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Fascinating conversations with founders, leaders, and experts about product management, artificial intelligence (AI), user experience design, technology, and how we can create the best product experiences for users and our businesses.
Kyle (00:00.854)
All right, welcome back to another episode of Product by Design. I am Kyle and this week we have another awesome guest with us, Ryan Glasgow. Ryan, welcome to the podcast.
Ryan (00:12.358)
excited to be here and thanks for having me on the show.
Kyle (00:14.666)
Awesome. Well, we're excited to have you. Let me do a brief introduction for you, Ryan, and then you can tell us a little bit more about yourself. But Ryan is the founder and CEO of Sprig, which is a leading product experience insights platform and works with high growth companies like Figma, Notion, PayPal, Loom and Dropbox. And you'll tell us a lot more about that. And Ryan, prior to starting as Sprig, was a product manager and early team member at five companies that he helped scale from start up.
to successful exit, including Weebly, which was acquired by Square and Verb, which was acquired by Snapchat. So I'm excited to talk a lot more about those, but before we do, why don't you tell us a little bit more about yourself?
Ryan (01:01.158)
It was a great intro and my background's yeah, always been in product management and you know, really started with these companies, uh, all as the first product manager, help them, you know, in many cases, find product market fit and other cases like Weebly, you know, scale to, you know, these eventual exits to acquires. And through that process started to realize and found that common theme of deeply understanding the customer problem.
and really getting obsessed with customer problems and then thinking about how to really bring that user from point A to point B and solve that problem for them. And started a SPRIG and what we do is we help other product teams and product managers and researchers deeply understand their own customers so they can build award-winning product experiences. And we do that through in-product surveys, session replay, and prototype design testing.
and use AI to analyze all that data and make sense of all the data that's being collected so that they can really focus on the fun part, which is building and designing and launching exciting product experiences.
Kyle (02:11.31)
Well, that's awesome. And I'm excited to talk more about that. But before we do, maybe you can tell us a little bit more about what you like to do outside of the office as well.
Ryan (02:26.006)
As a founder, I can't say there's too much free time. I think mentally it's 24 seven at a minimum, but I do have a one-year-old daughter. And so she's been a joy to come home to and spend time with on the weekends. And then, you know, lately I've been looking into some, getting into some hobbies that are a little bit more accessible, the things that I typically like to do fly fishing or skiing. You can't do on a given weekend. And so I've been starting to pick up golf.
and get into that, which has been a nice change of pace.
Kyle (02:59.842)
Very nice. Well, that is that sounds like a lot of fun. So hopefully you'll be able to continue to pick up some of those hobbies, which are very important. Well, I'm excited to dive into some of the things that you talked about, but I'm interested, you know, as we go backwards a little bit in your career and some of your experience, you know, maybe you can tell us a little bit about how you got into technology and specifically product management to begin with. Because
a lot of us get into this field in a lot of different ways. So how was it that you first got into product management and into this area to begin with?
Ryan (03:41.506)
Yeah. Something that I was born into, you know, I can't say that a lot of people have had that experience, you know, being born in San Jose, Santa Clara, and, you know, probably second or third generation. And my, you know, grandparents were working on the orchards in Santa Clara, you know, picking, uh, you know, prunes and apricots and, you know, fruit. And it's certainly transformed since then. And so there are no more, you know, apricot.
farms in San Jose anymore. And they all, it all got replaced with, you know, high growth tech companies. And so the one dot of Silicon Valley, you know, Intel, AMD, you know, Adobe, this company, you know, Apple, Google, and these companies, you know, really kind of popped up, you know, right around where I grew up. So my high school had the shared offense with AMD.
I live right next to the Intel headquarters. My dad worked in tech as well in the hardware manufacturing for companies like Apple. And so as a little kid, you read the, you know, Sunday Business Times, you read about, you know, Steve Jobs getting funding for his new venture Apple. And it's just exciting to really just kind of be a part of that. And so probably around 10 or 11, a lot of my friends would be skateboarding. I'd be skateboarding, but
I found out the fun, exciting part for me was building a website about skateboards. And so, you know, since 10 or 11 always kind of had that passion for bringing ideas and information online and building websites and learning how to build a website to the dreamweaver and, you know, buying a Java book, a 600 page Java book when I was about 13. Uh, and so can't say, uh, a normal childhood to be honest, but something that, you know, tech was really innate.
to how I was brought up and something that I was living and breathing since I was quite young.
Kyle (05:40.378)
Awesome. Well, that's a really great beginning. And I'm interested in how that kind of led to some of these early product management roles at some of the companies that you mentioned because you mentioned being one of the first product managers at some of these early companies like VIRB and Weebly. What was it like as starting as one of the first product managers at some of these companies and scaling up as they grew? I assume...
grew relatively rapidly. What was that experience like? What were some of the things that you were doing there?
