GTM: How Intercom Built the Highest-Performing AI Agent on the Market Using Outcome-Based Pricing with Archana Agrawal, President at Intercom

Archana Agrawal (President of Intercom) joins GTMnow to share how Intercom (founded in 2011) successfully restructured its product, pricing, and go-to-market to become AI-native at a speed and scale most legacy SaaS companies haven’t achieved.

Their agent, Fin, now handles 80%+ of support volume, resolves 1M customer issues per week, and has grown from $1M to $100M+ ARR with a $0.99 outcome-based pricing model backed by up to a $1M performance guarantee if resolution targets aren’t met.

In this episode, we cover:- Why customer support is fundamentally a 24/7 business

- How Fin now handles 80%+ of customer queries through automation

- Why human empathy often breaks down in real-world support workflows

- How AI makes instant, individualized service possible for the first time

- Why Intercom put a million-dollar guarantee behind its resolution rate

- What it takes to confidently price software on outcomes

- Why the future of support is humans + AI

Guest links:

- Archana Agrawal - LinkedIn: https://www.linkedin.com/in/archana-agrawal/

- Intercom - LinkedIn: https://www.linkedin.com/company/intercom/

- Intercom’s Fin Agent: https://fin.ai/

Host links:

- Sophie Buonassisi - LinkedIn: https://www.linkedin.com/in/sophiebuonassisi/

- Sophie Buonassisi - X (Twitter): https://x.com/sophiebuona

- Newsletter: https://thegtmnewsletter.substack.com

Sponsors:

HockeyStack - the AI platform that unifies GTM data to help teams convert, expand, and scale. Learn more at https://www.hockeystack.com/

Granola - the AI notepad that turns meetings into action by capturing context, decisions, and next steps automatically. Head to https://www.granola.ai/?utm_medium=podcast&utm_source=gtmfund&utm_campaign=intercom-episode  and get three months free with the code GTMFUND.

Transcript available under the episode here: https://gtmnow.com/tag/podcast/

Subscribe to GTMnow for the latest episodes! https://gtmnow.com/

Highlights:

00:00 – Why Intercom went all-in on AI

03:23 – What Fin is and how it changes customer support

05:27 – How Fin scaled to a 6

The GTMnow Podcast
The GTMnow Podcast is a weekly podcast featuring interviews with the top 1% GTM executives, VCs, and founders. Conversations reveal the unshared details behind how they have grown companies, and the go-to-market strategies responsible for shaping that growth.

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Transcript

SPEAKER_01 0:00

Intercom's been around since 2011, is like a large-scale company, yet despite that scale, you were one of the first big companies to go all in on AI.

SPEAKER_03 0:08

Finn is our AI agent. Finn manages over 80% automation rate for all the customer queries that are coming to us.

SPEAKER_01 0:15

Artana Agrawal is president of Intercom, leading go-to-market strategy in the sales, marketing, success, and support teams.

SPEAKER_03 0:22

Customer service is actually a 24-7 business. Do you want instant answers, accurate answers? But what really happens in the field is you find customers are stuck in phone trees, or okay, we'll get back to you in 24 hours. Instant service is very hard. And being able to scale that level of individual service is now truly possible for the first time.

SPEAKER_01 0:45

You are covering, I believe it was a million inquiries over week, which equates to about 6,500 humans.

SPEAKER_03 0:53

Yes, I mean our customer service agents, the human agents are now AI operators. One of the most bold pricing decisions that I've seen is your 99 cent pricing. Customers didn't want to pay for activity. And so we get paid when our customers have that positive outcome. I believe you have an actual guarantee. If we don't meet the resolution rate, there's the million-dollar guarantee out there.

SPEAKER_01 1:16

And Artana, welcome to GTM Now. So glad to be here. Thank you for having me here. Yeah, you bet. Thank you for having me here in the Intercom office in San Francisco too. Appreciate it. And what a beautiful office. Well, thank you. Yes, it's a lovely location. Yeah, it's wonderful. And really excited to be here, but also to sit down and just pick your brain on everything AI and intercom's transformation. A lot of other topics too, but that's a real big notable one. So let's start there. Intercom's been around since 2011, consistently shows up in the Cloud 100, is like a large scale company, yet despite that scale, you were one of the first big companies to go all in on AI. What was that decision-making process like to really go AI forward?

