you hit on my treasure hunt for this week, which is all the different names for our AI agents, and I haven't heard one single repeat, and Amber is a new one.

[Speaker 2]
Oh, there we go. We have a whole host. They're actually in our...they have HR files and everything. They're actual people so that we can think about where their remit is actually too much for that one person, in the same way you would think about, actually, is that person at capacity now? Do we need to hire somebody else? We think about it.

So yeah, we have a whole host of AI employees. Part of the team. I love it.

[Speaker 3]
Well, Jessica, I know you've mentioned that Genesys has built what you call an always-on success model. So walk us through that and what it actually looks like in practice.

[Speaker 4]
Sure. We think about always-on success as really giving the customer a path to resolve their task or take the next step in the most frictionless way possible. That's very idealistic, but that's really the goal, right?

And so we have a good hub of online resources, community, education, product support, all the things you've heard about yesterday and today. And we've layered on top of that a digital assistant. And so this digital assistant can answer questions, can pull in the right resource, and probably most importantly, there can be a handoff, if you will, maybe to a human support agent or a CSM connection via email.

So depending on the path that the customer takes or needs, sometimes they get a quick answer and then you get the next level of question, which is really impactful for us and the customer, right? So they may come with what is a quick question because they're really thinking about something deeper. And I'm sure you all have seen this in your own life and work world.

That's probably where you want to have the value, right? That's where you want to understand. So it's helping us get to that level.

And I think certainly helping the customer experience overall.

[Speaker 3]
I know we were talking about architecting and experimenting. I'm curious, you mentioned handoff. And so how did you go about defining what went into that handoff, who was going to own it?

How did you architect that?

[Speaker 4]
Oh, there's a lot of testing. A lot of testing. And we released the tool internally, oh, six or nine months before it was ever customer-facing.

So a lot of testing and systems, both in the sandbox and then kind of production. So picking a customer cohort and rolling out, monitoring, measuring, and then kind of a full release. Yeah.

Amazing.

[Speaker 3]
Well, Pablo, you mentioned a little bit earlier, role clarity and role changes. And I think CS teams everywhere are dealing with this kind of a change and less headcount and a lot of uncertainty. So how do you keep your team focused on customer outcomes when so much is shifting around us and we're needing to experiment, we're needing to try new things?

How do you keep the team laser-focused on customers?

[Speaker 1]
I mean, you're mentioning change and uncertainty, and those are usually not the most comfortable feelings someone can have. And yesterday we heard about choosing to be an explorer, but you need to give people the trust of being able to choose being explorers and not worrying too much. And you need to lead the change with transparency, empathy, focusing on the people, on their strength, seeing if you can move them within the organization, if they are more talented.

We also heard it from Kate before, I think, also on this stage, like if they are more attracted to commercials or more technical, what is their sweet spot they have and their talent they bring to the team because everyone is individual. And, I mean, we went through quite some changes, and I'm with Spriker since almost five years now. We had a segment-based model, then we had an industry-based model.

We again went back to one big customer success team, and you had to work a lot with individuals and the needs of the organization, but never forget about the value you want to bring to the customer and never let customers feel that change is going on. So there are so many things to keep in mind. And you need to be very transparent to everyone and try to give them clarity of what needs to change and where do you see maybe their path or where do you need them to change, but also what stays consistent, like what doesn't change.

And I think the more open you are with your team, and those are not always team calls, those are also a lot of very individual one-on-ones. You see if they see themselves as part of the journey and where, and then you can work with that and try to make it work for all the sites.

[Speaker 3]
Yep, yep, that makes sense. And Shannon mentioned earlier, you know, really focusing on curiosity. And I saw you nod your head, and this goes into it.

How do you look for curiosity?

[Speaker 1]
Absolutely. I mean, that is really like you need to have, I don't know, maybe the empathy and work with the people and asking the right questions to figure out if they are curious to explore different positions. Like I had one of my colleagues, he was missing a little bit the soft skills, but had a very different impression about himself.

So we talked about that. It was not an easy talk for him and not for me, but we figured out that he's great in creating value within the team as a value lead, like pointing the CMs to the right programmatic approach and how to work on different things, and bringing automation into the game and their individual strengths. And after six months, he said, like, that was the best reflection we had.

The growth of my role changed. I'm a value lead now and not a CSM any longer, and that really helped, yeah.

[Speaker 3]
That's amazing. Yeah, I feel like I've seen in so many teams this, you know, with AI empowering teams and, you know, for those who have been able to open up MCPs and really give the team language models to harness their creativity, we're seeing a different side of teammates where their superpowers and their interests really come out. So to identify that and then help propel them into that direction, that's incredible.

