← Design Better
Design Better
Bonus Episode: Amy Lokey, Chief Experience Officer at ServiceNow, live in SF for UserTesting's THiS Connect Tour
00:31:40
A special live episode recorded at the UserTesting THiS Connect City Tour in San Francisco on May 1st
Loading summary
Transcript40 lines
- [00:00]
Eli Woolery
Hey folks. This interview was recorded live on May 1st for user testing's this Connect City Tour. Interested in coming to our next live show? We're joining an incredible lineup at Disconnect in New York City, including former Design Better guest Seth Godin, where we'll talk about customer experience, innovation and the real impact of AI. You could catch us at New York on May 29th by signing up at dbtr co ut NYC. That's dbtr co ut NYC. Now join us for a recording of our live interview with Amy Loke, who has led design and product teams at LinkedIn, Google and ServiceNow, where she's currently the Chief Experience Officer.
- [00:44]
Amy Loke
You have to understand the world that we live in and what human needs are and then you have to have the idea and the vision for how to meet those needs in a new and creative way leveraging technology. Whether an AI model can understand them or your team can understand them. And you have to be able to rationalize and articulate the idea and then know what good is like know if it's going to meet that need and be able to evaluate that and iterate on it.
- [01:08]
Eli Woolery
At ServiceNow, Amy's team is helping shape how AI transforms our work, creating smart systems that can predict what we need, adapt on the fly and make it easier to work with complex systems and connect with colleagues. We're excited to talk with her about how her team approaches designing for enterprise level AI applications, including specific applications for agents and how they can help you in your day to day work. Amy joins us today for a special live episode recorded on stage in San Francisco, California at the User Testing this Connect City tour. This is Design Better where we explore creativity at the intersection of design and technology. I'm Eli Woolery. You can learn more about the show and listen to our conversations with guests like David Sedaris, Eileen Fisher, John Cleese from Monty python, the band OK Google Pixar co founder Ed Catmull@designbetterpodcast.com Amy Loki welcome to Design Better.
- [01:59]
Amy Loke
Thank you so much Eli. It's great to be here. Great to be here with all of you. Thanks for your time and attention.
- [02:04]
Eli Woolery
Let's start talk a little bit about the latter part of your career. We mentioned that you led design teams at Google and LinkedIn, so maybe tell us a little of the story from moving from those companies into your current role at ServiceNow.
- [02:16]
Amy Loke
Yeah, absolutely. So I think one of the connective threads from LinkedIn to Google and then ServiceNow was just a growing passion around helping people, people accomplish what they want to do in their professional world and their professional lives. You know, LinkedIn before that came from more of a 100% consumer product world. Working at Yahoo and other companies. At LinkedIn, we were building a social network for professionals, for businesses, for people to build their brand, to excel in their careers, to get learning and develop their skills, potentially make business, to business connections, marketing purposes, all those things. And what really resonated with me and felt like it connected to my own values were that we were helping people reach financial stability, we were helping them provide for their families, we were helping them get their next best opportunity. And that felt really good. It felt like very purposeful work. So that then also led me to where I spent a couple years leading user experience for Google Workspace. It was at that time called G Suite. And there again it just felt great to work on a number of productivity tools. My kids were using them in school to do their classwork. I had used them for many years as a professional. And it also was really the intersection of personal and professional in that world too. I used my Google Calendar to this day to manage across my family's activities, right? And having that view of my personal schedule along with my work schedule was incredibly valuable. It started to move me more and more into enterprise design. G Suite had kind of a fledgling app development product at that time. And as I was spending more time talking to customers about what they were trying to accomplish, I started to learn more about the value of business, business workflow, connecting teams across an enterprise, helping digitize tedious processes that might still be paper based or spreadsheet based. And one thing led to another and I started talking to folks at ServiceNow. And I just thought ServiceNow was a really unique product opportunity. It's one platform that a customer can install and then you can build into and create a number of solutions across the business. Everything from employee experience, customer service solutions, technology, products, and then a low code app development platform. So whatever we don't think of as an out of the box product, our customers can build themselves. So it just for me seemed like a fascinating product opportunity with an incredible diversity of products. You know, interest for me personally from an intellectual standpoint, but also just still felt really squarely rooted in helping people be productive, have good experiences at work, have great customer service experiences, and businesses really evolve and transform how they were operating in great ways based on the tech technology. So I just felt like that was the direction I wanted to head in from a career perspective. And it felt like really fulfilling work.