SPEAKER_03 2:12

Yeah. Intercom was founded on this mission of making internet business personal. Like the founders really care about impeccable, almost perfect customer service, which is very hard. Like that is very, very hard to provide. And especially with the old technology, while Intercom had invested in an AI team and had a lot of AI going on prior to that as well. It was really once sort of ChatGPT came through and the new LLMs came through that they were able to really see the transformative power that AI agents would be able to have. And that was when Fin was born. To fortunately being able to see us, we've been able to see how it's been able to change so many customers' businesses and the evolution of the AI agent itself across all different channels and all different models has been uh incredible. So that's been the wave the company has read.

SPEAKER_01 3:12

Incredible. Yeah. I I mean it's certainly stood out as one of the companies that have done it in the most bold-forward way. And Finn, maybe you can just give a little bit of a description for Finn, anyone unfamiliar.

SPEAKER_03 3:24

Yeah. Uh Finn is our AI agent uh that manages uh all of the customer service inquiries that come. So previously, you know, you'd have humans manage through informational customer queries or take actions on behalf of the customers. But now with AI, you can actually have an AI agent do a lot of that. In fact, here at Intercom itself, Fin manages over 80% automation rate for all the customer queries that are coming to us, either providing customers the information they need or taking actions on behalf of what otherwise a human would have been able to do. And fin works on Intercom, of course, the Intercom help desk, but it also works on other help desks. And so you can have Fin working on your ZenDesk platform or Server Service Cloud. And so it's really has has had a big impact in how people actually engage with their customers. Um now customer service is actually a 24-7 business in any language you want, instant answers, accurate answers.

SPEAKER_01 4:33

Uh, and that's been the change that Finn has driven. I used to personally always think that the most human and helpful way was actually having a human interaction. And I have since changed my mind on that because it is truly incredible to have that level of support available 24-7. And I think I saw a tweet actually recently that you're covering, I believe it was a million inquiries every week, which equates to about 6,500 humans that Finn is replacing.

SPEAKER_03 5:00

And you know, I think that the thing is it's easy to uh sort of really feel the empathy a human can could can provide. But what really happens in the field is you find that customers are stuck in phone trees, or okay, we'll get back to you in 24 hours, 48 hours, instant service is very hard. And being able to scale that level of sort of individual service is now truly possible for the first time. So when FIN released actually all the way in 2023, it actually released with uh resolution rates in the mid-20s, which means that on average, you know, 20-some percent of your customer inquiries were getting resolved uh by the AI agent. But fast forward to today, the average resolution rate is over 67%. Why? So that is product improvement that uh a hundred percent of our 7,000 plus customers are getting advantages of this product improvement without any sort of static uh custom software that's stuck in their uh, you know, instance. They're all taking this leap forward with the product. I mean, these are so incredibly programmable, right? Like for your towards what your brand wants, your your voice, your policy, your tone, everything. And so you can actually truly represent your brand with your customers and provide the kind of experience you would want to tailor make for your customers, which of course you can imagine has has big implications for any business.

SPEAKER_01 6:38

Massive.

SPEAKER_03 6:38

Yeah, definitely.

SPEAKER_01 6:40

And that brings me to, I mean, one of the most bold pricing decisions that I've seen personally, and I think according to X and Twitter has also seen, but is your 99 cent pricing? And that was rolled out initially, I believe, in 2023 and now is quite kind of incorporated within Fin3 in 2025. But pricing is super important because I mean, this is GTM now, but it is one of the most pivotal parts of go to market. It used to be from the venture lens, what we'd see is you can afford to get your pricing wrong or tweak it. Now it's imperative that you're getting it right, if you will, off the gate, or you're you're embedding it into your go-to-market in the way that it is your moat. It is your strategic advantage. And you did just that. So love to hear more about your 99 cent pricing and outcome-based pricing.

SPEAKER_03 7:28

Yeah, if I can go back to maybe a a story in that case, because um that was actually what caught my eye about Intecom. Yeah. Is when they launched Fin and Outcomes-based pricing. Uh, it was incredibly intuitive. First of all, a product that's so simple to try, you could actually, you know, um start a trial yourself, check it out how it works, and then know that every time it answered a customer query, it was it was really truly an outcome. It was based on the value that the customer was was getting. And it's easy to think, you know, you launch a product, um, it's an AI forward product, it's really good, but really to then take it to market is a go-to-market model, a complete operating model shift. And when your prior has been selling seat-based software, right, to add to that truly outcomes-based software, that means you have to change everything ranging from like sales to support, success, professional services, metering, billing, pricing, right? All of that uh changes alongside with it. So yeah, Intercom was one of the first to actually launch um, both the AI agent, but to turn around deep research with customers, trying to understand what they wanted. And this won't be a surprise. Customers didn't want to pay for activity. Yeah, right? Like, oh, take a long time to answer a query. That's not what they're looking for, the number of messages or the number of tokens or just any activity.

