Voc at Figma: How Figma leverages Al and VoC to foster product development

Summary

Michael Nguyen, an expert in building and leading Voice of Customer (VOC) programs at companies like Asana and Figma, and now pioneering the integration of AI into this process. Currently, he leads the Research Ops and Insights team at Figma, a collaborative design platform empowering teams to create together seamlessly. At Figma, Michael's focus is on scaling how customer feedback informs product development, making VOC an essential component of their process. In this Making Waves Podcast episode, Chun and Michael discuss:

• Experience in leading customer voices at Asana and Figma

• Advocates for customer-centric product development

• Need to understand organizational decision-making

• Identifying the role of VOC within the organization is crucial

• AI enhances data accessibility and aids decision-making

• Addressing biases in VOC data is essential

• Direct ROI varies based on company maturity

• VOC can de-risk revenue and inspire opportunities

• Democratizing data access and empowering individuals are crucial.

• Recommends "Unreasonable Hospitality" for insights into service and collaboration

• Envisions a future where everyone in the company contributes to product decisions

If you enjoy this podcast, don’t forget to subscribe on YouTube, of follow us on Monterey AI.

Speakers

Where to find Michael Nguyen:

• LinkedIn: https://www.linkedin.com/in/mrnguyen/

Where to find Chun Jiang:

• LinkedIn: https://www.linkedin.com/in/chunonline

• Website: https://www.monterey.ai

References

• Figma: https://www.figma.com

• Monterey AI: https://www.monterey.ai

Transcripts

Chun:

Hello everyone. Welcome to Making Waves show that brings the best and most interesting people and stories to you on building AI products and building products with ai. My name is Tr c e o and co-founder of Monterey ai. Today I'm super excited to introduce you to Michael Gwen, one of the groups in customer's voices who has been building and leading voice of customer, customer programs at companies like Asada and Figma, and now looking at bringing AI into the process.

Thank you, Michael, for being here.

Michael:

Super excited to be here.

Chun:

Awesome. Let's start with the pitch. Michael, can you gimme one sentence pitch of each who you are? What is Figma and what are, what is the voice of the customer program at Figma?

Michael:

Yeah. I'm Michael. I am a believer that customer-centric companies build the best products, the best businesses, and make the best cultures to work at.

And I am a lifetime student on studying how organizations can achieve and scale that. Belief. Currently I work at Figma. I lead our research ops and insights team. And for folks that don't know, Figma is a design platform for teams to build products together, from brainstorming, to design, to, to shipping.

We have products like Fig Jam and Figma, really make it fun and collaborative and super awesome. And VoC At Figma, we are trying to scale how customer feedback is integrated into how we build products. With our communities. And it's a, it's an integral part of how we build what we build. And, yeah, it's, it's, it's super fun.

Chun:

I love it. It's a, it's a seven year user of Figma. I'm super excited. I've been super excited to see how Figma has been evolving from, really it's a web browser design tool to now like everyday kind collaboration tool for the whole team. Awesome. Let's revisit the original story. I know like a few months ago when we first met, we're, you sent me this article about like VoC or voice of the customers in social listening for the customer packaging goods industry.

You mentioned that the digital industry or software industry have recently discovered best practices and principles that have been there. In other industry for decades. What inspires you, inspired you to become like the best or start in the voice of a customer's world? definitely not the best.

Michael:

I think, I think it was just like, it was just, I Googled it to be honest. It was like, you know, someone was like, Hey, can you build a VoC program? And I'm like, yeah, sure. What is that? And so did some research and it was like, oh, this thing has existed for a long time. And it goes back to the nineties with some of the, you know, modern management principles and theories that were developed.

And the, the strategy around it was very sound. And so I think for me, it became a blueprint for how to think about VoC in a modern digital era. And I think, companies are finally starting to understand that and leverage that, and just in time to kind of shift the thinking with the world of AI and like now I think it needs to be kind of rethought about again.

Chun:

Awesome, can you help us walk through the process a little bit? So saying like when you have a company saying like, Hey Michael, we want this voice of customers program. How do we start?