Ryan (06:17.65)
For most of the companies that I joined, it was actually too early for a full-time product manager. And so in many cases, I was designing, I was writing code, you know, product management when it's only a four-person company, you know, is more of a part-time role. And as these companies started to scale, the piece that I wanted to hold onto was that product management aspect. And so many of them, I started out in more of a generalist, you know, doing...
writing specs, but also designing those specs, but also contributing code to those specs. And then, you know, I think one of those examples was being Weebly, where I did start as a full-time product manager. They're a little further along than some of the other companies. And you know, it's just something that as these companies grew, that was the part that I was most excited about. The part that I, you know, felt the most passion about is really seeing how I can roll up my sleeves to make this product.
to be as successful as possible. And that meant, you know, that servant leadership of finding out, can I QA the product? Can I write the test plan? Can I do the user research? Can I write the launch announcement email? And really just doing anything possible. And in many ways, helping define product management. You know, when I joined Weebly, it was already a company that was doing very well and they had never hired a product manager before. And so...
You know, my second day, one of the early engineers, more senior engineers comes up to me and asks, why did we hire you? You know, what are you doing here? And so I quickly realized that for companies that have never had a product manager, it's about demonstrating value. And even if, you know, they have had a product manager, sometimes product management can get a bad rap. And so really leading with value, rolling up your sleeves, showing that you'll do whatever it takes for this, this product to be successful.
is how you build that trust you're in that respect. And given that's me, the companies had not had product management before, it's something that I learned to really demonstrate that value and earn that respect and not show up on day one and handing out product specs to be built. That's something that can be off putting for folks. And so as these companies grew up, continue to focus and double down on product management on the role.
Ryan (08:43.966)
And, but also that upbringing did help me realize how to really make sure everyone realizes how critical that role is. Not everyone wants to write test plans and, you know, talk to customers and write QA stories.
Kyle (08:56.81)
Yeah, no, that's really great. I'm interested, what was your response as somebody is like, what do you do here? Or what is your purpose for coming here? Because I've had that same question asked to me coming into early product roles, and I'm interested, how did you respond to that? And how did you kind of handle that mentality of, why did we even hire you?
Ryan (09:21.202)
Yeah, I had assumed there had been some buying already. I assumed everyone knew what I would be doing and you know, why the hire had been made and it just to be, to make this product successful, you know, doing what it takes and I would ask them, what can I take off your plate? Like, what do you not want to do? And you know, particularly in the early beginnings, building out the trust and respect for that function. And in that case, it was thinking about all the edge cases for introducing Google authentication.
Kyle (09:24.403)
Yeah.
Ryan (09:49.498)
the team had not thought about merging accounts when you've already created an account with an email address. And then you also authenticated with Google, how you had to merge the two and deduplicate. And so I quickly jumped in and said, hey, let's look at all the different flows that a user could take with rolling out Google authentication and make sure that we deeply understand and can predict everything that might happen. And then we've actually accounted for that in our engineering efforts. And so came back with something, mapped it all out, reverse engineered what they had done.
identified some key gaps and said, Hey, you know, this is what we also need to build for this feature to be successful and use it to have good experience. And you start to kind of see the aha moment, like, okay, this person, you know, is really going to help pick up some of the things that are currently not being done right now. And this actually is a really critical role for these features to be successful.
Kyle (10:39.23)
Yeah, no, that makes a lot of sense. I think that's really good. So I'm interested, as we kind of discussed your role at Weebly, you mentioned that not only being one of the first product people there as the company grew, but also having several patents to your name and being part of the process there of...
these patent applications and having patents there. I'm interested in that process because I've been part of those discussions at companies before, like, do we patent some of these either technologies or processes? What was that like going through the patent process and the application and then ultimately getting patents granted to you and to some of the work that you and others had done?
And then weighing, do you do this or do you not apply for a patent on some of these things? Like what was the discussion there and kind of the cost benefit analysis of doing that?
Ryan (11:44.462)
I think as folks working in tech, we're just really focused on bringing new innovations to market and bringing new ideas to market and getting those in front of the hands of customers. I think the dark reality is that there is a legal process in place around innovations and there can be scenarios where you come up with something and someone else patents it and then actually sues you for what you came up with. And so at Weebly, we did file several patents.
We often look at things that were first to bring to market. And so the first, uh, an innovation that we brought to market at Weebly, and I was the patent author for this was building a website on a mobile device. And doing that with a drag and drop interface. And so using your finger and moving elements around the screen. And that was something that we were first to market. No one had ever done that before. It was a very difficult technical challenge because we had to build a JavaScript bridge between objective C. The.
