Build What’s Next: Digital Product Perspectives

Breaking Silos: CX, Product, And The Metrics That Matter

• Method

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In this podcast episode, Method’s Jason Rome and guest Margaryta V. Rashev discuss the evolving landscape of customer experience (CX) and product development. Join us as we unpack how leading organizations are shattering traditional silos, leveraging data to truly understand customer needs, and driving business growth. Discover the shift from reactive questioning to proactive insights, the critical connection between CX metrics and business outcomes, and the exciting, yet often hyped, role of AI in the insights industry. We'll also explore the power of storytelling to bring user journeys to life and the essential foundations needed for organizations to swiftly respond to emerging customer demands. Tune in to learn how to foster true empathy within your teams and integrate discovery into delivery for impactful product strategies.

Jason Rome on LinkedIn: /jason-rom-275b2014

Margaryta V. Rashev on LinkedIn: /margaryta-v-rashev-35a517b/

Method Website: method.com

Medallia Website: medallia.com


SPEAKER_00:

You are listening to Method's Build What's Next: Digital Product Perspectives, presented by Global Logic. At Method, we aim to bridge the gap between technology and humanity for a more seamless digital future. Join us as we uncover insights, best practices, and cutting-edge technologies with top industry leaders that can help you and your organization craft better digital products and experiences.

SPEAKER_03:

Well, welcome back, everybody, to another episode of Build What's Next. Really excited about the conversation that we're going to have today with Margaret. Marga flew in from Chicago to talk to us. And we've been talking a lot about product lately and uh insights and measurement and AI. But one of the things that I'm most passionate about and I've had an opportunity to work with is customer experience. And especially today, we want to look at the intersection of customer experience, insights, UXR, and product and how that world is changing and evolving. And so really excited. Welcome to the show. Margo, would you give just a little bit of your background, I think, and especially being both an insights and a product person here a little bit?

SPEAKER_02:

Absolutely. Thank you so much for having me. I'm really excited to be here and to have this conversation. Super exciting topic as well. So yeah. So I'm currently based in Chicago, and I currently lead Medalia product pillar that's called listen, which is all the ways that we'll listen to our customer feedback, which includes all the direct, indirect, all the different channels, all the way the customers interact with brands. And then we analyze it and we act on it. But anyway, I lead the listen product pillar right now. And my background, I'm relatively new to product. I've been in product for the past two years. Before that, I was pretty much spending most of my career on the go-to-market site. So I've been in a lot of startup companies, and that's been my passion for my entire life. And now, of course, part of the big company, but very exciting part of the company where we can operate as a startup within a big company. Anyway, very exciting space.

SPEAKER_03:

Yeah. And you've shared, you know, some of the exciting innovation work. Um I think we're gonna draw on, you know, both aspects of your background today. And I guess maybe the first thing, you know, in terms of the intersection of customer experience teams and product teams, especially with the work that you guys do, right? And and I I don't think I work with any product team or design team that doesn't want more data on their customers and what they're doing. Like, how do you see those worlds coming together? And then I'd love for you to share um a little bit around how you're seeing insights evolve in general in the industry right now as well.

SPEAKER_02:

Well, there's a lot of really exciting things here to unpack in terms of how insights evolve in the industry in general. We are seeing a big shift right now happening with how brands are used to ask questions all the time. Ask, ask, ask. And now we're seeing a big shift from all the data that brands currently have about their customers, being able to put it all together and understand what customer needs and wants are before even asking any question. So this ability to put all of this together, understand before asking. And when you do need to ask, you ask in the right moment, with the right context, in the right channel to get the most valuable feedback. So we're seeing this shift right now happening, which is really exciting. And in terms of the product and CX overlap, we're also seeing that a lot of silos that everyone has been talking about breaking down is actually happening right now at a more rapid pace. So we're seeing more product realizing how much insights CX teams already have about the customers. Customers talking about different products that they use, how they use it, what do they like about them, what do they don't like about them? And that in combination with the metrics that we already track in product, which is usage, utilization, how we're able to connect it to the business impact, it's very exciting how these things start to come together. But another thing that I see a lot of overlap is actually foundationally when you think about these two functions within the organization, the customer insights and product. I had Will Goudara, who is the author of the Unreasonable Hospitality speak at our recent conference. And he talked about this idea that fats fade in cycles, but the human desire to be taken care of never goes away. So if you think foundational in terms of what CX at the core cares about and what product cares about at the core, is we want to make our customers happy. So when we connect those two, we find the common foundation. And now it's just a matter of figuring out how we can connect our metrics and how we operate together and how we complement each other to drive growth.