Michael:

Yeah, that's, that's a great question. You know, I meet with, I meet with V O C folks all the time that are kind of like starting this journey, and it's fascinating because there's a lot of similarities, there's a lot of like differences.

And I think what it comes down to is like, typically it's a, it's a reactive move. Hmm. It's like either our strategy isn't sound, or our culture isn't fully aligned, or we feel like we're not serving our customers in the best way. And so someone's like, oh, we need a VoC program to help kind of put guardrails on some of our product decisions or some of our prioritization.

And so, you know, they pick a, like a lonely CSM or like a support person. They're like, Hey, do you wanna like figure out our VoC thing? And of course people raise their hand like me and they like, yeah, let me, let me help kind of solve this problem. And so I think it starts there, but when you, when you kind of dig into it, it's really interesting.

Because it's, it's like the lifeblood of how decisions can be made within your organization. And so I would say it starts with like really understanding your organization, how decisions are made, and how customer feedback, customer insights can help either support, you know, the good decisions you're making or provide another perspective into some of those decisions.

Chun:

What's been the challenges?

Michael:

Oh, so many, you know, I think, I think VoC has kinda like a identity crisis because of this, because I think it's born for different reasons. And different pain points for organizations. So, you know, sometimes VoC is like helped, it's a tool to drive alignment between customer facing teams and product teams.

Sometimes it's used as like quality police to hold product teams or engineering teams like accountable. Sometimes it's just a list of like, Hey, what's the list of things support needs engineering to build?

Chun:

Right, right. You mentioned about guardrails. You mentioned about this kind of like, product place, which is pretty funny.

Also mention about, like this kind does it. It sounds to me like there need to be some common goals or common like metrics. I know, like, all organization talk about like OKR, or at least I using like a revenue, is like the common goal. Like do you think there's some common metrics there for VoC programs, to help with like build this kind of alignment or clock efforts?

Michael:

I don't think there's a metric, and if someone has one, I would love to hear from them. I've tried to solve this problem, but I think the challenge is with like, Hey, let's align around a single metric is. It's not inclusive enough to represent all the different perspectives of customers. Right. Like if you choose revenue, then it feels like you're waiting support and see us like customer success differently.

Right. Or if you say, oh, it's, it's nps, then you're like, well, then salespeople feel like their voice isn't as heard or valued. Right. Right. And I think that's one of the fundamental challenges with VoC is I think people can conflate what it's good for, or devalue what it's good for. Right.

So some, some organizations think like VoC should be driving strategy. It's, it is like the source of innovation. But the reality is like you're not gonna build everything your customers ask for. It's just one input into your innovation strategy or your product strategy, right? There's competitive intel, there's market intel, there's like your own intuition and innovation.

So I think that's like a big challenge that VoC practitioners have to face, which is like be able to articulate within your organization what is VoC good for and what is it not good for, and like how should it be leveraged?

Chun:

If you have to pick, one team or one vertical or one click POD to start with this VoC program, would that be kind of product team or entering team or like customer success team or

Michael:

I mean, you could start with one pod or one team.

I think maybe I would start with like whoever has the most data and influence currently in the organization. Interesting. Right, because that's just like where the traction already is. Yeah. Right. There's already like people there, there's already people championing it. There's like good data probably.

There's probably like a process and a spreadsheet somewhere of like, here's our, here's all of our feedback in one place. And that's a good starting point. But I think another common pitfall I see a lot of VoC folks do is they, they build what's good for them, right, which, which makes sense. Like if, if you're like a customer success team, you're like, okay, these are the top 10 things we're hearing.

I wanna build a bridge to product and I wanna communicate those. The challenge is sales is trying to do the same thing, right? Support's trying to do the same thing. Research is trying to do the same thing. Pmms are trying to do the same thing. And so now the product team has like six different people coming at them.

Like, here's the top 10. Right? Right. And actually, When you, when you combine forces and you build a coalition of people that care about customers and want to represent their feedback and their voices, you become much more powerful together, and that's one thing I learned was like, Hey, let's build a process where all of us can leverage it.