Apple, you know, iPhone operating system, APIs and the website, which was all in JavaScript and HTML and have those two sets of, you know, APIs control each other and, and discuss, talk to each other and something had never been done before. And so we realized, Hey, this is something really new. It's really innovative. The worst case scenario is we spend all this innovation budget in R and D efforts on something and someone else several years later comes back and said, Hey, you know, we have this patent.
we're gonna take royalties on every dollar you make from this product. And so usually within a one year of publicly launching something, you have a window. And so right when we launched it, we filed that patent. And about two and a half years later, we heard from the patent office and said, hey, you guys are, you've got this patent, congratulations. You're the first to bring it to market. Something that's very defensible. It is very unique and differentiated. Something that hadn't been done before. And so...
We got that patent, yeah, about two and a half years for the drag and drop interface on a mobile device for building a website. And then when you get a successful patent, you can then expand that patent. And so actually just a few days ago, got a, uh, update from now the square. Team and the patent office saying it's now building a drag and drop interface on a computing device. And so a few years later, probably five year process overall, but a few years later, we expanded that patent.
Ryan (14:08.754)
And I think at a minimum, it's important to be able to at least defend what you come up with and if you're bringing a key innovation, that's going to be core to what you're doing in a market. Being able to at least defend yourself from, you know, bad actors is always a minimum and here at Sprig, you know, about two and a half years ago, we also filed a pretty core patent to our product line and in about two weeks, that's going to be published, which we're really excited about. And so we'll be sharing a little bit more.
then, but against something that we're the first to market, a key innovation, something that many other companies in space now do, that we can now at a minimum say, this is something that we legally invented and can protect and say that we invented this concept. And then from there, whether it would be offensive or remain defensive is some open questions we're having internally, but at least we know that no one can come after something that we came up with ourselves.
Kyle (15:08.382)
Right, right. No, that's super interesting stuff. And like you said, the process is long and can be very, very drawn out. And so it's interesting as you go through, because again, you have kind of that narrow window of you have to make a decision, especially like once you've done it, you have a relatively short timeframe once it's been like made public to decide whether or not you want to file and do something otherwise.
that window starts to close very rapidly. And so you have to kind of move forward in the process. So fascinating stuff. I'll be excited to learn more, especially once more information comes out about what you have done at Sprig. So that's exciting stuff. I'm interested in talking more about...
Ryan (15:49.618)
Yeah.
Kyle (15:59.658)
You know, some of the things that you've done early on at companies, you know, you've both founded companies and been involved very early on with multiple companies, including Extra Bucks, Livefire, GraphScience, Verb, Weebly, and now Sprig. So named off a whole bunch there. One of the most important things, and we talk a lot about this, is product market fit, you know, making sure that you have the, you know,
the right product in the right market. But I won't define that, I'll let you define that. What does product market fit mean to you? And how do you know that you have the right product market fit, especially early on with these companies and these new products?
Ryan (16:45.338)
And, you know, when the first, the concept first came out, you know, by someone Chanel's about 13, 14 years ago, it was very, very early on, it was a very concise, specific definition, which I'll get into in a second, you know, and now someone asked me, Hey, you know, we're scaling to, you know, at 50 million ARR, you know, is that, is that product market fit? It's 25 million ARR. Is that product market fit? It's a hundred million ARR, you know, and Lenny, but Ritchisky, a popular influencer just did a
series on finding product market fit and of the 20 top B2B SaaS companies and Sprig was one of them and it showed us as the fastest to product market fit against one password and gusto and you know, Figma and all these other companies. And someone asked him, you know, how are you defining product market fit? And he said, however they define it. And so you probably have 20 different definitions from 20 different founders on what product market fit is. And it's really something right now that.
Kyle (17:39.406)
Thank you.
Ryan (17:45.114)
has I think become misconstrued. And so we always look at the original definition, you know, by Sean Ellis, and he was a early stage marketer, very similar career pattern with me, where he was joined as the first marketer. But I, you know, I was joining as first product manager. And so companies like Dropbox logged me in. He has a successful track record. And what he wanted to know, whether it's worth joining these companies, you want to market a product that is ready for distribution, is ready to scale, is ready to really ramp up that.
go to market investment. And so he ran a survey and the key question in that survey was how disappointed would you be if this product no longer existed? And so there's a very disappointed, somewhat disappointed, not disappointed. And if you get above 40% for very disappointed, which means that your product is solving a real need, but also differentiated amongst the other options out there. And so if someone is...
not disappointed, it means maybe there's something that is as equally as good, or maybe that you're not solving a critical need. And that really helped him understand whether a product was ready for that marketing scale for him to really come in, roll up his sleeves and say, I'm going to make this a hundred million dollar business. And so at Sprague, you know, we also look at, and we have a template, we have a free gallery of templates for anyone to try out. We have a template around product market fit. And so.
That's what we look at. That's how we define it. Something that we look at on a regular basis to see how our product market fit is evolving over time. And something that I encourage everyone else to also really be on top of and much more critical than net promoter score and some of these other vanity metrics because it really does show how critical your product is and how different your product is with a single question.