And to your point, new roles. There could be new roles any and every day that we can place folks into. So that's great.

[Speaker 1]
And I didn't touch now the topic of AI automation because we started two years ago already to capture every single customer call with the help of an AI tool and also every customer communication. So that really helped also along, like having the data already, seeing the history of an account and then, yeah, having this support with automation. But, yeah, don't do the mistake and capture activity as a proof of value.

So never do that. But you always need to have that human judgment in place as well.

[Speaker 3]
Yep. Agreed. On the human judgment piece, I mean, to that point exactly, you know, we don't want to measure activity.

What's maybe one way you all look at proving the value of your team? Is there a particular metric that you're focused on right now?

[Speaker 2]
For us, it's GRR. That's our North Star. I love NRR, personally.

Like, if we're allowed to have our favorite metrics, is that too nerdy? But GRR is ours as long as we're hitting that number. And then, obviously, that then leads to different behaviors and measurements further down.

But, yeah, that's it for us, I'm afraid. Yep. The ultimate one.

Yep.

[Speaker 4]
NRR for sure, but I think we're moving so fast in some of what our leaders are asking are, okay, well, what conversations or customer signals? Are we getting to a trial? Are we getting to a first adoption?

Are they doing a pilot? And so looking at how to capture not just the activity that a conversation has happened, but, you know, is there a next step outcome? And can we track, like, time to value within that?

And I'm sure the next question is going to be, can we forecast it? But we're not there yet.

[Speaker 1]
So I like both. Yes, the hard facts, of course, GRR, NRR, also the soft facts like customer engagement. So I hold regular one-on-ones with every single team member every week.

And also really going through the accounts, asking, like, with whom did you connect? Also leadership contacts. And I also try to monitor that, especially with the strategic and large accounts, that they are in a good exchange.

And also if they take the time to engage with them personally, to build that relation, because this is something we cannot automate. I mean, we introduced three years ago a self-service portal, digital customer success. Customers go there.

That's their first. They learned that if they want to know anything about the product or the documentation or about our academy, Spiker Safari, is it called? They go there and they help themselves.

But if there's something where they really need, like, more assistance or personal touch or where they have something they can't find there or want to connect to other customers, then the CSM needs to be that trusted advisor. Yeah, I don't like that expression because we use it all the time, but it is what it is. Yeah, you need to be approachable.

And I also question if they are engaged with the customers. And if not, how can we re-engage? Should we send them a pizza or should we show up in summer with a bag of ice cream or whatever?

[Speaker 3]
Yeah, the account-based marketing folks have had this down for a few years. I'd like some ice cream with me.

[Speaker 1]
It's more warm here on stage than down there.

[Speaker 3]
Well, if you had to point to one touch point in the journey, and we've talked a little bit about those various phases of the journey, we've talked about where CSMs are now fitting, where they're able to have more time to have higher order judgment and really focus on customer outcomes and value. But if you had to point to one touch point that has changed the most because of AI, what would it be? And has it made retention better, harder, or both?

And Jessica, I'll start with you.

[Speaker 4]
Yeah, I'm not sure it's one touch point, but I would say having the signals, and really the AI is helping take a fragmented data set and bring that together. So using AI tools really can help. And not just in CS, it's really a broader customer view or a shared view within that.

And so then it can certainly help retention. But with that kind of data set, just having the data isn't the value, right? It's harnessing that and understanding which signals maybe the human judgment can come in and make that impactful.

But bringing the data together is really the first step.

[Speaker 2]
Shannon, how about you? I'm going to stick to the support example, but for a different reason. Is that, I don't know if anybody else has this problem, but our customers are using AI to talk to us.

So especially in support, a customer has a complaint, they use AI to generate an email to tell us about their dissatisfaction. They send it through, they get Amber, who responds. That thing goes back and they put that into ChatGPT.

ChatGPT comes up with an answer. Our AI bots are talking to each other. And all that's happening is nobody agrees with anyone because they both decided on their own outcome, which they're programmed for.

And so it's actually making, it makes the problem worse. So this is where AI is actually making it incredibly difficult to come to a resolution about something really, really simple. And before you know it, it's escalated to gigantic proportions.

It's an official complaint, I have to deal with it, which may not sound great. But I mean, let's face it, it was something really, really small that Amber has blown up. So what we're doing is it's coming back to just picking up the phone.

So again, bringing humans in a little bit earlier, that was a quick lesson is AI talking to AI is definitely not the future. But yeah, other than that, Amber's fantastic. We have Adam, who sits in our onboarding team.

