3 Digital Insights to Win & Retain Loyal Customers of All Sizes with Fullstory CEO + CMO

Scott.

Hey everybody, thank you, uh, for finding some time for us today. Kirsten and I are gonna walk you through a few intro slides and then hopefully spend the majority of our time in Q&A on topics related to Insights to Win and Retain Loyal Customers. Kirsten, you want to talk?

We're really excited to be able to host this conversation with you today, and to that point, We're gonna talk about best practices, but hopefully also learn from you what is going on within your organizations. But we'll start with why some of us are all here today, right? I think it's kind of obvious, even, you know, Gartner data suggests from a forecasting standpoint, SaaS is taking off again. So we're reemerging into this age of hypergrowth. And if you've been watching valuations, then I think you'll see that that is being reflected in the market as well. But the other reason that we're all here today is because this situation, this slide right here, and this dynamic is all too familiar with all of us. It's on fire. SaaS is on fire and growth, but it's getting ultra competitive. It's so much more crowded than it has ever been. And it's continuing to get more crowded as we grow, which is why these stats are very important and kind of the backdrop for what we'll think about as we get into this idea of knowing your customers. If you're on kind of the SMB or product-led growth side, then you know that, you know, roughly 25% of conversion from trial to paid customer is a benchmark that you'd be looking for. If you're more on the enterprise side and selling into enterprises, 1 to 2% conversion rate from a qualified lead to a win. And Scott and I both know this in our roles. Those are tough numbers to achieve, but then layer in this sort of 5% churn, that would be best in class. And for every customer we win in this hard-fought battle, it's the opportunity to lose them is really, really high. All that to say that we know that right now competing on digital experiences is pretty much the battlefield. And you may have the best product out there, but if you're not able to drive value for your customers quickly, or if issues in the digital experience, either in your application or on your website, are causing them to fall off, leave, not engage with your offering, you're not going to win. And that means that understanding customers and understanding the why behind what their behavior is is more important than ever. So I think, Scott, we've got a question.

So listen, if it's just Kirsten and I talking to you guys the whole time, it's not going to be that exciting. Here is the mini-billion-dollar question. How well do you understand your customers? So just stick it in the chat, if you would, really quick. Let's say on a scale of 1 to 10, where 10 is you truly understand everything there is to understand about their customer, your customer, when they visit, right? Are they having a good experience or a bad experience? Are they happy? They confused? They engaged? You know, on the flip side, you don't have the lights on. You don't know whether they are here or not here. Wilton with the 7.2 is a solidly precise answer, by the way.

I love the precision as well. Wilton, thank you for being the first to answer. I see a Dave, I see a Carolina. Don't be shy, you guys. If we only have one 7.2, then that either means we're all hiding something or we've already put you to sleep. I'm not sure.

Don't make us Socratic this.

I know, Scott, when you talk to customers and sort of prospects, what do you think their average number is?

You know, um, averages are tricky, Kirsten, but I would say that You know, in the early days of things, most companies were at about a 2 or a 3, and what they understood about their customers were they visited the site, they understood what pages that they were hitting on the site, and then if the customer wrote in with a support ticket, they got a little bit more color commentary. I'd say over the past couple years, we probably see that shift up a little bit to a 4 or a 5. But there's still a lot of room to go to fully grok not just a customer's experience, but every customer's experience.