- [05:01]
Eli Woolery
So you lead a pretty large team Right now, Right. How many folks?
- [05:04]
Amy Loke
We are nearly a thousand people at this point. Pretty close. Global team, largely based both in the United States, but also globally. Across India, Europe, we have a team even in Egypt, you know, we've got teams all over and we're continuing to expand. I think I actually have my first team member in Costa Rica this year. I'm really excited about that. So we're continuing to grow and expand into a global market, look, looking for where great talent is and where we can also expand our product regionally as well, too.
- [05:31]
Eli Woolery
So with a team that large, I imagine it can be tough to change course. And given just all the instability right now and the rapidity with which things are changing, how do you think about that? How do you think about steering that big ship?
- [05:43]
Amy Loke
That's very good point. So things seem to be moving faster than ever. We certainly aren't slowing down at ServiceNow. We're in a very competitive market to take AI products to market, and we need to do that and continue to maintain the trust and credibility we have with our customers to do that in a safe and secure and ethical way. So the complexity is growing and the pace is growing. I think that it starts with having a really tight connection and relationship with my leadership team. We meet on an ongoing basis. You know, the folks that I have working on some of our core AI experiences, we're meeting on hourly almost. It seems like we're in constant communication, but I think it all starts with the relationships and strength of my leadership team, that we can work well together, they can work well together without me there, and that there's just a constant cascade of information to the team to keep everyone appraised. We definitely take kind of a hub and spoke model with that, where we do have central teams that focus on what we call enablement. And for us, that's both team enablement. So getting the right resources and information patterns out to the team and disseminated to the team, we have a number of mechanisms for doing that. But we also have an ecosystem that we work within where we have a whole slew of partners that have UX teams that build and deploy ServiceNow. We have customers that have UX teams that build on ServiceNow. So our enablement is both internal and also external. So we're also, you know, making sure that whatever resources we're building for our own employees, we're thinking about how do we also deploy those out to our ecosystem so we can get those design teams and UX teams up to speed on the latest and the greatest let's.
- [07:18]
Eli Woolery
Talk a little bit about agents. Who do you think the next James Bond should be?
- [07:23]
Amy Loke
Well, it's funny you say that. I thought it should have been Idris Alba, but funnily enough, we actually have him now as our spokesperson for ServiceNow. He's booked.
- [07:32]
Eli Woolery
You can't.
- [07:32]
Amy Loke
He's booked. Yeah, we got him. We nabbed him. So, you know, unfortunately the 007 franchise is out of luck because we got him. But I think he would have been amazing.
- [07:40]
Eli Woolery
He would have been great.
- [07:40]
Amy Loke
Yeah.
- [07:41]
Eli Woolery
Or they could maybe bring Sean Connery back to life with AI.
- [07:43]
Amy Loke
Well, that would be interesting.
- [07:46]
Eli Woolery
In all seriousness. So Ray's talk earlier mentioned this sort of division between generative AI and agentic AI. And I think at least myself and I assume a lot of the folks in the room are a lot more familiar because we're using day to day generative AI, we get all the use cases. I'm at least personally much less familiar with use cases and using agentic AI, but I know it's a big part of the work that you do. So maybe you could just talk us through some specific work cases and how you're thinking about it.