Kyle (19:36.158)
Yeah, I think that that's so good and so important. And I really like that. You kind of introduced another idea, and we talked about this a little bit prior to this discussion, but the idea of feature market fit as well. And as ideas and as companies get bigger, it's not so much necessarily about product market fit, but can be much more about
smaller versions of that, feature market fit. How is that similar to product market fit and why is this idea of feature market fit important and maybe how is it similar or how is it different?
Ryan (20:17.818)
Something that we're seeing much more often with our customers, particularly those that are larger, they might have several products, a product, a core product might have 50, 70 specific features or flows, or maybe even subproducts that they have under that product line. And we're seeing many companies as they achieve overall product market fit, you wanna understand the specifics.
of how all those features are performing and which ones are most critical. And we often see that the behavioral data doesn't really tell you whether a product or feature was critical or not. And so if someone uses a feature only once a month, does that mean that it's not critical? It could be a very, very critical feature that performs a very specific task. And if you ask someone, if we take this feature away, would you be disappointed? They would say, absolutely. This is a
critical, critical feature that I need. I think for me, you know, just took a flight home from Cleveland from a conference and downloading the music on Spotify, something I don't use very often. But if you took that away, I would have five hours of no music. And so you think about a feature with low frequency with incredibly high value. And so what we see many of our customers run now, either after a new feature has launched or they really wanna do an audit of all of their features.
is run a feature market fit survey. And it's the same question, but it's asked specifically about that feature. And so perhaps someone has used, you know, Sprigway have very advanced targeting for end product surveys. You can really get and ask specific questions to specific people in specific moments. And so an example of how we often recommend the feature market fit survey is looking at your high value user base. And so the users that...
pay you a little bit more than others. Maybe it's a business plan user or an enterprise customer or maybe a paying user if you're in B2C. And then after they use a feature X number of times, maybe it's after the fifth time they've used a feature, the 10th time I've downloaded music to my phone, it might pop up in the product and ask, how disappointing would you be if this feature no longer existed? And if it was, again, downloading.
Ryan (22:41.954)
music for offline consumption, it would be very disappointed. And we're seeing more and more companies, you know, really want to understand each feature that they've got, not just looking at the usage, which doesn't really tell you how important a feature is, but actually asking about that importance of that feature, and then ensuring that they're investing and improving the features that are the highest value of their customers. And the only way to do that is to ask.
Kyle (23:10.602)
Yeah. You've hit on a point that I think is so important that I don't know that we talk about as much. And I know at least in a lot of my conversations and a lot of my roles, like, I don't think this idea of feature market fit is talked about nearly as frequently. And you've brought up such a really great point that some of the things that we have in our products are can be really, really critical to.
a lot of people and can be really high value things. But again, they're not the things that are driving, maybe the daily activity or like the monthly activity, but they're still incredibly high value things. And I can think of multiple things that I have used. I may use like once or twice a year, but they're so high value to me that are like, I need this. And I have one like.
I have a couple specifically that came right to mind that are like, I use this like two or three times a year, but it is, I need something very specifically for this purpose for two or three times a year and that's it. And I was using a product for it and then they got rid of it and I was like, I have to find something specifically for this because it's so important to me and had to go out and like research products and find something. And like those are, again, you're talking about like...
and it was a feature of a product and I had to go out and find a new product. I had to stop using the whole product because they took away one feature that was so critical to me. And so those are the types of things that if you don't realize in your product, we take away this one feature, it could drive away somebody from the product entirely. And that was my case. I stopped using it entirely, had to go find a new product because that one thing was so critical to me that I needed it in that product.
Ryan (25:02.918)
Yeah.
Kyle (25:03.818)
I love that. And being able, like you said, being able to find out before you drive users away that, hey, if we take away this feature in our product, is it important to you? Yes, this is the single thing that is most important to me in this product. I will go find something else if you do not have it. And knowing that before you sunset it and take it away and drive people out. Like that's...
I love that. It's such an important thing to know. So a great, great topic that we probably don't talk about as much, or at least I know we haven't talked about as much and I don't hear as much conversation about. So I think that's an important thing for us to be talking about more.
Ryan (25:34.747)
Yeah.
Ryan (25:46.478)
Yeah. And I do think that's the challenge of product management is that when you have that home run feature that everyone's using, you know, let's keep investing. You have that feature that, you know, no one uses, no one cares about. Maybe no one likes, okay. We don't have to invest further. We can consider a son studying this, but most of our features, you know, as product teams are probably somewhere in the middle, it's something that people like, maybe they don't love. Um,
And so the feature market fit will help you identify, is it a 20% very disappointed, a 30% very disappointed? But then that follow up question will give you the insight into what you can do to get it to a 40. And maybe it's a 10 to 20, you say, hey, we're gonna let it go. Maybe it's not like that feature that you described, but maybe it is something people don't use often. It's a 30 to 40, we wanna get it a little bit higher. Here's some things that we can do to make it even more valuable to folks. And so.