Right. It's just like, it's just like my household right now. I have Hulu, I have Paramount plus, I got YouTube Premium, I got YouTube tv. I'm like, There's too many different platforms, right? Like let's just get all of the same platforms so that insight producers can create their show, tap into their audiences, and not have to build infrastructure for every function or every team.

Chun:

I love it. You are the one managing all the subscription, right?

Michael:

Yeah. I need to cancel 'em all to be honest. This is inflation. You know, I can't afford all these subscriptions. I love it. I love it. Cool. I really like the point that you mentioned about like picking the team that has the most like data, but also like highest influence.

Chun:

They usually come like come hand in hand. Yeah, Since we are mentioning about data, it's a great transition to my next question, so let's talk about data and also talk about the future a little bit. 'cause I know you've been using like AI for a lot of, practices in your day-to-day life. Nowadays it's Alsot is my B FO.

Oh yeah. Nice. Nice. I love it. Did you name it? Name it yet?

Michael:

Yeah. I have my stream deck button right here. It says BFF.

Chun:

Oh my God. I love it, cool. Yeah. So like, nowadays, this is really hard to talk about a future without talking about like ai, so imagine we're kinda like aligning stars. What do you get when you cross like AI with voice of the customers in your world?

Michael:

I, I think it's a game changer, and I'll, I'm gonna be very honest with you. Like two years ago when people were approaching me, they're like, Hey, you lead v o C at Figma. Like, check out our tool. I'm like, I don't need that. I was like, I don't, I don't need that. I don't need I l p I don't need, I, I don't need anything more than like data science team to help push all of my feedback into.

Snowflake. So I can join it with other data. Right. It was like, at, at that time I was very getting by with is like querying customer feedback by keyword, and so Asana, we had this process, we called it voe and we actually had a, a dedicated person so that when a product manager or designer said, Hey, what do customers say about this?

They would like rally the troops and say, okay, support. What are you hearing about this? Sales, what are you hearing about this css? What are you hearing about this? And they would like go mine all their feedback and like, bring it to one place. And then they would have a meeting and just like share it.

Mm-hmm. Right. When he told me he wanted to do that, I was like, that's a horrible idea. It's a, it's super inefficient. No one's gonna wanna do that. People loved it. It was crazy. They were like, oh yeah, like Brian's v OE program's amazing. 'cause I get like all these really fast insights across different sources.

And so now with the advent of AI and all of these like new technologies, Those things are not just like possible. It's like there, it's easy, it's now the norm. It's what people expect. So when you go from like a product manager having to slack different channels and be like, Hey, what do what, what do customers say about this and support?

Hey salespeople, do you ever hear anything about this? Hey, research, do we have any knowledge on this? Right? That's how normally customer insights are spread within an organization. That's ridiculous. Like how do you make good decisions quickly if that's your source of customer feedback? Right?

Right. Now you're like, I can Google anything. I can chatGPT anything, but why can't I do that when it comes to like, what are customers saying about my feature? Right. Or the thing that I just launched. Yeah. I love it. So I think AI is a game changer because it makes so much data, more approachable, more accessible.

And now the question is like, how do you organize that data and how do you make it trustworthy? How do you make it safe? Yes. And how do you make it clear so that when people are making decisions, they can kinda show their math of like, here's the insights that are driving these decisions. Right.

Chun:

I love it.

One interesting one, design challenge I've been thinking about is, For the traditional, like BI tools or, tools like Amplitude having a common dashboard actually helps like the team to know, okay, this is the metrics we care about. This is the behavior data we're tracking. This event that we're tracking.

Whether this data goes down or up, it can like affect like our own mapping right away with like, for example, like, like our tool, like you said, you can ask like questions like, Hey, can you tell me what are customers saying about this feature? So all this experience. Are very like personalized, customized, because data is like more accessible.

But do you feel like with this, it's like even harder for everyone to drive a collective like effort and goal from your perspective, from like VoC perspective?

Michael:

That's a great question. I don't know if it's harder. I think it's just different. Yeah. Right. I think, I think a lot of quant data like dashboards, I think. I think there was illusion of alignment and illusion of shared understanding. Like obviously if you look at a revenue chart and it's like up to the right, you're like, yeah, right.