- [08:12]
Amy Loke
Yeah, absolutely. Yeah. I've been kind of on the ground floor of all of our AI development since I joined the company. We had been investing in AI for a long time, even prior to kind of ChatGPT being launched and OpenAI first launching the large open source LLM model a couple years ago, three years ago now. So AI has been built into our products since the get go. Generative AI obviously, we realized, was really good at some key things, obviously, as you all know, you know, content based things. So summarizing content, generating content. Right. And so we looked for a number of use cases where those activities happened most often for us, I mentioned, we do employee experience. That means we help employees with various services or support they need. It could be anything from inquiring about their benefits to getting software to updating their computer, to understanding if they can take days off to going on leave, you name it. Anything across, like HR legal it, anything you need to get your job done is what we call our employee experience suite. Customer service as well too. A lot of those things you can kind of think of as a request fulfill model. And on the fulfillment side, there's frequently a lot of tedious tasks. Right. That lend themselves very well to this world of generative AI. So a lot of folks that work in those worlds, they get cases, you know, they have to get through a number of customer support cases or employee Requests, what have you. So, you know, generative AI was great for things like summarizing a case, helping someone get up to speed, generating emails or chat responses in a really appropriate way, even starting to diagnose and suggest resolutions to complex cases because of a precedent that existed or other information that existed in an ecosystem. So those are the things that we first delved into. We also delved into the development world. So ServiceNow is written on a kind of proprietary code language. There's tons of it available for us to write models on. So text to code kind of experiences, developer experiences, those were highly accurate and very quick to deploy. And so those were really like the home runs for us in the first year or so of generative product solutions. And again, there are activities where we saw people doing them, where there was large volumes of people doing them, highly repetitive tasks, things happening at a high frequency that were repeatable, where you could actually come up with a pretty clear value prop for the customer on the time savings and the productivity savings for their employees. And I know we've got a lot of user researchers here. This is based on user research. So we used a very foundational system, usability score type of measurement to look at how much time were people spending on these tasks and measuring that in a very quantitative way and then looking at the reduction of that time and the comparison and then you could extrapolate a value prop to your customer. Even we even developed pricing models based on that. So that was kind of the world where we started. As we move into agentic AI, really the way that that works is we develop skills. Skills are like an individual kind of atomic level generative AI thing like summarize a case, right? Agentic AI, they're built on those same skills. So we took all the same skills that we had made generative, which typically had a human kind of trigger them, right? So a human would look at a case and click a summarize button or draft an email or summarize a case or write a knowledge base article, right? So they're all kind of like human initiated generative skills. Well, in making those agentic, you're just basically automating that trigger. And you're saying in the event that this happens, have that AI agent run off and execute that skill. So that was kind of step one of agentic AI. And again, very kind of like individual skills doing individual tasks. Now we're in a world where we have an orchestrator. And that's really the really powerful part of this now is with the AI orchestrator, you can Kind of think of as like a team manager. Right. So the trigger happens, it kicks off the orchestrator, and the orchestrator is saying, what team do I need to solve this problem? So it can handle a much more complex, maybe lengthy process and pull together a team of AI agents that are all essentially unique generative AI skills to accomplish that task. Right. And then we do it in such a way that we look at it as a read write kind of analysis. The AI agents can go autonomously, do all of those read type of activities. So pulling together the research, doing the analysis, conducting a diagnostic, pulling that information all together in a succinct way for a human to evaluate, make a choice and then execute on that. And then when it comes to the right part of it, where you make a change, that's where that human's in the loop to execute on it. So that's kind of been our evolution. And trying to say it in a very short way, it was obviously a lot more to it. But where we move from kind of those fundamental generative capabilities into kind of singular skill based agentic capabilities to now orchestrated teams of AI agents. And then coming up now, there'll be agent to agent frameworks where you do that across systems. Right, so our AI agents can collaborate with Microsoft's AI agents and so on to really do complex activities across systems.
- [13:03]
Eli Woolery
Yeah, Talk a little bit more about that because we spoke before about that Copilot integration and that agent to agent work.