Looking at both of those together is really where we see the magic happen of really knowing the features that are critical, even if they're infrequently used, like the one you mentioned, but more importantly, understanding the gaps to get the ones that you want to be critical. And what, if anything, you can do to get them there is where you can then think about how to invest your roadmap.
Kyle (27:04.694)
Yeah, absolutely. Okay. I feel like we may need to come back and do a whole podcast on future market fit because I, this, like, I keep, ideas keep popping into my head of like, okay, here's a whole bunch of examples we need to start talking about because I think this is like more and more keep coming up. I will, we'll step away, I'll step off the soap box for a minute and we'll save that because I do want to talk about some other things, but this is.
Ryan (27:12.674)
Hahaha.
Kyle (27:33.094)
you've hit on such a great topic. I do want to talk about, obviously, something that is top of mind for everybody, which is AI. And being such a topic that has become top of mind for everybody over the past year or so, as AI has just become so much more prominent in all of our tools and everything that we're using. How do you see...
AI changing the role broadly of product management both currently and as we move forward.
Ryan (28:12.546)
It's certainly a really exciting time to be a product manager. And I, if you're at a company that has no need at all for AI, I, um, sympathize for you and would slightly or gently encourage you to find a company that has a future of incorporating AI because it is such a revolutionary technology and something that have not seen since maybe the iPhone.
know, something come out and, you know, be really this exciting, and perhaps even, you know, some people are comparing it to the internet, which, you know, somewhere between the iPhone and the internet is probably where it ranks. And it had been something that had been overhyped, you know, for the past probably five plus years. And you'd call it AI and everyone says, no, it's just data
Kyle (28:50.542)
Thanks for watching!
Ryan (29:10.226)
push back on you and investors would say how it is something that's more of a services business because you have a human in the loop and you have all these people behind the scenes actually performing the work of the AI and doing all the complex tasks and how you have low gross margins as a result. But in the past 12 months, thanks to OpenAI and really taking Google's transformer research paper and finally having that breakthrough where
It is something that can take on complex tasks and it can do large data analysis. That does not require a team of people behind the scenes to do a lot of the complex efforts and we are able to now deliver, you know, intelligence and our applications and give very complex inputs, whether it's our products, giving complex inputs for tasks or as people giving complex inputs and getting complex outputs.
is something that has really changed how we build products, how we think about product management, and an area that I think is just really exciting for all of us. And we're still, it's very clear we're in the early days of figuring out how to use these technologies, you know, what the boundaries are, what's possible, what models to use. And so very much a arms race right now from companies selling the pick axes to the gold miners.
but also the gold miners figuring out how to use the pickaxes. And so just this back and forth every week, every month, has been such a rush to follow and also be a part of. And here at Sprig, we had some really exciting AI launches ourselves. But we're also thinking about how we can use our product to help others build with AI. And so we're seeing both of those play out this year in particular.
Kyle (31:02.454)
Yeah, and I want to touch on that because you mentioned at Sprig, you're focused on the in-app and in-products like surveys and playback. So for those of us who are in product management, really being able to see what is happening as users go through and use different applications and tools and being able to understand that.
How have you incorporated AI into that to make the process, I guess, better? Or help those who are analyzing and looking at these surveys and looking at this information to maybe get more insights? Or how have you incorporated it in some way?
Ryan (31:56.262)
Yeah, the founding thesis for the company is really from my time at Weebly, where we were a high growth company when I left, you know, 50 million accounts. And the, there was an unmet need in the world for companies that are quickly scaling to get in context, qualitative data from their customers about what they think in the moment about. A particular feature, like we just talked about future market fit or how to improve an onboarding experience or to understand maybe a trade.
And so from day one, it was really hyper-focused on helping these companies quickly scaling who had larger user bases, collect large volumes of data. And so the first person to join me at Spreg is our head of AI, Kevin Mandich. And so we've actually been working with AI since day one of the company's founding. And we had used the open source models from Google and it was a very different process to work with AI. And we brought on
our own data sets, we did all of our own training, and we had all of the models running ourselves with open source models on our own hardware. And so we had been relatively early, now when you look at how everyone's at with AI, we're relatively early to building and scaling with AI. And the piece that we've always focused on applying AI towards is helping these companies wear a sprig unbiasedly.
the best in the world at collecting in context data at scale, but helping our customers understand that data at scale. And so if you're getting a thousand survey responses in a week or in a day, really making sense of all of that data and helping understand the trends and the themes. And so that's why Kevin joined Sprague as the first person after me to join the company, because that was a piece that he was focused on since day one.
And over the past nine months, we've now switched to different models, and used different techniques. But the efficacy and what we can do with those models is now significantly farther along, significantly more advanced. And that's what's been really exciting is taking something that works really well and our customers are happy to something where the realm of possibilities are far greater from where we were, you know, even just one to two years ago.