Adam Obey, Amber Jackson, they've got surnames too. And they choose their own photos. Any more As?

No. Lucy and Emily. I think, I don't think there are any more As.

Next time, next book. You know what, we'll get them up on a panel. Yeah, perfect, perfect.

Pablo, how about y'all?

[Speaker 1]
Yeah, I also agree to the data collection and also everything what you said. Yeah. I mean, it needs to support communication and single touchpoint.

I also have a hard time with that. But I mean, if I think about video calls, having the AI in the call, and I think everyone knows that is easy. Like the AI is taking care of the notes and is capturing the transcript.

And you have a very easy follow up after that. You have the action items. But also, before you enter the next call, you can just pull it up and prepare yourself for the call.

And you directly get what's important and what you need to touch base. I would say there we really feel the biggest difference. We started to explore that also with onsite meetings where we asked the customer on site, like, is it okay if we have that transcribed in parallel and the AI runs through it.

So most of them are okay. So also with most of our customers, we are able to record all the video calls and the emails. And that's really helpful because you collect the data over time and you really get the payback after a certain time.

Like we didn't feel that maybe after three or six months, but now after two years, it really, really helps. And you can compare data to, okay, where have they been two years ago, where their risk signals, buying signals, what changed?

[Speaker 3]
Yeah.

[Speaker 1]
Yeah.

[Speaker 3]
That's great. That's awesome. You all alluded to this, but there is also just so much more.

There's now more transcripts, more data points to harness, more conversations happening between technologies. And one of the things that we're finding is for each of the, maybe touch points is the wrong word, motions, each of the CS motions. As we think about where can we augment the team, where can we improve the customer experience?

It's funny how you take one, maybe it's an onsite, you start to crack that open and oh my goodness, there's the preparation, there's the agenda, there's the deck itself that we're presenting, there's coaching myself and my team to be ready for it. So there's all these different moments in each of the key motions or what might've historically been considered, oh, it's just an EBR. Gosh, there's 21 steps there and there's probably places we can help augment the team.

So that's, I think, some of, again, the creativity and the fun behind all of this. So for anyone in this room who's just starting to rethink their retention strategy, what is the one thing of all the incredible things we've been talking about or what we haven't touched on that you would tell them to do first and maybe one thing to avoid?

[Speaker 2]
Shannon, you wanna start? I think I gave this answer earlier already. I went too soon.

Plot out your journey with the customer journey, not your journey internally. Nobody cares what you need to do. Think about what the customer needs to do to get to their end results and then layer things on top of that and that'll help you understand where you need your teams and where you need technology and where you just need to chop off a whole part of the process, which does also happen.

And don't be afraid of doing that. What I wouldn't do, especially with AI, I wouldn't have efficiency targets as your end goal with AI. Like I said with Amber, right?

She was answering 65% of the questions. She was resolving 85% of them and that looks amazing and the board loved it. But the reality is actually we were giving her too much.

We weren't focused on the customer value and being able to deliver the outcomes that we needed. CSAT was still fine, interestingly. You'd look at that and we measure CSAT for Amber versus the rest of the team.

But when you really dug into the details, we just realized that wasn't the right way to be managing the business and so we pulled that right back. So that would be my, warning is too strong a word, but yeah, don't rely on efficiency metrics with AI. Think about the value.

Keep it customer success-y.

[Speaker 3]
Capacity planning, not just for CSMs. We also got to think about the agents and to your point, how big is the remit? How much can and should they really take on? That's great.

Pablo.

[Speaker 1]
Very similar. Know your customer, but also know the individuals. Like know the leadership, the IT, the operational people.

What are their goals? Because they might differ from what you would say, this is a customer goal and then bring that together and then also work on an account plan. So we are working very close with account managers and the customer success managers.

They are reporting to me and they're working together on that one platform and also aligning with each other. So kind of a power couple in both directions. And then might also be that one is aligning better with the leadership than the other one is aligning better with the IT and bringing that together as one strategy in the end.

What I said before, avoid and also what you said, avoid taking activity as a proof of creating value. I mean, that is something I think everyone had that topic at the very beginning of AI because everyone thought like, okay, I'm active. Also it's like, I'm using AI or I'm adopting and really taking the value out of it.

That's also a big, big point here. Like really proof against what is the customer value and how's the adoption going. And also what is the ultimate goal is the renewal, but after the renewal is before the renewal again.

So it never stops and it's an ongoing journey.

[Speaker 4]
Jessica, how about you? Yeah, so I would start from a customer perspective. I think that's a really good point.