- [13:09]
Amy Loke
Yeah, yeah. So we're very close partners with Microsoft. And last year one of our bigger announcements, we actually have a big customer event next week, by the way, and I'll be going to that next week. And so last year this time we announced our first integration with copilot, which was really cool. So we had, you know, kind of like a bot to bot interaction where you could be using, say copilot in teams and say, you know, my laptop's not working very well, I think I might need a new one. And the copilot agent can call in our bot, basically, and we could provide all the service that you needed through ServiceNow. So it was kind of one of the first forays into the Microsoft copilot, so to speak. You know, at that point it was a virtual agent calling in ours. What's coming up next week, I can't disclose 100% yet, but you can imagine that same kind of framework will now again work with teams of agents on both sides. And we are in a good position to do that at ServiceNow because we already have a platform that integrates really well with all these other systems. So we already had the framework and the APIs, the access controls, the security, all that built in that we can leverage to open up those lines of communications, even at an agentic level.
- [14:17]
Eli Woolery
So designing AI enabled products for enterprise is a lot different than consumer. On the consumer side, there's a lot more liberty to ship something and it breaks like, okay, well, we'll roll that back. But if you have enterprise customers, that's not so easy. Right? How do you think about that?
- [14:30]
Amy Loke
Yeah, that's been, I think, probably one of the trickiest parts in all this. With enterprise, we've learned so much along the way. I mean, first you've really got to the technology in a very robust way. There's a degree of dynamic unpredictability. Obviously we're all very familiar with generative AI, can hallucinate it might come up with the wrong answer. That's why you need humans in the loop at enterprise scale. That can be pretty serious. Right? Which is why we've been very, very careful to always disclose when we're using generative AI. All of our initial four ways, of course, were kind of human driven, human triggered and so on. Now, as we get into AI agents, the good news is we've had the time to develop these skills. Right. Again, they're all based on these fundamental generative AI skills. But we've learned along the way how critical it is to test with realistic customer data. So we've made big investments in making sure that the data that we're using internally to test these models accurately represents our customers. We also then have an early adoption methodology where a number of our customers can kind of go into what we call our innovation lab. And they know that they're getting into an early access situation, but they are excited to be the first adopters and they want to give us feedback on the product and they're willing to test it out. And so, you know, I think I see our customers who are definitely, some of them are very, very risk tolerant and they're ready to jump in with both feet. They're also making sure that they're testing this really, really well. But fundamentally, we always make sure that we're being really transparent to the end user that they need to trust. Trust but verify. Right. Like it should be working at a pretty high level of performance and accuracy. We're testing that and hitting certain thresholds before we release it, but there's always a little room for error there.
- [16:09]
Eli Woolery
Let's talk about how you stay connected with customers. Tell us about your research practice, how you get feedback.
- [16:15]
Amy Loke
Yeah, absolutely. So I'm really proud of our research team. We've got, you know, again, a global team of researchers that we've grown over the years, led by a leader on my team on Anthronathon, who's amazing. And When I joined ServiceNow about five years ago, we were very, very focused on foundational research. And I heard some folks talking about that in our last session. And I do agree that when you're in the earlier stages of a product company, when you're trying to figure out how to grow, where to develop, where you want to place your bets in terms of your product strategy, foundational research plays a critical role. And so our research team was almost heavily oriented into almost like product market fit research in those years. And that was at a time in ServiceNow's history where we were scaling tremendously. So we were moving from being kind of an IT technology company to all these other areas within the enterprise, from employee to customer service and beyond. So we needed to figure out, like, where was our product the right fit? How might you need to modify it? There were a lot of questions, but a lot of what we were doing is influencing product management on where to take this product and where it could go. Then we had a lot of product out in market that we needed to improve. Right. Like, we put a lot of stuff out there. Some of it was sticking, some of it wasn't. And we really had to look at the fundamentals of usability, like, were people able to use these products? And so we've really invested and matured. Now, our fundamental usability testing. And like I mentioned, a lot of that's based on a system usability score. We created our own branded method that we called UX Quality. And it is based on time, on task, accuracy, number of clicks, qualitative measurements. Like, how do people feel about it? What did they think about the aesthetics? Do