I agree. It sounds like— it looks like our audience is there too. Between Dave, Jay, we've got— we're probably averaging in the 5s here. Wilton, you are still in the lead with the 7.2 and that precision. But yeah, the 0.2, the 0.2 that puts you on the top. Awesome. So I think that actually paints an appropriate picture for what the reality is, right? I think we would see 4s and 5s are pretty common out there, and that means we all agree we've got a ways to go. And, but what's interesting is it turns out that most of us are still doing it the wrong way or doing it the old way. The old way that companies engage, right? They use basic analytics or they did some surveys to get a little voice of the customer data. 70% don't do more than that. But unfortunately, most of your customers don't answer surveys. 91%, they leave without complaining. They leave without filling out that survey. So So how are you going to get that data at scale? Because knowing what is wrong and really understanding it is important. So for, for most SaaS leaders right now, if you're not doing more than that, customer behavior and experience is kind of a black box, but it doesn't have to be. And that is essentially what we're going to talk about. We are going to talk about how you can access those insights and what some best-in-class companies are doing and things that you could be able to learn from them. So we'll jump in with today's discussion. And I'd love for you to be thinking about this as we go, because we probably have 5 more minutes of material before we ask you how you're doing this, what you're learning from kind of your insights, where you're struggling, and how you're sharing those insights across your organization. But we firmly believe that there are 3 key digital insights for SaaS companies to be effective. And they're not rocket science. They start at the beginning, right, with buyer's journey insights that you might be looking at. On your webpage, on your single-page app to understand conversion into those customers. Then leading SaaS companies are using product adoption and usage insights to understand where are customers getting value from a product, or more importantly, where are they not getting value? And then the third is really often unsung, but many brands aren't yet thinking about this unsung hero of using those same types of modern tools and insights to think about customer engagement and support to really drive that retention metric that we all worry about. So let's dive into the first one. What does it mean to be improving the customer's journey with insights in that buyer's journey? I think I'll start with saying that most of you are probably in the camp of, I've got Google Analytics or Omniture, I've got an A/B testing tool, I'm good. And those tools are critically important. They should be part of every digital team's tech stack. But what they simply do is they tell you a lot about what. They tell you that, yep, from point A to point B, they didn't go from my blog post to my trial. They didn't go from my trial to convert, but you don't know why. And that inability to understand the why is what limits you from really being able to solve that problem. So how would you actually investigate further and learn more about that drop-off? We believe that there are a number of heuristics that are now available to companies like you to think about that. That could be things like rage clicks, which is like, I'm mashing the mouse. Because it's not doing what I expected it to do. Dead clicks. Maybe there's an element on your webpage that people expect to go deeper on, right? They want more information, but it doesn't go anywhere. Gosh, maybe you could help them with some more content. Or even, there's a new signal that we just launched yesterday called pinch and zoom. Imagine this, right? Someone's pinching and zooming on a screen. Probably means that the image that you're sharing is not big enough. They're looking for more information again, but your site isn't satisfying to them. So it's not enough to know from your existing tools, that someone bounced or that someone fell off in a funnel like this, it's really critical to know why. So let's talk about an example, right? In each of these cases, we'll talk briefly about how are brands doing it. Greenlight is doing this in practice. If you're not familiar with them, they're an Atlanta-based fintech company that makes a debit card for kids and then a companion app for their parents and family members to participate. In the app, family members can do things like set savings goals, set allowance targets and help them make financial decisions, which I think is really cool, getting kids financially literate very, very early. And we work with their growth team, right? So akin to any PLG team at other organizations, this team is focused on increasing app conversion, sign-up, and engagement. And they were using FullStory on their web property as they were looking to try and get people to sign up. And one of the things that they observed was that people were rage-clicking and dead-clicking on the MasterCard logo that you can see here on the screen.

Right?

And so it was like, well, why, why, what are they doing? Well, go back and look at some sessions and understand what's happening. And it turns out that what Greenlight had designed as a simple trust mark, people were perceiving as a need to make a choice. They thought they had to pick, oh, I want MasterCard or I want FDIC, when that was not the intent of the site at all. People were dropping out of the funnel just because of that one simple thing. So they did an A/B test using data that we fed to them. And guess what? Removing the MasterCard logo improved conversion 7%. That's huge for something that was ultimately very, very simple. But the reality here is that if they'd had only the what data, that people did not convert at that stage, they might have been left thinking, you know what, people just aren't willing. People don't trust us. People aren't willing to use a financial application for their kids. And it turns out that a large percent of the problem was a simple UI issue that getting that why data was really critical to the insight. So that's kind of a top of funnel, if you will, example where a SaaS company is using these types of insights. But let's talk about in the app, right? This is near and dear to all of our hearts. And what, once you've secured those travelers, once you've secured those users and you've got them engaged, you want to know why are they using your features? Why are they not using your features? Who, right? Here's an example of a persona-based dashboard. Which types of users, what cohorts are actually thinking about and getting value from your product offerings. We ourselves are obviously a SaaS company, and we think about these things every day. And in fact, yeah, that idea that knowing someone dropped off without the why is anathema to us. So we, we use these types of tools all the time. And actually, Scott's going to talk to us about something that FullStory did last fall when we were thinking about how our data could help us inform and improve our application.