And very few customers follow what we think is that happy ideal path. I know, I know. So in your customer perspective, think about those, the data points interactions that you can pull together for the early signals.

I think they said it in the keynote this morning, act early. And I think I've said it two or three times since we've been up here. So that's important.

And you may not have all the data that you want at your fingertips. What can you get and what to work towards, but that's important from that customer perspective. And avoid, I would avoid around kind of rethinking retention and that playbook particularly.

I would avoid broad risk codes and lumping categories together. So if you're using AI for summarization or playbooks or things, I think there's a danger of saying, oh yeah, that's all X, they were oversold or that's all adoption. They're always oversold, by the way.

Right. So if we can dig kind of one layer deeper into that, you're gonna get actionable things that you can work on as a business, right? And so maybe it contributes to an adoption problem or it could be oversold, but how did that surface or what is that?

So avoid using AI just to use it and get to an end goal, but how can it help? How can it really help the business?

[Speaker 3]
Yep, that's incredible. Not just harnessing it at the highest and aggregating, but actually now's our moment to go deep and really get to the root and not over automate, but find real moments where we can engage and bring in the team based on their superpowers to get them to customer outcomes. Well, thank you all so much.

We'll get to questions here in a second, but really appreciate your insights. I know I learned a ton and look to go on treasure hunts with all of you one of these days, but appreciate your time. Let's give them a round of applause.

And so as James said, feel free to put your questions in the app and we'll get to some questions for this crew. Don't see at all. Here we go.

Fantastic. Okay. And you can vote on these as well.

And if you vote them up, they go up higher, but let's start with the first. How important is NPS as a touch point in the journey? And should it ever be treated as a North star metric?

I want to take this one. Put my poker face on.

[Speaker 2]
I'm happy to talk about it. I love NPS because of the information it gives you to act upon, but I'm less concerned about your score and more whether it's moving up or down. So different organizations I've worked in, the same organization, but different countries have different approaches to how they will score somebody.

And so that's always my, it is a very good metric, but what I love is just what you do with it. For us specifically, the role I'm in at the moment, it's embedded in that voice of the customer. You said we did.

How do we take NPS, get customers to vote on some of the things that come out of it so they can really see that their feedback is impacting the product and the journey that we're taking them on?

[Speaker 4]
I would just add, I think it's a signal, and you should have some kind of closed loop process on that, especially if they're verbatims, if customers take that time, but I would not say it's a North Star metric for us.

[Speaker 1]
And it should never be surprising to you, like knowing your customer base and being into some relationship to always kind of be able to relate to if the NPS is actually in line with your gut feeling or with your own impression. And I think it's also very important to differentiate or to try to see where is this coming from and question it and not just take it as a result.

[Speaker 3]
I heard a great Jeff Bezos quote recently of him saying, asking about how he makes decisions. He said, if the data and the anecdotes disagree, believe the anecdotes first and go deeper. So I love that.

There's a metric to it, but there's also context to it. And does that context give us anything additional? All right, can you share your number one use case where AI improved the customer journey and increased quality, quality of team, quality of interaction?

[Speaker 4]
I can start. I would say ours is probably product support. So you mentioned a deeper story on that, but that ability to have a better initial search and then a handover.

So carrying the information, customers don't have to repeat themselves. It's great. Anyone else?

[Speaker 3]
What's your favorite use case these days? Motion, moment.

[Speaker 2]
This is probably an internal AI tool that we use for our teams where it scans all of the call data, meeting data, all of the information that we've gathered. We've only just started using it and it's helping our CSMs to manage a large number of customers more professionally and to be able to understand where they need that high, low touch potentially, whereas before it was just literally who was screaming the loudest. So it's giving us some insight there and increasing the quality of those interactions.

It's early days, but so far, so good.

[Speaker 1]
Not much to add, like efficiency with self-service, but also playing with open cards is very important here that customers know like, okay, this is not, or within self-service, I'm talking to an AI, which they sometimes really appreciate, especially also in the academy. We have videos for our solution implementers and the customers, but we also have the opportunity to chat while they are watching a training video and getting to the right point and timestamp within the video if they want to solve something. So this is really, I would say, one of the benefits.

We got a lot of positive feedback here.

[Speaker 3]
Yeah, that's great, that real-time engagement.

[Speaker 1]
Yep.

[Speaker 3]
All right, let's talk about, I saw one pop up, but I'll come back to it. Okay, we'll go to the next one. What are the unrealized over-automated points in the CS journey?

Anything over-automated right now you want we could redo?

