B (2:13)

level here and what I touched on in the intro, just moving from solely observation. I mean, observation certainly is still important, but moving from observation to action. And why don't we start with FullStory's acquisition of Ustaful? A lot of companies face that build versus buy decision when they're deciding to expand their platform.

A (2:34)

What was the strategic thinking at Fullstory

B (2:36)

that made acquiring a company the right move to accelerate your roadmap, particularly in this area of in app guidance.

C (2:44)

Absolutely. Well, let's break that down a bit. You know, ultimately I think there's a build, buy, partner equation that companies go through when they, when they're answering this question. For us, we wanted to start with the customer in mind and really in turn their customers understand the outcomes that they needed. And once that vision was locked, we really thought about how is it that I can actively and organically activate real time behavior into something that matters for an end user. Everyone that we work with, from engineers to product to support to the marketing teams, they really want to make this about the end user interacting with their digital platforms. And that's really what this allows us to do, allows us to understand what's happening and then turn out really meaningful data in a way that helps the customer achieve the outcome they're looking for.

B (3:33)

Yeah. And that a big part of that meaningful data is closing the loop right between identifying user friction and resolving it. How does combining that deep behavioral data with the ability to deploy no code guides represent really a fundamental change for how modern product and CX teams should operate?

C (3:55)

Well, I think it's all about that context and the immediacy of the context. With no code guides, you have the ability to take the moment, the literal customer's interaction, understand what's happening, whether it's positive engagement, whether it's a new user, whether it's friction that's occurring, we can understand that in real time and, and activate a meaningful response that's based on the end user. It doesn't feel generic, it doesn't feel like it's for everyone. It feels very specific and unique. And I think as people have been engaging more and more with solutions these days, they expect the solutions to listen to, learn and guide them. And that's exactly what this allows us to do.

B (4:36)

So with these new capabilities, then who's the primary user inside an enterprise? You know, is this a tool for product managers, marketers, CX teams? You know, how do you, how do you see it kind of maybe breaking down some of the operational silos that often exist between these groups?

C (4:55)

We love it. I mean, we use this ourselves, so we're our own case study, really. It's fantastic. So what's nice is the tool is set up in a way each of those teams that you mentioned. So CX teams, the product teams, the engineering teams even can see and interact with the solution. What we do is we do a pretty significant focus on what does a high quality customer experience look like? What are the beacons of success? What are the beacons of challenge? And along that pattern we identify moments where we may be able to help the end user. And what's beautiful is each of the teams have the capacity to build and operate their own guides or their own surveys. But we do harness them into basically a bi weekly review where we decide how much content's going out, who it's going to go to, how long it's going to run, and how we're going to assess the impacts. That's pretty fun to do.

B (5:45)

So I mean, in essence that is helping to. I mean, everybody has a piece in that, to your point, but it is helping to break down some of those silos, right?

C (5:55)

Absolutely. Helping to break down some of the silos. Because a couple of things happen. One, a lot of organizations have stated truths, they have things that they believe to be true. But when you combine fullstory with our guides and surveys, formally used to full solution, you can start to work with observed truths. And what I mean by that is because we can actually see every single session that happens, you can not only understand when the guide is firing based on what context, but you can watch how the end user interacts. You can see how deep they're going. You can see when they abandon both the product itself as well as the guides themselves. And it really takes you down a path of not just what I believe to be true, but to the true observational truth, which is backed by forensic detail that I think people are missing today. And it also can, Greg. It can be uncomfortable because it's not always what you expect it to be.

B (6:46)

Yeah, yeah, definitely. Yeah. And we're certainly not running short on dashboards and analytics and stuff like that. But maybe one way to do this. Can you walk us through a tangible example? You know, maybe A team uses FullStory to identify a common drop off point in a user journey. You know, what does this look like in practice?

C (7:08)

Yeah, this is the best part about guides and surveys. So what does it look like in practice? Well, what we've done is, you know, this is specific to a SaaS company such as ours, or SaaS and AI company such as ours. And what we've done is we've broken our end user experience down into, you know, four essential phases. The implementation phase, the adoption phase, the value phase, how they're using it, and then a growth phase inside of each of those particular functional points in a customer's life cycle. We've identified beacons of positive use and beacons of negative use and we actually use the guides and surveys in both circumstances. So if it's a new capability for a particular Persona or going to really push them down this path of hey, did you know that you can do this with the data? Now if it's a negative use, meaning people are using the solution less and we believe we understand the why behind that, then we can use the surveys or the guides to say, did you know this is possible? Here's what we can do and here's a link to a video or to a help guide to help you achieve it. So what this does is it allows us to understand the Persona, it allows us to understand where they are in their journey and allows us to very micro segment moments that kind of matter to people based on the actual session that was happening to them. And I think what this means is it feels hyper personalized and it kind of starts to lead you into you got to heal the moment when people experience friction or you need to seize the moment when people experience engagement and they're really positive with something.