So for, for every SaaS company, to state something pretty obvious here, feature engagement is key. You spend so much time, engineering dollars, research hours to build a feature, but a lot of the times as soon as it ships, you kind of turn your back on it and, and move on. Um, and so we thought we'd share a true story about a little bit of an aha moment we had out of the intersection of understanding, using product analytics and digital experience in the intersection of those two things to truly understand some improvement opportunities for us. So we had launched a new and very important feature for us, Reed, expensive investment of engineering time last year. And so we set a company-wide goal of driving deep adoption, deep and continued adoption with our customers on this new feature. And so out of the gate, we were seeing adoption. Yay! But it was slower than, than we wanted to see. And so what we then did was have our customer experience team dig in and start building cohort-based funnels and analysis to understand, understand where the groups were sort of trailing off and not engaging as deeply as we would like. Then using experiential analysis, We sort of popped in and looked and saw that it was really a lack of clarity on how to use the feature the way that we expected them to do that. Turns out users don't actually engage the way you think they're going to. So what we did see though was that when we launched some new training, there was an uptick, but we didn't stop there. We then analyzed the new cohorts and watched those groups of users as they interacted anew with the feature and the training content. And it turns out that we were, we were seeing users tab back and forth from the product to the help, from the product to the help, and the content of the help was too text dense. So there was a lot of scrolling and there was a lot of mousing to understand that interaction. We then iterated to make the help much more screen-heavy bulleted out, and that really saw an uptick in adoption the way that we wanted to see. So much so that we saw 75% increase in successful usage of that feature in a 3-month period. Now, if we had just shipped it and forgot it, it would have never moved the needle. So don't fall into that trap the way that a lot of companies do. Kirsten, back to you.

Yeah, I love that example. And for me, what's so interesting about it is this intersection of product and customer success to arrive at the ultimate value that we want our customers to have so they retain, right? So let's talk about then, this transitions greatly to that, that last point, 5% churn. That's what a best-in-class benchmark is, but we all want less than that. How can we do it? Too few brands are actually using these same types of modern tools to understand what's going on in support. Why do we get so many calls on this topic? Is this bug real or is it just Poor user design or weird user behavior. Those types of things are just, again, critical. And having your teams all across the organization think about these questions and have that curiosity and access to data is critically important. So here's kind of our final example. It's from a company called Sendoso. Some of you probably know them. They are a sending platform that really helps bridge the sort of physical and digital world in sending gifts and assets to engage folks in the buyers and retention journey. And they're using FullStory to understand understand first at scale, what are the top issues, right? Stack ranking. You can kind of see right here how many bugs or issues are affecting users. How do we then stack rank and prioritize them? And what their product managers are doing is checking out these issues, prioritizing them by how many folks are being impacted, and then going to look at them in sessions to see if it's a real bug or not. And they're only then progressing those to engineering that are real bugs and that can be solved in that way. And they've saved endless engineering hours, not investigating stuff that was sort of spurious. But in the event that it does keep going, right, and there is something that sort of elevates all the way to a customer care call, that same data, that pinpointed data is being used by their care team to do live cobrowsing. So Scott has an issue in the Zendesk application and he's really frustrated. He calls customer care. Customer care can identify where he was, really look at it together with him and help him solve the issue. They've moved from sort of a very reactive stance to a very proactive stance. That's made a big difference in their business. And it's something that you all should be keeping in mind, right? Don't forget in the last stage to use these same types of heuristics and analytics. Which brings me to my final point before we wrap it up and open it up to you. So get ready, get ready to unmute and the like. All of the data that we've talked about today is necessary, but it's more important that you share it across the organization than almost anything else. Right? These are not data points only for PMs, or only for UX and CX folks, or only for engineering. Finding access to, you know, whichever tool you decide to use in the market and whichever platform makes sense for you, ensuring that you're democratizing access across these teams is the only way that you will get the full value across that entire buyer's journey that we talked about. So to wrap us up for today in terms of the points that we think are important for you, Given how much experience is the battlefield, right? You might have the best IP and the best product, but if your customers can't get value out of it, it does not matter. You need to move past surveys, past basic analytics to really understand the why behind what's going on. We think there's 3 key insights in your buyer's journey, in product usage, and customer support. Don't forget that area, super huge for churn and retention. And you need to socialize that data across the organization. If you aren't, then I think activating is very, very hard. We did research last year and we found that best-in-class companies are really doing that across, across the organization. So with that, I know we only have a few minutes left, but we will stay around as long as you are interested. What we'd love to do is I'm going to stop sharing now and we've got a couple of, couple of teaser questions to get you going. But if you have questions already, we would love to hear them from you. Scott, what are your thoughts?

I want to hear what everybody else thinks. Somebody come off. I'll be so impressed if somebody comes off mute and asks a question. Come on, you can do it.

We'll give you a prize.

Yeah, you don't need to give them a prize. Great content, great session. Where do you think people go wrong as they, like, I think it's easy to sometimes like set the goal and get people going, but I think sometimes what gets really tough is trickling down to the rest of the company.