SPEAKER_03:

Yeah. I mean, there's to your point, there's a lot to unpack there. And I think it's so fascinating. If I think back, you know, earlier in my career, uh, you know, there were there were certain clients where we were doing both product and product development work for them, but then their CX team would hire us to do journey mapping and persona work and archetype work. Um and I remember the big aha moment for me was, you know, when when I was on the product side of the house, right, we had so much work to do that, you know, for for that client, such a big back, you know, who doesn't have an 18-month backlog, right? That, you know, it it was so hard for them to take in this new information all the time because they were already felt so overwhelmed. But then for the CX team, you know, we would find these really big aha moments about something or these opportunities to innovate. But then we'd take them to the product team and they said, you know, unless you've got a couple of developers hiding in that journey map, we don't really care about it. Um, because we're at capacity already. So I think it's been really hard for organizations to kind of synchronize the rhythm of business of the people who are listening to the customers and the people who are preparing those feedback loops as a way of maturing that. And especially now, I see a lot of companies trying to stretch a dollar a little bit further, trying to stretch their teams a little bit further. Um, and and whether it's the product team being asked to do more, the UXR team being asked to do more, or CX teams have to cover such a wide area, it's really hard to make sure that the right insights get to the right people to make those decisions. You know, you mentioned this um earlier at lunch of making sure um the right kind of insight gets to the right person. So I mean, how do you think about that of making sure, or maybe like advice to the product team, what their CX team probably knows that they would benefit from? Like, how do you think about making sure those insights get to the product team from a CX standpoint?

SPEAKER_02:

That's a great question. Yeah. So a couple of things here. I think when the idea that CX teams have such a rich understanding of the customer needs is there, right? And I think that we're seeing a natural progression in terms of how this kind of functions are starting to merge. But when you think about the product development lifecycle and how we build our roadmaps and how we think about prioritizing initiatives, that voice of the customer is so critical, right? Because on the product side, we are doing this work on our own. We're doing discovery, we're doing the research, we're doing the UXR. We're already doing all of this, but we're seeing it in this kind of a very limited space. But when you connect with CX teams, you realize they have this wide array of data on all of the customers and all of their key priorities. This is where I think that connecting the data will help the product teams not only um ideate on ideas, but also prioritize what's going to be really important. And in the end of the day, I think what is critical is for both functions to understand what is the business impact. CX, we're seeing a huge shift right now from moving away from score tracking to understanding what does it mean for the business? What does it mean for customer churn? What does it mean for the growth levers of the organizations? And then we're already doing this in product. So connecting those things together, I think is a really exciting shift that's happening.

SPEAKER_03:

Yeah. And and you you started to go there already. So I will follow. But talk about the the difference in what's in the the CX metric toolkit versus the product metric toolkit a little bit more. And we can get into some specific things. And I think this is such a rich space where there's so much misunderstood at times around like what these different metrics mean and how to use them and how to incorporate them. So but I think it's a place where both sides have a lot to learn from each other, potentially, as you just went into. And you know, building on one thing you said, I think that's one of the things that that we see in design projects a lot where, you know, you know, you you go do and user research, right? You're gonna talk to, you know, five, 10, 20, 30 people. Maybe maybe you run a specific survey. But I see so many teams when they do that, the results of that become their truth. And there is no kind of historical context where they're saying, okay, what is our existing set of beliefs that we're using this research to update those beliefs? And I think that's where the CX team has kind of that historical view. They have the view of the entire relationship. And um, one of my favorite quotes, I forget who I stole it from, is that you know the difference between CX and UX is your users are always customers, but your customers aren't always users because there's stuff going on for the customer with your brand outside of that user experience. And I think as product people, it's easy to forget where those journeys start when it doesn't involve our product sometimes. And CX can kind of connect those dots and tell the story. But let's dive into some specifics because I I think what you said is really interesting, of we're seeing this evolution of, you know, kind of sentiment tracking to more deep understanding. Can you talk a little bit more about that?