Kyle (34:20.918)
Yeah. Where do you see kind of the next phases of that? Because obviously, you know, things have changed significantly since, you know, since you probably started. So how have you seen things change over, you know, since you started to now? And then where do you see things going and changing over, you know, the course of the next little while?
Ryan (34:45.626)
Very similar to building a startup, you know, 10 to 15 years ago, it was, you know, 20 years ago, it was who can, who can build the product that was really, you know, if you could build it, you usually were the winner. Uh, you know, it was very difficult to, you know, bring complex SaaS applications online and, you know, the hosting and the, all the processes there. And, um, you know, even things like Ajax for complexities. And I think with AI.
45 years ago, it was who can build the model? Who can tune the model? Who can get all the data? Who can figure out how to make it work to specific problems? And that's where we were as a company in 2019, 2020, 2021. We had our own administration panel. We had a team of researchers tuning the model, correcting the data, reviewing every response, providing feedback on all the theme analysis. Very intensive, technical, and
labor task. And we're now at a point where the accessibility for AI is something where you can do in a weekend project and you can get access to very advanced GPT-4, 3.5 models. Google is about to roll out their own models as well. That'll be very easy to use as well. And so the accessibility of AI is very low. And that's why there's just this huge rush of AI startups and they all look candidly the same.
because the barrier to entry is so low compared to where it was four to five years ago. And so here at Sprig, we are applying it with a text analysis, theme analysis, and those are some things we've been doing since day one of the company's existence. But we're thinking now about far more complex, more interesting, compelling use cases. And so one we just launched this year is analyzing an entire set of survey data. It's something that no one has been done before.
is a vertically integrated solution where you're collecting large amounts of survey data in context from your users, but also you're at passing SPRG is ingesting all that data into GPT-4 and you can now ask questions about your survey as that data is coming into SPRG. So you can ask about correlations between question one and question two. You can ask about even suggestions on how to improve your product based on the survey data. And so here at SPRG we just ran
Ryan (37:09.55)
understand our onboarding process and some in-product surveys pop up, you know, after you complete the onboarding and we got some really great insights and we asked, you know, in the Sprig interface, it's very conversational now. And our product team was asking, how can we improve onboarding based on these survey results? And it came back with some really great insights and ideas and helped us really think about how to move our product forward. And so as product teams, it's exciting to have a, you know, co-pilot is the word that a lot of folks are throwing around right now.
having a co-pilot to do things that might have not been possible before to ingest volumes of data that perhaps we didn't have the time for or even the mental capacity. And so at Sprig, we're also looking at how to ingest everything in Sprig into the models. And every event, every attribute, everything users ever done in your product and all their session replay data and all their survey data and actually making sense of that with AI.
Those are the things that have never been done before that we're really excited about, and will be launching later this year. And so I think that's where you start to get the real power, the absolute maximum of what's possible, is when you go beyond these more obvious use cases, but think about something that is far more powerful that is outside of what a human can possibly do.
Kyle (38:31.018)
Yeah, you've touched on something that I think for me is one of probably one of the most exciting things. It sounds to me like for you, it's probably one of the most exciting things is to have an, like you said, almost an AI co-pilot to help you as a product manager where it's taking a lot of the things that used to be incredibly, incredibly difficult and being able to say like, hey,
all of this data, let me ask questions about it. And kind of like you were saying, like, hey, how can we improve this part of the product? And so rather than me as a product manager having to go through and say, and look through all of the, both the data and the survey questions and everything about like our onboarding process, being able to just take all of that in and then ask questions into.
the kind of like you were saying, the, well, I guess I'll call it the sprig co-pilot in this case and say, like, hey, how can I improve this? Or where is the most difficult part of our product to use? And being able to get actual answers back and then being able to like almost have like a collaborative session without having to dig in because I mean,
I'm thinking back to some of my experience like five years ago of, you know, digging through like just, just massive amounts of like questions and data and then like trying to pinpoint like, okay, here's the most, here's where I think the most difficult part is of this process. And then like, you know, correlating that with like actual user interviews and being like, okay, yeah, this is, this is it. And you know, matching that and then like going out and testing it. Like these are, I mean, that's like a typical product management process.
If you can make that like a question and answer session based on all the data that you have, like all of a sudden what would take like several weeks could potentially take like a few minutes. And I don't know, like that's an exciting thing as a product manager. And that's kind of, I may be like simplifying it, but that's like kind of the vision that you're painting for me anyway.
Ryan (40:44.482)
Yeah. I think we'll get far better product experiences as a individual. We'll get far more leverage for what we can do, you know, in our time. I know that the CEO of, I think JP Morgan predicted a three and a half day work week thanks to AI. So maybe a little bit too futuristic, but I think it's just exciting to see just how much it's impacting our lives. And at Sprig, you know, we're certainly part of that journey for product teams and they're already letting us know. I now have far more.
insight into that product experience because some, you know, the AI is able to analyze all the data for me. And then I can deeply, you know, again, our vision of helping people, product teams deeply understand their customer. They now get far deeper understanding of that product experience and that customer experience with their products because the AI is doing all of that analysis for them. And they can get very specific on those questions that they have and it's able to process all that data.
and then come back with specific recommendations.