SPEAKER_02 9:09

They want less messages.

SPEAKER_03 9:10

Exactly. They want they want the vendor to be equally incentivized on the outcomes that they care about. And so we get paid when our customers have that positive outcome and the customer support tickets are absolutely completely resolved. And so it's it's a an amazing way to actually converge both sort of sides of the incentives to make sure that we're delivering value to the customer at every point.

SPEAKER_01 9:36

Incredibly customer forward. And I think it goes without saying from an outcome-based pricing, but the customer actually selects when they're done with that inquiry, and that's what triggers the pricing. And I find that's just putting the customer truly at the heart. But what did that do for your go-to-market? Introducing the 99 cent pricing? Like what has that done now for ARR growth overall?

SPEAKER_03 9:57

Yeah. And so um, the entire operating model around this has to change, right? Because first of all, you know, your sales team is not trying to figure out, hey, how many seats do you want to sell? What kind of subscription length do you want? Instead, they're actually trying to figure out what how what kind of volume do you get? How much are you open to automating? What is your transition plan to automate it like? To actually figure out they're selling you outcomes. And then the success teams are actually helping realize those outcomes. In fact, I like to think about it like almost a little bit like the success team is helping with performance management of the AI agent more than, you know, previously you'd think about logins and activity and things like that. But now they're actually tuning and performance managing your AI agent for you. Um the the sort of billing and metering so that the customer has complete visibility around what they're using becomes very important. Um, but we go even further, frankly, because we know every customer has a different way in which they would actually want to adopt AI. Some folks know that they're going to try to transform their customer service organization. Others want to step into it. Right. Right. And so we actually have Bay as you go models as well. Try it, figure out how you'll evolve it with you, how you'll onboard the thing, figure out how much you want to use. And then when you're ready, we'll actually talk to you about a longer-term contract and help you get on board with it, right? And so we really have massive amounts of pricing flexibility all the way from self-serve to enterprise contracts. Pay as you go models, where you have 99 cents per resolution or longer-term contracts that you have with us. And so it was the entire tuning of that system across all the different functions of go-to-market to get us to that place.

SPEAKER_01 12:04

And I'm sure it did have a ton of fine-tuning under it across, like you mentioned, sales, CS, every team essentially changes how they operate. How did you operationalize that change as you moved forward with this outcome-based pricing model?

SPEAKER_03 12:17

Yeah. Um, there's there's so much that happens sort of both on the product and the go-to-market side to actually realize this in the field, right? Um, so I'll start with the idea that the Intecom product is, I like to think about it as you can try it any way you want, you can buy it, you can configure it, you can deploy it, you can manage it, you can do all of that all by yourself. And there's a huge product investment then that goes, you know, in the fact of being able to truly serve enterprise features and enterprise change management, but also having the consumer-grade experiences, if you will, to allow someone to go through that journey themselves. And so that that describes a little bit of our self-serviceability and the self-serve business, the PLG-oriented business that we have. And there too, you can imagine the metering and the billing and the transparency to help the customer actually get on board and start using FIN becomes very important. On the sales side, as customers get into larger footprints and want to sign up contracts, you can imagine we have a help desk that they may be purchasing, which is sort of seat-based. Right. And then they have the outcomes-based FIN AI agent that they're also purchasing. And so this was a new motion for the sales team. This was a new motion for our entire revenue operations and our financial planning. How do you actually forecast people's AI resolutions and outcomes? How do you incentivize your sales team to actually sell that new part of that business and work with our customers in a consultative way to make sure they are able to onboard into this new AI agent world? How do you then have success teams step in to fine-tune the performance and help customers realize the outcomes that they have on that front? And so each of these teams themselves took on new goals, new skills, new upskilling as well. It was a very, it's a very consultative model in that regard. But once the customer has been set up, right, even the product pulls its weight in terms of being very, very self-manageable so that the customers can tweak and configure. Our businesses are changing rapidly. I run our support team as well, and so I can tell you that just as the business evolves, the guidance I need to give our AI agent also evolves. And so, how do you get on this continuous improvement cycle? That's something success needs to be able to help you with. And through this entire process, if you want help or partnership, whether it's through our forward deploy engineers or whether it is through our professional services, how can we be there to help the customer get started off on the right way to be able to evolve from there?