SPEAKER_02:

Yeah, absolutely. So when you look at the CX function historically, a lot of the metrics have been kind of centered on tracking NPS and LSAT. There were easy metrics to track. They made sense for many, many, many years. And they're still really good metrics, but they're not telling you the whole picture, right? You need to understand what is driving your NPS and LSAT. You need to understand from what are the key drivers, what is going to have the most business impact on more business metrics like retention, cost to serve, lifetime value of the customer, right? So connecting CX metrics to the business outcome is critical. And then for the product teams, this is where we're already doing this and learning from the CX, for example. We can say when we look at our roadmap or when we look at the backlog of the features that customers have requested through the PEQs that are coming into our product board. Right now, just looking at the the volume of the features or the specific topics that come in as the key features or the type of customer is giving you all also a part of the picture. But having an understanding of what are the key uh frustration items for the customers at a scale can give you much more context on being able to prioritize what's gonna truly drive impact in terms of feature prioritization and ideation stages. So I think this is where it starts coming together in a really powerful way.

SPEAKER_03:

Yeah. And it's interesting there. And you hit on an important point, which is these are valuable metrics, but none of them tell the whole story. And I think that's where a lot of teams struggle and get lost talking about books at lunch and talking about effortless experience, which is one of my favorite books in the space. And, you know, a lot of insights from that book and other things I see, right, is there's a very particular type of person that leaves a bad review. There's a very particular type of person that fills out an MPS survey, and there's many that don't. There's a very particular type of person that requests a product feature. Funny enough, for the first time, as a complete aside, I filled out a survey for a product I love this morning. It was the first time I've done it in a while. And and they asked me if I would be willing to do user research, and I said yes just because I want to kind of sometimes it gets boring being on one side of it. And I want to I want someone to interview me for once, you know. But uh uh so I I is I I I guess maybe that was a little interview prep for today of taking a I couldn't tell if it came from the CX or the product team who asked me for the survey. But um I think people get lost in that when we're talking to companies these days, intake prioritization and roadmapping is probably one of the most popular topics. All of those things inform the roadmap, but none of them can dictate the roadmap. And I think people want these listening posts they have set up to tell them what to do. But there's so much noise in this of you know, especially you know, NPS over the last couple of years, everyone does NPS now. And so customers are just oversaturated in seeing it and being overwhelmed by it a lot of times. And doing NPS for a B2B company versus a B2C company, very different context in managing that. So the the point about hey, making sure you understand what the data is actually saying, can you ask the question to get down to the root cause of analysis? And I think that's what's exciting right now is especially with AI coming along, you know, we can start to parse all of this unstructured data and kind of source data and understanding that. And so um, I did segue into we we can't have a podcast in 2025 without talking about AI and its impact. How are you how are you seeing AI potentially impact the insights industry? But then also how are you seeing it not impact the AI industry, the industry? You know, talk a little bit about uh that's a very interesting topic.

SPEAKER_02:

We have to talk about AI, of course. Right now, no conversation actually happens without this topic. Exactly. Yeah. So that's I think we live in a very, very exciting times. And that's one of the things that excites me about being in product right now and RD. There's so much innovation that's happening right now in this space in all the different areas and different verticals and industries and different types of applications for the AI. But I think when it comes to the insights and how AI can help, I think a lot of what we have seen over the past two, three years have been hyped up, right? And we're seeing that coming up right now in a lot of the um headlines with MIT research showing that 95% of the AI projects don't get past the pilot stage. Yep. Right. So that was really interesting data is coming up right now that is showing that a lot of it has been hyped up. So the people who are thinking that AI is gonna take everyone's jobs in like two years, it's probably not gonna happen. But we're seeing that very healthy correction right now in terms of understanding the most valuable use cases. And a lot of it right now, at least today, we don't know what's gonna happen 30 days from now or six months from now. The field is evolving so fast. But at least for now, we're seeing a lot of improvement on and optimization on the tasks that humans don't like doing, right? So I would say that this is the biggest application right now of AI in a lot of organizations. Like, how do we optimize some of those operational tasks that humans don't want to do? But again, throwing AI at a messy data set is not gonna solve your problem. So this is what the results of the MIT research are showing that just to have AI on top of a messy organizational structure or lack of processes or a messy data set is not gonna help you. It's gonna make things worse. So I think this is a really good reset moment for us right now. Understanding how fast the technology is evolving and what are all the different capabilities of what we can do. We need to loop back at the foundations and understand how we're currently operating, how we're talking to each other, what are the business problems we're trying to solve? We're having a lot of these conversations right now in the product. You don't need AI to solve every single solution that you want to build in product. Sometimes it's about automation. You don't need agents for everything. Sometimes it's just automation. So, what is the problem that you're trying to solve going back to the foundations and how do you want to solve it? And AI potentially may be an application. It can help you speed up research, it can get you more insights, deeper insights, especially on the large-scale conversational data. That's that that's what AI is really good at. But there's a lot of things that AI is not great at. So I think setting this foundation, very strong foundation in the beginning is critical right now as we prepare to advance to a new level.

SPEAKER_03:

Yeah, I mean, completely agree. And and, you know, obviously, you know, we do a lot of customer research for our clients. So, you know, we're playing with it with the ability to take interview transcripts and do that theming and everything. But I've had some interesting conversations with colleagues where I've seen sometimes AI overdoes it. It comes up with too many insights and it's too long and it almost you kind of like lose the context, you lose prioritization, right? And so, and you know, I I think there's been other studies that have come up showing that it negatively impacts critical reasoning for certain people if they end up over-relying on it. So I do think it's a delicate balancing act, especially in this case of where I do think there's still such an important role for a a strong craftsman, kind of going back to what you said about hospitality, that can really, really deeply empathize with customers and segments and understanding those differences, but thinking about like how that turns into a product and a product vision, because you can't solve everyone's problems in product. There's always going to be people who complain talking about NPS. I was doing a workshop with a client one time and and they uh were talking about their OKRs. And one of the OKRs was raise our NPS by 10 or 15%. I said, okay, what's your NPS? And they said something like 80. It was like extremely high. It was good. So that's what I said. It was it was like the highest I've ever heard. And I said, why? And they're like, because we want to improve customer experience. And I said, why? And they said, well, you just want to improve that metric. I said, Do you have retention problems? I said, no. I said, let's pick a different metric. Let's let's go after something else. Because your revenue not growing? It wasn't solving, it wasn't solving a business outcome for them. And so I think it's very easy for some of this data, some of these metrics to to become the hero. And and especially with AI, if people kind of lose track of where the data came from and the ability to kind of translate it and become too reliant on it. On the flip side, I do think you know, AI is not only going to be help us with that data, but it's it's creating new data for us. And data that didn't used to be data is now, you know, this podcast wouldn't have been data 10 years ago. But now it's technically data. We'll see how good and structured and maybe semi-structured data.

SPEAKER_01:

I mean, right now you can do a AI podcast, right? Like you don't even need to have a human that AI can do a podcast.

SPEAKER_03:

But you know, um, I think to your point, you know, one one of the things that I've always looked for when I've done product work in the past is even if I'm working on a digital experience, going to the call center and going to call center data and trying to figure out all right, what can I see around what issues people are calling about? And like and I think that's one of the saddest things for product and CX sometimes is like the call center data has been such a silo from product teams in the past. And so I I do think there's all these data sources in organization, whether it's business analytics, CX analytics, call center analytics, um, for locations that have stores, some kind of store feedback, employee feedback, that if product teams can incorporate those signals into their rhythm to your point around how they're thinking about their roadmap, they'll be able to be a lot more precise on just what they're trying to solve for. And and you used the word friction earlier, but I think so much of good customer experience is just removing the bad from it versus trying to delight. And yeah, delight has its place and its time and that type of thing. But anything else that that you're excited about when it comes to AI and insights that that you're thinking about?