Kyle (41:44.77)
Yeah, well, that's incredible. Is there anything that you know now, looking back kind of on your career so far, that you wish you had known earlier, either as a product manager or as a founder?
Ryan (42:24.178)
can't think of any good ones here. So, might have to pass on this one. Ha ha ha.
Kyle (42:29.802)
Okay. And is there any advice that you would have for anybody who is maybe starting out as a product manager or looking to kind of scale up their career in product management?
Ryan (42:58.546)
I don't think I have anything specific, like unique on this one. Yeah. Let me think about it though.
Okay, what if you just ask about like founding a company? Probably give some advice there.
Kyle (43:11.422)
Okay. Yeah. What advice would you have for somebody who is either thinking about founding a company or maybe starting out and founding a company?
Ryan (43:27.762)
You know, founding a company is something that I'm glad that I took really seriously. It's not something where I was a solo founder, 22 and. Poured my life savings into starting a company. And I know some folks are doing that and right after they're just really eager to be that entrepreneur. I ran through the paces. I put in my time, you know, I joined verb. It was very early on pre-product market fit, you know, as another founder and helped bring that product to life.
won a bunch of awards, got acquired by Snapchat, Weebly, put in my three years, joined as the first PM, helped that company scale to run 400 people when I left. And really just seeing the different parts of building a company, really being a part of other successes, seeing what a well-run company looks like, helping another founder achieve product market fit or scale her own company.
did give me a lot of experience and confidence when I started Spreg. And it was, you know, we were able to get to product market fit, brought in some really exciting early customers, raised a really exciting seed round with the top seed investor. In our series A was Excel, our series B was in Dresden Horowitz. And, you know, they look at all the startups. They get...
probably 2000 pitches per year per partner. They do two investments per year typically per partner. And so you look at the odds and the ratios of being chosen by, you know, a tier one A VC firm. I think it does show that experience does come into play. And I think people even are a little bit shocked about, you know, my Niners fan and Brock Purdy was chosen as the last pick of the draft, but he's now considered a top 10 quarterback. He put in four years in college. He was at Iowa.
You know, as a starter, I think for three years and the person that he beat had played only, I think 12 games in college, Trey Lance. So, you know, he just did the freshman year. He jumped right into the NFL, didn't get the experience more talented, but ultimately is now a third string on the Dallas Cowboys. And so using that sports analogy, I would, I would encourage anyone to just because you can raise a seed round today.
Ryan (45:51.95)
doesn't necessarily mean that in 10 years your company is going to be that home run exit. There's a lot of seed money floating around and I would encourage you to put in the time with the startups, get that management experience, learn how to be a great manager, manage three or four people for, you know, at least two years. You guys have a startup as well. You don't want to learn how to be a manager with your own company. You want to get that experience somewhere else. You want to bring that to starting your company and not have to learn that on the fly.
And so would really encourage folks to put in their time, join companies like Sprig, join a company like Retool, you know, join some of these, you know, uh, these companies that are doing well. Be a part of their journey, be a part of their success, see what success looks like, um, roll up your sleeves. And then when you have put in that time, then start that company and it'll just give you so much better odds, not only of just the first one or two years.
but also really building an enduring business. Something 10 plus years that really has an impact on the world. It's very, very rare where you're a Mark Zuckerberg or a Dylan Field and you can pull that off at 19 or 20. And I think Dylan put in five years before launching Figma. So it even shows for the very, very best, they're gonna have to figure it out along the way.
Kyle (47:18.11)
Yeah, I think that's absolutely great advice. To learn a number of the different things as you get that experience, because obviously as a founder, you're going to have to know all of those different areas because you're gonna be responsible for a whole bunch of different things, managing people, managing a company, imagining all of those different parts. And so getting...
those reps in, like you said, and getting the experience or at least the exposure from people who have the experience and then being able to take all of that into your own company and being able to at least have an understanding of all of it and having done parts of it, whether that's managing and marketing or product and being able to take that experience into what you're doing has to be, has to give you so much more confidence. And then
You know some peace of mind obviously you know as you own it You know there's only going to be so much peace of mind that you can have but you're being able to take that experience into what you're doing Makes it that much more likely that you're gonna be able to have some success with it as well. So I think that's great advice
Ryan, this has been an amazing conversation. I appreciate all of your insight. I think we've covered so much ground and so many great topics. And like I said, we'll probably do a podcast episode on several of these areas. But I do have two kind of final questions that we'd like to ask everybody. And the first one is, have you read or watched or listened to anything that you found particularly interesting that you'd like to share? And these don't have to be product or business related, but they certainly can be.