[Speaker 1]
No, I mean, we tried out things and we left them again if they didn't work or if they were not, they didn't prove the value we wanted to have, but that's very individual.

[Speaker 4]
I would say we have a lot of automation that may, there's an adoption signal that comes in and we're trying to nudge a customer to do something. I don't know if it's over-automated or not, if you just counted the emails, it probably looks like it's over-automated. But there's a lag, right, in somebody, an interest in something and an actual trial or adoption.

And so we're trying to understand that better. Sometimes you don't know what actually pushes the customer to take the action. Yep.

[Speaker 2]
Complex systems. Yeah, I think you're right, we're just overexcited by the amount of data available to us. Plugging it all into AI.

Yes, let's do that. Automation of information coming to us.

[Speaker 3]
Yeah.

[Speaker 2]
And make the decision. And then it's a new thing next week. Can be exhausting.

[Speaker 3]
It is. Okay, do you still use success plans and account plans? Pablo, I know you mentioned account plans a couple minutes ago.

And have you dropped one in favor of the other? Do they still exist?

[Speaker 1]
Yes, but very different than in the past and not how I learned the customer success plan has to be. So it lives in our system, it's very, it changes basically every second whenever there's a communication or an external signal or internal signals. So more or less like a dashboard.

So maybe if we can move customer success plans or account plans more to a dashboard style, but some things still live in kind of a max five slides like having the org structure or anything which is a little bit more solid, which doesn't change like every day. But I would rather say dashboards, but we use them to replace more or less customer success plans or account plans.

[Speaker 4]
I like it. We still have success plans. And interestingly, we recently released kind of a initial success plan that's generated in part by AI, personalized and available in that online hub of resources.

So early days and seeing how many customers take action on that. But the goal, particularly in the long tail of customers is to have that interest and envision are you aligned long-term so that we can build that with you. That's incredible.

Yeah, and we gamified it. So we're hoping that helps. We'll see.

So it's visualized in your community, the CS? Yeah, so they can walk through a short process to get this document. And again, it's just kind of a condensed intro to a success plan.

And they essentially get points if they go through those steps. So that's the gamification piece.

[Speaker 2]
Oh, I can't top gamification. We've got a company. Yeah, I mean, similar.

We've got plans for each of our customers. We've got the goals we want them to achieve. We've got scorecards for each of them.

Specifically, our enterprise customers are acting in similar ways. How do we actually benchmark them against the things that they care about rather than our own metrics? But our CSM team only looks after our top 5% of customers.

95% of our business is unmanaged, which is, yeah, scary. But we're trying to look at how do we use AI to now extend those report cards to the rest of our customer base so that we can drive different behaviors. And then I'm going to ask Jessica to come gamify it for me.

[Speaker 3]
That's amazing. You know, we're going through an exercise of rethinking both success plans and account plans internally at Gainsight. And the sort of analogy I use with the team is we used to have a map, there used to be a road, and places you would stop, and you would move a customer along the road, or at least we thought there was a road.

And these days, all we have is a compass. So we need to know how far, close, or off are we from potentially the path. But ultimately, do we know where we're going?

Do we know the outcome? So in a compass world, plans, we have to hold our hands a little bit more. We have to be a little bit more open, but we probably have to talk about them more often and realign each other.

[Speaker 1]
And if I can add to that, because it also inspired me, it's like I mentioned the dashboards and some slides, but still also we have specific prompting. We pull up either every second month with certain accounts or before we engage with a certain account that we also get pointed to the right info we need at this point of time. So it's like the direction of a compass.

But also having the info ready whenever I need it and not being in charge of maintaining it, just that it's maintained.

[Speaker 3]
Yep. Treasure hunt. Not having to go on a treasure hunt every time.

Perfect, okay, last one. We'll keep it quick. What skills do you think we should train our CSMs on now?

I'll ask each of you to pick one. What's the current skill of choice?

[Speaker 1]
Soft skills.

[Speaker 3]
Yeah.

[Speaker 4]
The consultative, yeah.

[Speaker 2]
Hard soft skills. So being able to challenge and to negotiate, I think. CS has maybe become a little bit softer over the years.

We're all about taking people kindly on that journey, whereas actually, I want you to do that, but I want you to be able to tell them that they're a piece of shit. In a nice way. Armed with data, armed with context.

Yeah, exactly.

[Speaker 3]
Incredible, well thank you all so much. We appreciate your time and all of the insights that you brought to today. So thank you so much.

[Speaker 1]
Thank you, Taylor.

[Speaker 3]
Thank you.