SPEAKER_02:

I think this idea of being able to be proactive, to be able to see all the data across operations, contact center, marketing, product, legal, all the operational data, understanding that and being able to be proactive, not only measuring the experience, but orchestrating the experience. So the shift from the CX function to say we measure how we how we deliver experience, but also being able to deliver a great experience before actually measuring the experience. So I think that's that's becoming really powerful. But at the same time, you have to, you kind of have to look at it like when you look at the like innovation curve. You're gonna have brands that are made this huge shift and understand the value of building the right foundation to make to be able to connect all these data sets. And it's gonna be some of the top brands that are ready to do this, that are willing to take the lip, to take a leap. And maybe one or two percent of all the brands will be there. These brands that are innovators in this space and are not afraid to take the leap to make this huge structural change and how they operate and how they ingest insights, they're gonna be the ones who are gonna be the first one to prove the ROI because this is where the business is coming down. A lot of the times when a CX team or a product team is asking for an investment, show me the ROI. And this is where we are in this really exciting moment where some of the leading organizations are already doing this. We're starting to see some of this ROI coming in. And this is where I think we're gonna start over the next couple of years, seeing a little bit more adoption of the AI functionality at a wider scale.

SPEAKER_03:

But you mentioned ROI and business outcomes a couple of times. One of the things I used to say about one of the difficulties of being on a CX team was often that you own nothing and you inform everything, right? Where your real customer, a lot of times as a CX team, is other functions in the business because you hear all these things from customers, but then you have to convince someone else to do anything about it. You don't get to, I mean, some CX teams do, but you don't get to write the email. You don't get to pick up the phone, you don't get to prioritize the backlog. You know, you're you're kind of this master of empathy, but then also you have to kind of work through others just to be that advocate for customer vision. I guess do you do you see CX teams carving out a larger role if they can kind of start bringing more of this ROI in? Or are you starting to see that shift take place at all already? Or how do you see the role of CX evolving?

SPEAKER_02:

I think it's a natural evolution, right? Because it's not enough to say our NPS score went up, right? Like in your example with a customer that you work with. You want to be able to say this had an impact on our retention. This had an impact on our long-term value. And when you're able to prove that, and when you're able to connect with other functions in the organizations that are already doing this, I think for CX, your biggest partner should be finance, right? You should be working with them 24-7 side by side, understanding the PL, understanding growth levers, understanding all the metrics that are important to the business and being able to run correlation models or being able to tie the key metrics in CX to the business outcomes is critical. And we're seeing that happening more and more. And I think that's really exciting.

SPEAKER_03:

Well, you heard it here first, people. Put your CX department next to your finance department at the company and magic will happen. No, I I do think it's so important of having that kind of econometric model, especially, you know, maybe we'll pick on CSAT for a moment because we've kind of given NPS its run on the show. You know, there's so many layers to these metrics, right? And the ability to, you know, segment that data and and look at performance within segments or performance within products or performance within any issues. And because the one thing I always tell people about CSAT or NPS is, you know, if you're at negative 20, those next 20 points are pretty easy, right? Because you're just trying to avoid detractors. If you're at 40, those next 20 points are going to be like hard. And so, you know, these metrics also have their nonlinear relationships to the amount you need to invest to improve them. And so that that relationship that you talk about is really important because the the bar changes. Like once you fix some of your NPS, the model probably is is no longer valid in some cases. You know, some parts of it are going to be, but now you're probably solving a different problem. And if you can't constantly figure out what that problem is and make that business case, it becomes really hard to kind of get those initiatives funded and pushed through. I think what CX can do that others can't is they can cross boundaries in the organization really easily. You don't see a ton of product teams and call center operations teams partnering really closely, especially at larger companies because they're so far away from each other on the org chart. But CX, who can own that end-to-end experience, can kind of say, like, hey, you know, product, listen, we're getting a lot of calls about this. And it's probably downstream air from, you know, this page or this content or hey, marketing team, the val prop here isn't clear. And so you're overselling and you're missing this. And so it creates really unique opportunities for that. Collecting the data, listening to the data, analyzing the data is one thing. Um, I think an an underrated part of this that's really important is storytelling as well. And what do you see product teams potentially being able to learn from CX teams about bringing insights to life and using them to kind of convince people outside of the ROI model, like, hey, we need to do something about this?