But you're like, what's driving that inflation? Why? Why did that go alive? And then you're like, oh, I don't know. You know, like that's where things get interesting. Hmm. I think what's interesting at Figma is like what I've learned is qual data here is valued just as much as quant. And I don't think I've worked anywhere where that was the case.

I think you can simply segment the audience into those two things. Yeah. Is your company actually customer centric or do they say they are, but they're not. And you'll have a very different conversation with people that are like, yep, my company's customer centric. These are the tactical problems and like blocking issues that I need to go solve, whether that's like engineering resources or, um, you know, shared taxonomy or, uh, a better cadence of when product and, and customer facing teams talk to one another, uh, a prioritization framework, like pretty like solvable prompts.

But when you talk to people are like, Oh yeah, you know, we're not that customer centric or our leadership team kind of just builds whatever the CEO asked for or, um, Our product team just kind of is like super reactive.

Right? Like ,at Figma ,we've built these like B o C charts and rankings and dashboards and they're like, I'm like, oh, is that interesting? And then the, like, the PMs or designers are like, Hmm. Kind of, but like, I wanna read all the feedback. Right?

Right. Or like, Dylan would be like, oh cool, you guys did some research. Can I watch the interviews? There's no replacing, like hearing the customer's voice. Mm-hmm. And so, I think when you abstract it into charts and graphs, I think it loses some of that. And I think what people real don't realize is like, yeah, the charts are a good attention grabber, but what people are looking for is the insights buried down below.

Chun:

I like it. We're talking about attention grab. I'm like asking a lot of painful questions to you and talk about, talk about attention grab I know like, All the user feedback we see from our customers, they al always like come from different sources there can be like social media, there can be like internal sources, of that in the, one thing I can agree on is like customer are being more and more vocal about what they want on social media, right now. But like, when you are trying to put all this data together, like what are some practice that you're. Doing there to prevent this kinda like bias, or beauty, something that for the people who are the most, like loudest in the room?

Michael:

Yeah, that's a great question. I think it's, it's actually not that profound. I think it's just like accepting that bias and just being transparent about it. Right? Like, so for, for us, our VoC program, like there's a meme that like our product teams are highly engaged on Twitter, right. And so what that means is like on on the surface, it's like, oh, we make a lot of decisions based on tweets.

That might seem like the reality, but it's not. It's like tweets are a good way to share how people are talking about Figma. Mm-hmm. But we're more rigorous in that. We also say, Hey, we're seeing a tweet about this. Do we see it in other places? Right. Like, do we see this also coming up in Zendesk? Do we also see this on Reddit?

Do we also see this on sales? And so there, there is this like understanding that feedback sources have different contexts and just knowing what those contexts and biases are is super important. Yeah. It's just like, it's just like misinformation now. It's like my wife would be like, oh, did you hear about this?

I'm like, that seems weird. Where was your source? You know

Chun:

always, always challenge the data and a conclusion.

Michael:

Yeah, and just like, you know, like you gotta be able to like kind of weight the, the sources a little differently because they come from different contexts.

Chun:

Yeah, yeah, yeah. One interesting story to share here is like, when I, started like hiring this month, I see so many like AI generated, like resume and I reach out message, from like different sources and you're like, oh my God, everyone here is so good. I know, right? They they do exactly what I want. Yeah. They write like a 500 words about my company. I'm like, oh my God, they are no more our company than I do, but like one interesting question I had last night was like, oh my, what if everyone started using like AI to write like, No, like write reviews.

I don't think it would be a problem for a software company, in a while, but when I think about like, okay, should we sell to like CPG or e-commerce, companies, that got me worried. I'm like, I don't even know how many of most message are generated. Or like even just bot message.

Michael:

Yeah, I know people worry about that, but then I'm like, have you read human written reading, chew.

Two, two. You know, so I, no, I jokes aside, there, there is a fear of like homogenous, like feedback, right? Yeah. Or just like, everyone's sounding the same because they're using the same, you know, chatbots or, or temperature settings. Or whatever it might be. But I, I think that's just like, uh, I think that's short term.