Right.

What have you seen, like tactical tips of like companies that get that right? Like where they get everybody thinking about like growing usage with the same mindset that you've shared on today's call.

We talk a lot about employing empathy, and I know empathy is a pretty heavy word nowadays, but if you, if you think about the sort of the wagon wheel chart that Kirsten showed, Digital experience is not a siloed function within an organization. It is something that everyone has a stake in, whether it's support or user experience or engineering or product managers. And so, stating obvious things, if you put the customer's experience at the center, and then you're able to get those cross-departmental teams empathizing with the customer, That drives action way more than just a chart or a graph will.

Right?

I mean, like, no engineer wants to ship a piece of code that their customers don't like. They get super grouchy about it. And so if you show them an experience or give them a customer testimonial where they're having a hard time, it hits them on a human level. And that really helps drive action a lot of the times.

Yeah. I'd layer in an example, actually. So something that we see people do that brings that to life is, Yep. We've got the dashboard that says the bad things are happening, but then some of our customers do what they call watch parties and they will actually go. It is super painful. It's like cringeworthy. They will watch their users do the bad thing, right? Like mash around trying to find something only. And that makes it super, super personal. I need to fix it. We need to solve this. And that is very compelling.

I'll take it one click further. That's something you can measure. So we used to do a thing called game film where you can count your winces and your wins during these watch parties. And you can say, for this feature, we launched it on such and such a day, you know, dot, dot, dot, how many winces did we experience? Right out of the gate, it's gonna be a ton, but you can try to take that number down 20% over time and not relent until you feel like you've gotten rid of that. Another thing— I'll follow up real— Yeah, sure.

I'll just follow because it's interesting. In early stages, sometimes the anecdotal, the things that like you hear in the trenches, sometimes differ from the data, right? Like, how do you, how do you tackle that problem? Because it's a very common problem, at least from my experience.

100%. I mean, this comes back to the way that you capture and deal with data. And so I, I do think at the highest level, the fundamental flaw that 90% of companies are making now is they are not collecting in a privacy-friendly way the right depth of data. And if you have a sort of a visitor system of record where visitor comes and you have all of that interaction data, you can take the Anik data, if you will, that was a bad experience, and then count how many other people had that same pattern of behavior. It may be a one-off, but if you don't have the data, you can't do the extrapolation to say, oh no, no, no, this is a significant problem. So it can't just be qualitative and it can't just be quantitative. That's— to me, that's the soul of digital experience intelligence. It's the idea that it's both of those things, starting with the visit and then across all the visits and counting those things up.

Helpful? Great.

Awesome.

I couldn't have said it better. What other questions out there? I know we have questions for you guys. I guess, actually, before— I know we're going to wrap really soon here, but if there's folks still around thinking about it, I'm curious about what you think the number one thing is that's stopping your team from achieving this type of insight today. Are there barriers for you? Are they cultural? Are they budget? Are they tooling? Are they knowledge? Feel free to share in chat. Go off mute and ask the question as well.

Resources, timing, small teams.

Resources, timing, small teams. How do you get it all done? Is that really like the question? There's too much to do. Uh, a couple of thoughts here. Ruthless prioritization. Is key. And so, you know, aligning to what you think is going to move the needle the most is the most important thing. It sort of gets back a little bit to the first, the first question, which is, um, the intersection of what is painful and what is going to move the needle from a quantitative standpoint, understanding that quantitative, and then And then scoping the work as best you can to understand which, which are the low-hanging rocks, low-hanging fruit, low-hanging rock fruit, in order to move the needle quickly.

Yeah, I actually like one of the things that we added into our platform in the last year or so is this idea of kind of conversions that allows you to literally assign dollar values to things so that you can both make the business case a little bit more easily, but also see the 10 opportunities and do that prioritization in a bit more bionic way. Versus trying to have to manually do it externally as well. Liz mentions in chat that tools are one of her challenges. I could interpret that multiple ways, either not having the tools— we can help— or I think certainly one of the things that we see very often is too many competing tools and this idea of how do we really align on that single north star, that sort of element of truth, a lot of which is cultural, but also being able to expose data that people feel confident in, right? And marrying the anecdote with the data to say, this actually does look real. This does look true. That's great. Elias Wilton, thanks so much for your comments. Sterling, are you going to kick us out now? Yes. Thank you guys so much for joining this session. We have a lot— we have a lot more great content today, and we hope to see you guys in the next session.

Thanks everybody, appreciate the time. Thanks for attending.

Thanks you all, have a wonderful SASTR.