D (8:41)

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A (9:45)

So let's talk a little bit about measurement.

B (9:47)

And I would imagine there's a million different use cases and therefore a million different metrics that can be solved. But you know, maybe, maybe give us an example of, you know, when a team implements a guide to resolve a friction point. What are some of those metrics that a team should be looking at to

C (10:06)

measure effectiveness I think this is what matters the Most. So at FullStory we adhere to a concept known as say, show improve. So any software vendor can say they do great things, sometimes they can show them in compelling demos, but, but it's really proving that matters. And so here's how we go through the process of proving the efficacy of a guide or survey. Okay, so you know, one I mentioned, the Personas, we, we break our customers into the different Personas. So that's important. So the first thing we'll measure is users that were impacted or interacted with. Well for surveys, we'll look at things like open rates or click rates. For flow completion on a guide, we'll look at percentage of people that completed the entire flow. If not the entire flow, how far did they get? And that becomes a very big indicator of is it working? Well, we'll also assess the total in our case as a SaaS and AI company, the ARR touched by said guides. And the other thing that we'll look at is how many different campaigns were we running that worked, how many campaigns that we were running that didn't work. And what this does is it helps us give direct feedback to the product managers or to the digital success team. This was working, this didn't work. You didn't collect the right insights and I think those are powerful. But number of users, open rates, the completion rates and then the total ARR touch is a good way to just get your hands on the efficacy of the solution itself.

B (11:33)

Yeah. And I would imagine that in some cases we're talking about making micro improvements as well. And so certainly the, we all know if we can reduce friction overall, we're going to get more, you know, whatever it is, we're going to sell more widgets or you know, whatever the, get more subscriptions, whatever the case may be. How do you, you know, initially, how do you make that business case that improving these micro experiences are going to lead to things like customer lifetime value and you know, some of those, some of those larger KPIs that these teams are also being held to.

C (12:09)

I think, I think the, the art. We partner very close with our finance team and the art of connecting a given segment of users and Persona of users tied to the, the what you run. It is possible we saw in one of our particular segments about 11% improvement in GDR. 11% improvement in GDR. And we really believe that is based on the fact that we engaged with people at those right moments and we gave them new insights. And I think what it also did is it Makes that user feel like, oh, this is a company that understands my role. This is a company that understands my problem. This is a company trying to help me do my job faster or better. And I think when you hit that union, we see the spikes in usage just go way up. And we've seen, it's been fascinating because again, it's an observable truth. You can see who was engaged with, you can see who engaged and you can actually see the improvement over time. That's pretty powerful.

B (13:07)

Yeah. So thinking out, you know, months and maybe even years ahead here, this seems to point to, you know, first we were just observing and then taking some set of actions at some point whenever we could get it in the product queue or whatever. Now we're talking about much more actionable responses. Are we moving towards a time when digital experiences almost become self healing automatically, you know, based on some of these, these real time observations?

C (13:40)

We are, I mean let's just make it simple. It look it it we are and I think it's, it's really this, this union of intelligent digital experiences. They're going to be powered by human context. Okay. Whether that's an agent or a human by the way, won't matter. But the context of what the human or an agent is trying to achieve is going to ultimately deliver the intelligent experience. And this is precisely what we're working on. It's not just the fact that we can observe and understand what's happening, it's all about the speed and it's also about the data openness. So with FullStory you can capture the exact thing that's happening with the user on the experience. That data is then accessible via API and mcp. It can be connected to a. We have many customers doing this to their preferred LLM or data bridge to a set of LLMs. And we can help them identify what exactly is happening to a user in the exact moment within seconds. So think about that. It's the real problem happening to a real person or real agent, but a real person, let's just take it down this path. A real person. And you want to see difference. You want to help them solve a problem and you don't want it to be generic. Right. So the only way to do that is to really take that context that only can be created by the unique user flow that a person traverses. You want to be able to take that, understand what they should be doing, identify the right level of intent, and then immediately suggest back to them what to go do or at least engage them right in A two way communication and this is where it's fun. We have some customers doing some amazing things, Greg, as you can imagine. And it's very unique because it's not about who the user is because it's user xx4416. We don't even know the person. It's just more about what's that intent, what's the objective and how can I capitalize on that, not just hope that they'll follow the right path.