I'm optimistic. You know, I think from, from my experience, like how I've been using AI is, is just like, you don't just like, Trust it blindly. It's a, it's a collaborative partner. It's a, it's an assistant and for me it's helped me articulate my ideas more clearly. Mm-hmm. It's helped me articulate my voice tailored to a certain audience, or help me just think about different ways of trying to articulate what I'm trying to say.

Yeah. So I, I think there's a fear there and I think, you know, humans naturally are lazy, but I'm optimistic that AI actually helps people bring their ideas to life and like be able to talk about them more articulately than. You know, before they had it.

Chun:

I love it. I love it. One follow up questions on that.

I trust it's the last, like hardest one, for you mentioned about like a trust, so trusting like ai, but also like trusting what my customers telling me. Not nothing like they're lying, but in a lot of cases, like when I see, okay, there are 10 people mentioned about dark mode. Sometimes they don't really care about dark mail.

They just wanna have a better accessibility of the product. Like how do you kind of like structure your VoC data pipeline analysis or progress, to empower like other product owners or researchers to find out the root cost behind what users say?

Michael:

Yeah, I think that's what set separates like great product builders versus good product builders.

Mm-hmm. Right. I think some people might say like, tell me what to build or Tell me what to prioritize. Okay. If that's what customers want, okay, we will build dark mode. But I think the great product builders are like, yeah, we hear that a lot, but like, why? Like what's the underlying reason? Mm-hmm. You know, and like we have plenty of examples here like, Tokens, design tokens.

Everyone talked about design tokens forever. And they're like, people love tokens these days. Yeah. Build tokens. We need design tokens. We need design tokens. Yeah. And like, it wasn't that the product team here didn't know that. Mm-hmm. You know, they were like, we know that, but we don't think that's the best solution.

And of course, you know, they launched variables and everyone's like, holy cow. Like this is totally different. This solves our problem and more. And I think that's something that like really inspires me at Figma is like when I see our hackathons or our maker weeks and I'm like, you know, not only are they like grounded in some customer insight, but they take it further and they take it like in a way that solves a problem that like if you, if you told the customer that that was inspired by their feedback, they're like, what are you talking about?

I didn't ask for that, but this is amazing. Nice. You know, so I think. I think just like put a finer point on that, like V O C and all of this data is not to make decisions for you. It's in service of helping you build better customer intuition. It's in service of, of helping you build better products, sense faster or so that everyone across your entire company has great customer intuition or great product sense.

And I think that's something that I've been trying to tell folks is like, It's a, a misnomer, but to me, my, my bet now is really like v o c has infra innovation infrastructure, and I don't think people think about innovation as infrastructure. Mm-hmm. I think, I think tech has, like, we've talked about this.

Innovation is based on heroics. Yeah. Right. Who's the next Steve Jobs or who, who's the best designer? Who's the best thinker in this space? And I'm not trying to discount those folks, but my goal is like, how do we build infrastructure so that every company can innovate quickly in service of their customers?

Chun:

I love it. It's like being education system.

Michael:

Yeah. Like who doesn't want every product to be amazing? Yeah. Like, right. Like why do we have to have just like one really good product in every category? Why can't every product be really good?

Chun:

Why can't everyone build their own product?

Michael:

Well, I know why I can't.

Chun:

One day, one day AI will help with, with that.

I want you to dive a little bit deeper into the flip site or the challenges, voice of the customers, especially on proving the ROI.

Michael:

Yeah, I think, I mean, I think direct ROI is part of it, but I also think like, it depends on like where the company is in its maturity and like their position in the market that they play in, right? Like if you're a leader in your category and you are afraid of being disrupted or being out innovated. Then ideally your leadership team is thinking about how do we ensure that we're constantly monitoring what our customers are saying, ensuring that we're constantly like identifying and rapidly solving the needs that aren't being met yet and so that they never consider leaving to a competitor.

So I think, I think that's a much easier sell when you're like, Hey, this is, this is to help de risk your and protect the revenue you already have. And in addition to inspiring and sourcing new opportunities. But then you have companies out there that are like, we're just working on net new products and like net new markets.

So like customer feedback doesn't really, uh, give us as much value as a, you know, like research or market research, or just like building stuff that. We think is good. So I think that's, that's part of it. And then also being in this kind of like AI boom, no one really knows what people want and like, and like, everyone's just like figuring out as we go.