SPEAKER_02:

I think product teams are already doing it to a degree right now. When you talk about the UXR research, a lot of it right now with the new technology is being captured by the video technology that you can put in a show reels, right? That you can tell that story. I think product teams are starting to realize the importance of telling the stories. A lot of times human beings are making emotional decisions, even though we think we want to make a logical decision. So I think that storytelling aspect is really important and doing it to a degree. And technology is allowing us to do that even more. But I think being able to work very closely together with a CX team on combining that story would make it even more impactful. And combining the business impact from what a product has done to the business impact on the customer experience, because depending on the type of the organization or the vertical that you're in, some organizations' product is an experience, right? Some organizations are more service heavy or some of them is a mix. But if you're a product-led organization, then that is your experience. What you're building in the product is a huge part of your customer experience, right? So I I see those functions working much more closer together right now than before.

SPEAKER_03:

It's interesting because I I do see that as a step that gets skipped sometimes is the storytelling nature of it. Because, you know, you you do a lot of research, right? And it comes back and it says six out of ten users like to this feature idea. And there's only so much you can emotionally, even rationally or emotionally, like, is six good? You know, is sixty percent good? Like what does that really mean? But being able to kind of paint that in light of a customer's journey and like their why they came to the product and the problem it's trying to solve and like highlight one of those and bring to life. That's one of the things that I'm hoping, you know, AI with the ability to kind of pull sound bites and pull video and help teams kind of put that together can help with that storytelling. Cause I feel like that's been lost sometimes. And you know, you go into these big planning events, right, where it's all about prioritization and breaking down our a roadmap. And it's easy to feel like sometimes the user's been left out of that room and the customer's been left out of that room. Or if they're in the room, it's it's very transactional. And so people talk a lot about like customer centricity and falling in love with the customer. But I think sometimes with all this data.

SPEAKER_02:

Forget about the customers.

SPEAKER_03:

Yeah, it's easy for them to become data points instead of people like really staying close to them, and especially for you know, telling the story to the engineers, you know, telling the story to other people of you know, one of um a gentleman I've had on the podcast before talks about he sends his engineers into the store just to see people and like watch them interact with the technology. And I think that's so key is you know, how can you bring these folks to life? And I think AI creates that opportunity. One of one of my consulting tricks over the years has been, you know, if I had to deliver a user insight that I knew my stakeholders were not gonna like, I always delivered it as a video recording of one of their customers answering a question. Because then it was you're not gonna be you're not gonna be arguing with the consultant about if they're right. Like here's here's a customer. Like, let's argue with the customer instead and like putting them front and center. And so I do worry with all this focus on collecting all the data to make the perfect decision. Like we, you know, I think that craftability of like true empathy is is still so important. Um I think that's one thing that more product folks can really curate um and and be able to bring into their practice.

SPEAKER_02:

It is at the core of what product, how a successful product is built. You need to bring your user story to life. That's what we do. We build products to solve for user problems, right? So I think it's it's a part of our function that we just need to remember to come back to all the time, more and more. Some of the most powerful strategies that I have built started with a user in mind, started with a quote, with a story. When I talked to the head of the insights department at the large grocery store, and they told me that this is my biggest problem. That was the beginning of my strategy. I think it's so powerful. Engineers love, love absolutely not be in front of customer when something breaks and there is a buck, but to hear what customers' pain points are because they get so excited in terms of how they can solve for this problem and how they can fix it and what they can build. So I think it's critical.