SPEAKER_01 15:20

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SPEAKER_03 16:24

It would definitely depend on the sort of the business model and the kind of functions that the AI agent or your AI software is providing. At least in customer service, we believe that the future is humans plus AI for a very, very long time. When you think about even how Intercom customer support has evolved, you'll see that it's it is a it is one of our functions where we haven't actually seen headcount growth because the AI agent is taking up a lot of the volume and the demand increases that we've seen over the years. However, the skills within the team are transforming because the team members are no longer answering simple questions that they used to or taking actions on behalf of the customers. By the time something reaches your AI agent, it is an extremely high-order, very complex situation that you might have to be a customer might need to navigate that they're actually reaching out to a human for, right? So that's sort of like the the skills change. Our customer service agents, the human agents are now AI operators. They manage the AI on behalf of the company. And so the transformation has been both a human and AI-oriented transformation for us. That is a long-term sort of model that we will have. And so we expect even our customers will always have that human component that's guiding and helping, playing a slightly different role than they did previously, but is guiding and helping the customers in the same way. Now, by all means, one can also just purchase and use an AI agent, but it's got to have some other human help desk at the background that actually helps them when the AI agent has to hand over something to a human to help through the process. The thing about this transformation, you know, when usually when you used to think about customer experience, you thought about the UI of the product, the experience of the product. But now I think customer experience actually extends into the customer's org themselves because the humans are changing the roles that they used to do. And so the practice and the transformation that customers need to adopt, it's we we're actually developing a blueprint for that so that people know actually how to launch something, how to evaluate an AI agent, how to launch it, and how to scale it. All of that is honestly just the um I the good fortune of having 7,000 customers deploying it, that we're able to also take a lot of those best practices and feedback into the system, both from a product perspective, but also from a practice perspective.

SPEAKER_01 19:15

And it's interesting because you mentioned you're now at around 67, I believe, percent resolution rate. On average, yes. Many customers see much more than that, but yeah, across the across them all. And I believe you have a an actual guarantee on that too, which is very bold. Yes. How did you decide to put a guarantee on your resolution rate? You'll actually reimburse somebody if you don't hit it. Yeah. And then how do you model that into your financial side?

SPEAKER_03 19:43

Yeah. Um, it comes with the confidence from having an amazing product, I have to say. Um, you know, when you get into head-to-heads or competitive situations and you're seeing that the product is uh able to win out, it comes from the self-manageability of the product that it's much easier to configure and get going. It comes from the simple things that I mentioned about not having custom software in different parts of different customers' workspaces, but actually allowing all boats to lift with the product improvements that we drive to be able to say, drive in. We know, we know you'll love it if you don't. There's a money-back guarantee if we don't meet the if a large customer's high-volume customers, if we don't meet the resolution rate, there's the million-dollar guarantee out there. And it really comes from being able it from having that confidence in a product that has sort of every step of the way objectively shown to deliver uh the goods for the customers.

SPEAKER_01 20:41

Do you think we'll see more software companies putting guarantees on them and following suit?

SPEAKER_03 20:47

I certainly hope so. I think it uh it uh increases vendor confidence and trust. I would I I would imagine it uh it's definitely a big sign of partnership. I mean, the outcomes-based pricing definitely also tries to signal exactly that. It's it's a big change in the entire software landscape and how we run businesses. I I personally find myself very fortunate to be a leader at this time, you know, in my career where there's so much changing across all functions, across all um industries, right? And um that that signal of confidence um, you know, that that that customers look for, I think it's an important one. There are other signals people will look for. They'll look for um, you know, pace of innovation. I think that's an extremely important one today. Um a sense of partnership. I I the entire idea of consultative selling and consultative support is very, very important to us just for the same reason. We've we've been through that transformation ourselves, and so we know it's uh it's one that's very methodical and one that you need to plan for and impacts um your end user experience, really. Which is which is which will a company's really put that at the forefront and their uh priorities.

SPEAKER_01 22:06

What advice would you give to a company that wants to make this transition? Maybe they're at an earlier stage, but they want to be putting more of their product at the forefront in a way of the pricing. Any any advice there for someone maybe 10 steps behind?