A (15:32)

Right, right.

B (15:33)

And what you've touched on already, there's a lot of AI stuff going on behind the scenes. I would imagine you also touched on a little bit where we're not just talking about human users as users of these applications, we're talking about agents. And consumer adoption of AI is increasing pretty, pretty quickly and pretty dramatically. And so you know, we've got this agent to agent world as well. But you know, so whether it's UX or AX I guess they call it, you know, all, all of these things, there's friction and all of a hundred percent.

C (16:11)

There's, there's, but there's inherently when you do anything in any application, you know, whether it's the tool you're using to run this or it's a slack that's going to someone else or you're inside of one of your tools, you have a goal and objective, you have a path that you're working on. You're typically one of many in a cohort. What we've been observing is in a given cohort, whether it's 10 or 200, there are certain patterns that develop. It's and I hate to say this, I know the product managers out there won't love this, but it's never the golden flow, it just isn't people, people follow the paths that they figure out. What we need to do is help people and we need to in organic ways nudge them towards like outcomes that they're anticipating. And this is what really where we see guides and surveys ultimately being it's not just about the guide or just about the survey, it's about taking that context, understanding the goal and nudging the person into a way that gets them to the outcome faster. It does two things. One, it gets the product managers, engineers, CX teams pretty happy because people are doing more in the tool. But two, the most important is it's the most rewarding for the end user. Right. The end user again agent or human is going to want to get to the outcome they were asked to get to. Right? So if it's paying an invoice or if it's evaluating some sort of rfp, they need to get through that process. And if we can make it simpler, faster, easier based on exactly what they're doing versus the preferred path, then you've just kind of leapfrogged or curve jumped around some complexities that just are hard to get past today.

B (17:43)

Yeah, yeah. Love it. Well, Jason, thanks so much for joining today. Got a couple last questions as we wrap up here. First, if we were having this interview one year from today, what is one thing that we would definitely be talking about?

C (17:57)

I think that the self healing concepts start to materialize, it's that we find that context, we can rapidly use it to drive meaningful impacts right in the real world. Today we like the concept in Instagram in our personal lives to just scroll through. But if you think about it, or maybe you think of your favorite TV streaming service, they do a good job of getting you the data you want. Right. In the end, I don't think the software that people use or that agents use is going to be that much different. We should be able to understand people's intent, understand people's objectives and navigate them to successful outcomes at a faster clip. And I think that's what we'll be talking about is how we've kind of gone from design and all these sessions to listen, understand the context and guide. And I think that's what's going to happen.

B (18:49)

Nice, nice. Yeah, we'll have to talk about that

A (18:52)

next year then probably six months.

C (18:54)

Greg, let's do it in six months.

B (18:55)

Yeah, fair enough. Yeah.

A (18:57)

Great.

B (18:57)

Well, last question for you. What do you do to stay agile in your role and how do you find a way to do it?

A (19:03)

Considering consistently.

C (19:04)

Oh man, it's. I, I think it's first to do a lot of reading, generally end of day, very beginning a day to start and end. And then I think a lot of it's podcast like yours, it's listening, seeing what's going on out there. And then it's conversion. What I mean by conversion is two things. So if you read something, listen to something, that's interesting. But how do you convert it? I think the first thing you do is you play, have a test with it, run with it. You've got to be curious enough to be curious enough to play it. If you're not playing, that's a problem. And then after you play it's then you got to act and it's, is this meaningful? Not meaningful. Make a decision, make it part of your routine. And I think those are the kind of the four principles that I go by read, listen, play, and act. And that kind of helps me stay stay abreast of what's happening.

B (19:47)

Oh, that's great. I love that. Well, again, I'd like to thank Jason

A (19:51)

Wolf, President at fullstory, for joining the show. You can learn more about Jason and FullStory by following the links in the show notes. This episode is brought to you by Tech Systems. They're leaders in full stack, tech services, talent solutions and helping companies put it all in action. You can learn more@techsystems.com that's teksystems.com and thanks again for listening to the Agile Brand podcast. If you like the episode, hit subscribe and drop a rating so others can find the show too. And if you're interested in consulting, advisory or work, or if you need a speaker for your next event, feel free to reach out. Just visit GregKilstrom.com that's G R E G K I H L S t r o m.com the Agile brand is produced by Missing Link, a Latina owned, strategy driven, creatively fueled production co op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. Until next time, stay curious and stay agile.

C (20:54)

The Agile Brand.