SPEAKER_03:

I think, you know, that that's one of the themes that we talk a lot about on the podcast is, you know, this system of discovery and insights and how do you integrate that a little bit more into your delivery system. You know, as an organization grows, that discovery system and the delivery system, I think there's more and more layers between where, you know, a CX person has told a UXR person something, who's told a product person something, who's made a decision, who's handed it to a PO, who's then turned into a requirement, who then hands it to an engineer. And you're almost like six or seven layers removed from like, you know, what's the problem we're solving and being able to bring that back to life. Um I guess if if you look into the future, like what what are some things, you know, over the next couple of years you hope to see in how organizations are evolving, how they interact with their users and how they bring these insights to life and how how teams kind of bring this into their rhythm.

SPEAKER_02:

I really hope to see that the shift that's we're going through right now from just asking, asking, asking and understanding really evolves and really becomes table stakes for every organization in terms of how they interact with their customers and consumers. I think the period where we are right now in building the right foundation is very important, right? We need to make sure that before we throw AI the problem. We're ready operationally to be able to execute on it and act on it and really drive business impact. And I think for us in the RD team, it's probably one of the most exciting times because there's so much unknown right now. Nobody knows what's gonna happen. We can all speculate about different ways that AI is gonna have an impact on our life, our careers and everything else that goes from that. But we can all have at the same time the impact on that development, right? Especially in RD teams, we get to identify the business problem. We get to identify what's important to solve for, and we get to build it. So I think it's a really exciting time for us. And I think the more stakeholders that we connect with, the more we work together as one team versus trying to pull into the different directions, the more successful we're gonna be and the more business impact we're gonna deliver.

SPEAKER_03:

I think you wrapped us better than than I could have, but I'm I'm gonna give it a try to kind of wrap on top of yours. I I think two really powerful themes and maybe just questions that we can leave people with today, which is, you know, for product teams and design teams, thinking about are are there questions that you're going out to ask your users or your customers that someone in the organization might already have data that could help inform your answer and would change the question you ask. I think that's really powerful. Of I've always loved the concept of natural experiments where organizations that have a lot of locations or they have a franchise model or they have, you know, silos and they have this kind of unintentional heterogeneity of people not running different experiments, but just running the business differently. And that's creating data that could tell us about like, hey, let's go look at all these different things we're doing and see is it generating any data that tells us something unique about our business. I think that's like one really valuable point is what are questions you're asking today that you could rely on behaviors tomorrow? Um, and sense that. And then I think the second thing um when you talk about the the kind of the foundations and the operations for a company is if you heard something fascinating from some of your customers or a segment of customers, or there was a new need emerging from your customers tomorrow, could your organization respond to it? Like, do you have the ability to take and recognize a need as an organization, decide we should stop some of the other stuff we're doing? We should prioritize this and we should invest in this because it's important and we're hearing this and act on it. And you know, would that take you a budgetary event where you have to say, like, well, let's put it on the docket for next year? We're gonna have to make a capital request. Would that take you going through multiple rounds of planning where, hey, we have to go through and you know, build the business case and do discovery and then kind of get it approval by these committees? You know, is that something that your teams could hear and pivot kind of in the moment of something they're designing? Could they reprioritize? I think it's a powerful question for us to ask ourselves. A lot of companies right now focus on their cycle time. And a lot of them focus on cycle time from kind of idea intake to execution and release. But a lot of them aren't asking like the true cycle time is the recognition of a need in the market. And so you're gonna be getting more data. You're gonna have to be upskilling and training your teams on how to use that data. But you know, that that true version of agility is that recognition of a need and the ability to go respond to it. And so, do you have that in place? Because I think to your point, if you don't have that in place, we could share all the AI insights ever in the world, but they're just gonna sit there as insights instead of turning into actions. So, any other parting thoughts for us? I think this was great and love the conversation today.

SPEAKER_02:

I love it.

SPEAKER_03:

Awesome. All right, well, thank you very much. And uh, we'll sign off as another version of Build What's Next.

SPEAKER_00:

Thank you for joining us on Build What's Next Digital Product Perspectives. If you would like to know more about how Method can partner with you and your organization, you can find more information at method.com. Also, don't forget to follow us on social and be sure to check out our monthly tech talks. You can find those on our website, and finally, make sure to subscribe to the podcast so you don't miss out on any future episodes. We'll see you next time.