they feel like it was a good design? All of those things. And we've been rolling out those benchmarking studies now for probably about four years. And in some of our products, we've done them pretty regularly. We do two big releases a year. We call them family releases. We will do another benchmarking study. And it's just provided really clear, actionable feedback for our teams to act on. And so we had a product, for example, it's called Field Service Management. So it's part of our customer service product. It's, you know, technicians that go out in the field and have to fix things you can think of like the Comcast person that might come over and fix your broadband connection, right? So they're out there, they're mobile, they've got equipment on their truck. You need to do a lot to like help them find the right job to do and make sure you're assigning the right person to the right type of job and you're looking at their logistics. Anyways, our product in the early days wasn't so awesome, right? It was really in early stages, it wasn't garnering much business, it wasn't easy to use. We've done these studies now probably I think about six or seven times, and we've taken that from what was scoring kind of in the 40% to about 85% in terms of usability. And that's like a consumer grade product at this point. And we've seen the revenue from that product go at the same trajectory. We also helped garner investment in the team. So the UX team has grown over that time too. And we can show this really great correlation from the investment in research making those changes in product. The adoption and sales of that product and how well it's performing are all very, very closely connected, right? There's a causation there, so that's been really cool. And then the other piece that we do that I'm really proud of from a research impact standpoint is we have internal tooling. This is part of our product suite too that is kind of a developer operations or engineering management tool. It's a product that works for product managers as well as engineers. And we're building out for our design team and research team too. And so, so we log every single individual unique insight into this tool. Each insight is an individual record essentially in the tool. And we're able to also connect that to a design artifact that is our design record, which ends up being the revised design or the proposed design that we will build to address the research insight that then also gets attached to an EPIC and a story and a prd. All of this is in the same tool. And then we track it that it's shipped. So we have this really nice tracking mechanism now where we can track from insight to impact in terms of we discovered this thing, here's the design that addressed it, here's when it shipped, here's the EPIC and the story for the engineering artifacts that were built. We can see when it was shipped. And then we can also now measure the throughput of our insights to product execution. And we have an accountability model too. So we look at the Burn down rate of how much UX debt is sitting on the shelf. Right. So if we have teams where we've got a bunch of insights and they're not being acted on in kind of a race, regular amount, that's a red flag. And so those insights now, both the user experience quality and the insights to impact tracking that we do, we look at it in executive review on a quarterly basis. Overall, we call it our UX Health scorecard. And our executives have to speak to that in quarterly product reviews, which I think is pretty awesome. And usually they're good stories, but also there's an accountability model there. If there's work that we still need to do, that's great.
- [21:04]
Eli Woolery
In the last panel, Leanne was saying that if you're a researcher, it's not just your job to do the research, but you also have to be in sales and marketing, essentially. So do those tools kind of play into the sales and marketing story?
- [21:14]
Amy Loke
Oh, 100%. We've debated if it's the right time in place, but we do show team investment too. Right. So if there's a lack of investment in research in design, you know, we can show that as potentially contributing to the poor usability or adoption of a product. And then we can also show, like I was talking about field service management, team health, continual progress against user research findings and continual business results that match to that investment. So, you know, we can show the payoff that can come from investing in user experience.
- [21:45]
Eli Woolery
Let's shift over and talk a little bit about sort of the future of the designer's role, the researcher's role in this new era. And we're both associated with education. I teach and you serve on an advisory board. Right, for scad. And so I think we both got a little bit of a look into like, like how do we teach to this future of design? And at least with my students, I'm seeing a lot of the blurring of boundaries between what might originally be considered design task or a developer task, where the designer can now vibe code their way into a really effective prototype and vice versa. An engineer could use a lot of these tools to build out a first pass at a wireframe or even higher fidelity mockups. So we were talking about this at lunch and there's a feeling that, that we're not going to be calling ourselves designers or developers in the near future. We're going to be builders or creators. So how do you think about that? How do you think about advising your own team to upskill and kind of be on track for this New feature?