So I think like the old playbook of just like, Hey, talk to your customers and, you know, use that as inspiration, I think is tough.

Chun:

But I think there's this huge space of like personalization that we haven't dug into it. And the personalization would only be unlocked by having a really good VOC foundation.

Michael:

Yeah. Like VoC can, it's, it's funny. No one ever thinks about it, but like, if you had VOC connected to your CRM, imagine what you could do,.

I've been talking too much, but like, what, what excites you about this space? Like, you know, you, you told me early on like you've, this is a pain point you've experienced, but like what keeps you going, working so hard to build for folks like me.

Chun:

I think like the fundamental like value for me is like, I do believe everyone should have the same level of access of like using data. So like coming from self-driving like background, for me, Finding like autonomous like system that work for the car itself is like one thing. But on the other hand, like what is the best way for all the riders?

What's the best way for all the developers to understand what is this car thinking? What is this data doing in different, on the different platform that is the hardest like part about like my job is like how to build that trust. So cracking that code is. Giving me like more fun, so that's like what one thing.

And the second is just I love automating things, and then if I can put like my most, like, best like energy in thinking about, hey, how the future should be, how to like talk with like customer how talk with like humans to understand, to learn about their own stories. I don't wanna sit in front of the laptop like doing labeling or doing like structuring of the data, right?

I don't wanna like copy, paste a same sentence about like this insights and sent to a of different people in the company telling you that, hey, this is what customers are saying about that. So that is kind of like the second, drive for me. And the third one, like exactly what you said is like everyone should be empowered to make their own bet.

Own position, like product function is, should not only belong to the product managers. Like everyone is builder, like everyone right now they are part of the company. Like why are we only holding product decisions to only some, right? Some people in the company. So building this, kind of elevate this kind like whole data infra, make it like accessible, make it like delightful to use, that's also is like my thing. I love that. Yeah. Who would've thought, This would be as hard or harder than self-driving cars. It, yeah, I call it, I call it like autonomous, like a product, couple years ago when I was like literally drawing things in Figma, like everyone was asking me like, how are you, how are you so fast?

How can you design all like 10 different products in couple days? And like there's a logic behind it, and humans that needs, or humans fundamental like needs, they don't change that much. Humans, that user flow, they don't change much. So in the future, I do believe there's like more and more automation also gonna happen in like user research, user design and product development, software engineering, in general.

So, yeah, I'm, I'm a nerd. I wanna make that happen.

Michael:

Yeah. You are making happen. I think even just us talking about it and working together is just like signs of, of, you know, the progress we're making.

Chun:

Thank you. Thank you for hearing my struggles and complaints every day.

Michael:

No, it's your feedback.

Chun:

Awesome, awesome.

Cool, I wanna wrap this up with some recommendation from you, for audience here. What would be the one book and movie about the Voice of Customer you recommend or is some recent book you really like? I know what it is, but yeah

Michael:

I've been sharing this un unsolicited, but to me the most powerful book that I've read recently is Unreasonable Hospitality, and it just talks about, you know, the, the power of service and serving others and helping others. And it, it, it's perfect because I just binged the Bear season two and it, you know, there's a lot of parallels there and it just, I don't know, there's just like, There's something good about helping others and being a good collaborator and not worrying about getting credit for it.

And just like, you know, it makes you feel good at the end of the day, like you're providing infrastructure, you're providing insights for people to make better products that will help the lives of other their customers. That just makes you feel good. So Unreasonable Hospitality is, is my like go-to recommendation right now.

Chun:

I love that. I love that. Or maybe you just wanna be a chef.

Michael:

No, I can't cook. I can eat. I can't cook.

Chun:

Yeah, you can't direct, but you can maybe be front of house.

Michael:

I think I can do front of house.

Chun:

Awesome. Awesome. I love it. Thank you so much. This has been amazing and thank you so much for being here. Here, Michael.

Michael:

Yeah. Thank you so much for everything you're doing and help and supporting us and the community, so appreciate it.

Chun:

Awesome. Thank you.