Ryan (49:05.05)
One that, you know, I'll call it very specific parts. I think the all in podcast is interesting. Uh, and the, you know, ignoring all the politics, which I'll put aside and not something that particularly interested in is just the macro economic, um, the macro economic insight that they provide on the podcast is really interesting. I think if you're a founder out there or someone who needs to deeply understand the macro economic picture to perform your role.
I think there's a lot of really interesting insight, you know, Brad Gerstner, for example, from Altimeter Group. And then in terms of books...
There would, yeah, I don't think there's any particular books in mind, but I think that's probably something that I would consider for anyone in the macroeconomic insight that they're looking for.
Kyle (49:55.646)
Okay, that's great. Well, yeah, we'll put the link in the show notes to that. And are there any products that you have been using recently and you may be enjoying or not enjoying, you can call those out as well. It could be a digital product or a physical product.
Ryan (50:12.538)
I'll be a contrarian here and say Google Bard. I've been very impressed when I tried it four months ago, I asked, you know, I asked the question, I think about the next warriors game and it made a completely incorrect response. So, I mean, that was absolutely not true. I asked about events due in San Francisco and it gave me an event from two years ago. But I've been using it lately and I've seen some regressions in GPT. Uh, I've been using Bard lately and I've been actually far more impressed with.
Google Bars responses about real time questions, but also mathematical questions about historical knowledge. And I'm seeing a dichotomy between OpenAI and Google's approach to AI Emerge, where I'm seeing that OpenAI is launching a lot of really exciting features and products, but they don't seem like they're going to cross the chasm. And it doesn't seem like they're features that
we'll be able to have mainstream adoption. And a specific example is that for OpenAI, I find that I have to do very advanced prompt engineering to get the response that I want. Or with Google, I find out that much more basic prompts, it's able to come back with the response. I'm also seeing in the responses for OpenAI, they're using, I think like MATLAB formulas and how they will, you know.
display mathematical formulas and equations. And it's almost like I'm in a math class when I read the responses of how they're formed and everything. Where at Google, it just will give you the answer, 42. And the other thing is that OpenAI recently launched custom instructions that require the user to think about, okay, how do I tune the model for my own purpose? Where I found that with Google, it doesn't require that tuning. And so it's interesting in a product management perspective, and as someone...
You know, in the product space, seeing one company at Google with a very kind of mature, more nuanced view of building a product that can gain winestream adoption and where open AI launching on things difficult to use needs a lot of instruction, you know, needs a lot of hand holding. And so I'm curious to see that race play out.
Ryan (52:33.53)
But recently I've been a little more confident in Google. It's just seen their approach to product management and how they were able to bring more polished consumer-grade experiences to market.
Kyle (52:42.85)
Completely agree with that. And I found myself continually bouncing back over to Bard as I've used chat GPT obviously a lot and then have found more and more, it's probably similar to you, like a little bit disappointed and will bounce over to Bard periodically and more and more frequently to just get some of the responses and pull those into different things that I'm working on and like, okay, yep, this is what I needed and kind of the ease of use there
Ryan (52:52.302)
Mm-hmm.
Kyle (53:13.344)
do I just, do I go there first now? Because it's like, does that become my default? Like you're saying, like the ease of use is becoming much more apparent there as opposed to chat GPT. So like you said, it'll be interesting how that continues to play out over the next little while.
Awesome. Well, Ryan, again, this has been an amazing conversation. Where can people go to find out more about you, about SPRIG, about, you know, anything that you're working on?
Ryan (53:39.846)
So definitely check out SPRiG. So we're at sprig.com. And again, we offer in product surveys, session replay, design prototype testing, and AI to analyze all the data that you get with SPRiG. We just launched that conversational interface. You can ask questions about all the data that you get, which is a really powerful way to deeply understand your customer and find product market fit, increase product market fit, find feature market fit, and deeply understand that customer experience. And we have a really generous free plan.
that we just rolled out. And so I encourage everyone to try out Sprig, sprig.com slash sign up. And you can create your free account, you can install our SDK, you can ask your own in product survey as run your own session replay to understand your user experience. And the best place to find me is on Twitter or LinkedIn. So slash Ryan Glasgow, my full name on either LinkedIn or Twitter or X as I should say.
Kyle (54:40.967)
Okay. Yeah, but I probably continue to use Twitter for the foreseeable future, but we will put both of those links in the show notes as well, so you, actually all of those links in the show notes. So you can definitely check out Sprig and check out Connect with Ryan on Twitter or X and LinkedIn. So we'll have those links in the show notes. All right.
Ryan (54:45.953)
Ha ha.
Ryan (55:00.814)
Awesome. Thanks for having me on the episode today and really excited to meet some of the listeners. I'd love to hear from you. DMs are open. Also, if you try out Sprig, let me know your thoughts as well.
Kyle (55:14.458)
Awesome. Well, again, appreciate it, Ryan, and thank you everyone for listening.
Ryan (55:20.006)
Thanks, Kyle.