- [22:38]
Amy Loke
Yeah, absolutely. It's such a great question. I think we're all wondering about how this field might change. And yeah, I was with a number of my old colleagues from back in my Yahoo days the other day and we were at a talk, an event by the founding designer Perplexity and we were all talking, we kind of joked, we're like, are we going to see like the rise and fall of UX as an industry in our lifetimes? And I don't think, but it was kind of interesting. It will change a lot for sure. Like when I was working back at Yahoo, we were all using Illustrator and that was our best UI design tool because it was at least vector based. Anyways, we all liked Illustrator for various reasons, but now you've got Figma and so on. So I mean the tooling keeps changing and evolving to meet our needs, which is really exciting. I think that will continue to accelerate. And like you mentioned, I had the chance to go to SCAD a couple times and talk with their academics and their students about what do they think about AI. And I would say like a year ago, students and faculty were pretty nervous about it. You know the fact didn't know if they should allow their students to use it, but they kind of felt like they probably should because they were going to need to learn it at some point. And the students also felt ethically like, well, should I be using it? Is that cheating? And so we just asked them to like full disclosure, like show us what you're doing, how are you using it? And one of the examples that really stuck with me is there was a fashion design student and she had constructed this beautiful pink dress, physical actual prototype of a dress dress. And normally she would have wanted to explore a bunch of ideas and she would have wanted to try it long or short or puffy sleeves or no sleeves or all these different variants, right? But to do that physically in the real world would have been a tremendous amount of work and taken weeks and lots of materials and so on. So she had constructed this real dress, she took some photos of it and she brought it into Mid journey. And then she was able to do all these cool iterations on this dress, right? Really push her imagination, try all these different things without the limitation of like actually having to, to build it or construct that herself. And we thought that was kind of like one of the perfect examples of what AI can help us with as creatives, right? Is that really that expansive ideation and creativity of exploring those ideas. So to me, like I keep coming back to AI as a tool, it's just like back in the day when I got to use the magic wand selection tool and it kind of stuck to the edges of a picture and I was like, wow, that's really cool. Now it's like you just click one button and it does it for you. You don't need to go into lasso tool and like perfect it. AI is that same kind of tool, but it's kind of exponential in what it can help us to, where you don't really need to spend as much time learning expertise in these really complex tools like a Photoshop. But you still have to have the idea and you still have to have the understanding of humanity, of human need, of society, of technology, of cultural appropriateness. You have to understand the world that we live in and what human needs are. And then you have to have the idea and the vision for how to meet those needs in a new and creative way, leveraging technology. And I still think that our roles are very much the interpreters of technology like to help people understand how to leverage technology. And those interfaces may evolve, they may become more simple and conversational, but you have to have that idea and that vision. So I think we all just move into more of the role of a creative director and a visionary. But also I think fundamentally you have to understand how to articulate and direct those ideas. You still have to be able to communicate them in a way, whether an AI model can understand them or your team can understand them. You have to be able to rationalize and articulate the idea and then know what good is, like, know if it's going to meet that need and be able to evaluate that and iterate on it. So I still think those fundamental skills exist, but I just think it's going to be less about being an expert in a particular part of that craft. Again, whether it was I'm a, you know, wizard at Photoshop or Figma or I can code in any language, those things maybe are going to be less important than really having that idea and knowing how to articulate it and see it through to a high quality product that meets a human need.
- [26:27]
Eli Woolery
Amy, what are you watching or reading or listening to right now that's got you inspired? Doesn't have to be work related.
- [26:32]
Amy Loke
Oh, goodness. Well, I mean, on a work related front, I'm pretty religious about listening to Pivot twice a week. I love their podcast. I just find it's a great way to stay appraised of business, economy, technology, news. So I do listen to that quite a bit. It reading I have about 10 books on my bedside table that I am probably not making as much progress on as I would like them. But I mean everything from. Actually I grabbed Brian Solis's book. I've got three of his books on my bedside table, I'm going to admit. And I partially threw all of them. So I do. I kind of alternate between work and fictional books as well too. Gosh. What is it? I think it's like the Art Thief is something that I read. Fictional. That was really good. I thought if you like art history and European travel and stuff like that, that was really, really enjoyable. So I try to mix it up. I'm actually an Eng, so I do love a good fictional story. I'm also reading a random kind of more spiritual book around like past lives and stuff like that. I don't know if I believe all of it, but it's very interesting and thought provoking. So I don't know. I'm all over the place between business and personal interests.
- [27:32]
Eli Woolery
That's great. Awesome. Well, let's do one audience question if there's anybody has a question for Amy.
- [27:38]
Amy Loke
Hi, Will Jordan, grab design boss. Hi, nice to meet you. Nice to meet you. Nick here. Wit.
- [27:45]
Eli Woolery
Hi. Types or categories of insights or themes resonate the most with enterprise stakeholders for your experience?
- [27:57]
Amy Loke
Well, it depends on the stakeholder. So if I'm thinking about what resonates that maybe has the most impact with our product teams making product decisions, if that's kind of what you mean. We're looking at three altitudes of how to resonate with the customer. And I think this has been a really good learning for me in my time at ServiceNow. There's three audiences that we have to build product and they have to serve at these three different altitudes. So first you have like kind of the C suite. Right. My peers and our C level executives are frequently having customers with CIOs and CEOs of massive Fortune 500 companies about how do they solve their greater business needs? You know, we're talking to CVS around like how do you reduce turnover in all their retail stores? So you have to kind of look at it from a very high level. What does this business need to solve for at the most important strategic level? You know, I met with Stellantis is a big car, you know, manufacturer. They're thinking about car flow. Everything from supply chain and manufacturing to transit to getting cars to dealers to in the customer's hands. Right. So what I love about my job is I get to learn about all these different very diverse businesses and think about, like, if I was the CEO, what are the top problems I need to solve? We have to think about how does our product solve that. Then we have to think of the next altitude down, which is the person who decides to, to buy our product. We call them often like a service owner. So in the enterprise world, you're going to have someone that chooses to buy the product. They're like a decision maker that's going to evaluate this technology solution and decide it's the best thing for what the employees need. You have to solve for them, too. Usually for them, you're thinking about what's the ROI on this investment and how do we prove that out to them? How do we make sure that the product's easy to configure and deploy and get adopted and their customers are ultimately the end users who we also have to satisfy. So that's the third category that we have to think about. So a lot of our demos, our vision pieces, the presentations that I will give, have to be at those three different altitudes of we need to solve for the end user, which could be the employee, the customer service agent, the developer, the productivity worker, the HR expert who are using our software to do their core job. And so that's like, you know, kind of more of the consumer product mindset of just usability. Great product has to be valuable. They have to get what they need out of it it. But we also have to think about then how does that then turn to make that person who chose our software the hero. Right. Like, so you have to prove the ROI on those things. So they might be thinking about metrics like employee engagement, productivity, efficiency, customer satisfaction, stuff like that. And then ultimately that overarching solution has to drive a business result that a CIO makes them the hero for their board. Right. So I'd say that's, to me, the difference in enterprise design and research is we're thinking about those three different audiences which are trying to solve at very different levels. But ultimately our product solution has to do all three.
- [30:45]
Eli Woolery
Thank you for the question. Amy Lokey, thanks so much for being on Design Better.
- [30:49]
Amy Loke
Thanks so much for having me. It's great to be here with everyone. Thank you.
- [31:00]
Eli Woolery
This episode was produced by Eli Woolery and me, Aaron Walter, with engineering and production support from Brian Paik of Pacific Auto. If you found this episode useful, we hope that you'll leave us a review on Apple Podcasts, Spotify, or wherever you listen to finer shows, or simply drop a link to the show in your team's slack channel. DesignBetterPodcast.com It'll really help others discover the show. Until next time.
- [31:35]
Amy Loke
Sam.