SPEAKER_03 22:21

Yeah, uh it it would it would depend on the business model. So for as an example here, you know, when you have uh and there aren't very many AI agents uh on on sort of the application side that are self-serviceable at a team level, right? Like customer service, an entire team's got to use the same software and uh you've got to program it that way. And so, but when you're trying to do something like that, um then really focusing on both discoverability and activation, but then the product becomes important, giving customers the appropriate nudges, education, allowing them to be able to reach out and get um the support they need in order to activate and deploy, all of that becomes uh very important. Now the same thing you flip it. If you're doing mostly predominantly enterprise-oriented businesses, then a lot of what we said regarding the sales partnership and the support model as well as forward deploy engineers, professional services, partners, all of that comes into play to help a customer get set up correctly.

SPEAKER_01 23:28

Sounds like holistic enablement from every touch point.

SPEAKER_03 23:31

Yeah, and uh holistic enablement. It's uh it's also another remarkable um change that we've seen, right? Because uh there used to be an era, I guess, where you'd have a couple big launches in a year and you'd have your teams enabled for that. Um it's completely different right now. There's the product velocity like no other time that we've seen. Products are constantly evolving. So, how do you keep an entire sales force, an entire success team abreast of all of those not those bits of knowledge, but also at the forefront of being able to actually help the customer and in a very hands-on way get set up? And so it's also uh, I'd say continuous enablement that has been uh a big part of this journey.

SPEAKER_01 24:20

Yeah. It sounds like that's really what spins the go-to-market engine because as product velocity speeds up, yes, no longer is it the bottleneck. It used to be that product was the bottom and neck, and now your go-to-market is the bottleneck. How quickly can you adapt sales, customer success, everything around your product? Exactly. It sounds like enablements, what you really put in place from every angle.

SPEAKER_03 24:40

Exactly. And I and um when I think about this um really as the dual motion, which is um self-serve and enterprise being able to service customers of different sort of who have different speeds of adoption in of themselves, then I think about that enablement's got to come in all possible different channels for the customers, right? It's not always a one-on-one conversation with the customer that's going to help the customer get to success. It's all the digital education and the nudges and the blueprints, as I mentioned, that actually tell a customer how do they go ahead to do it. You can imagine all of that quickly evolving for new channels or for new types of customer service that are being provided. A quick pause.

SPEAKER_01 25:27

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SPEAKER_03 26:36

Um, I think that the the thing that was most challenging is that they all had to adapt at the same time, to be honest. That was that because there was you couldn't leave one portion behind and evolve the others, right? Like our org structures themselves changed in order to accommodate uh all of this. Like our support team structure changed, a number of different things. But I do believe that the a big benefit that we get is like instead of just launching a product, I think one of the biggest changes we made then in the operating model is sort of the revenue operations that took place alongside with sales incentive, sales enablement. That became like critical because I I completely agree with Chris on this. It's like you have to have the teams working with customers, usage and outcomes, not even just usage, but outcomes is what they are engineering this for right now. And so, how do you know that every sales rep, every customer success rep is actually laser focused on customer outcomes and the growth of those outcomes? You know, customers might start with one part of their business or one channel, email, phone, chat, like, and then they need to grow and evolve the channels that they're using. How how and different customers, different industries, e-commerce, different from B2B, different from financial services. How do you enable the teams to give them sort of the right formula and the support that they need in order to be able to increase their automation rate meaningfully through their journey? Um and how do you create, um, I mentioned a little bit about the billing and the metering, but let customers get the confidence in what they're buying and how much they're buying. Uh, make it easy for them to get into overages and then and then build in contracts when they need to. I mentioned our pay as you go model as well. So build in the flexibility for the customer, but still hold the outcomes as the most important thing for the company and for all my teams. And that was sort of the um I I think one of the critical things that we had to do in order to see the RAMP receipt. Been a busy two years for you. It certainly has. Yeah. Yeah. And an exciting one.

SPEAKER_01 28:58

Yeah, yeah. Definitely, definitely. And you've, I mean, made the transition. You've got the outcome-based pricing in in uh motion. You've got the seat-based model also. What does the future look like? Do you see the future as dual or do you anticipate everything shifting to usage or uh outcomes, for example?

SPEAKER_03 29:15

Uh we do see this future as dual at at this point in time. We still we we see the role humans play in the process changing and therefore their software evolving alongside with that. But but they are still very, very much part of the process. And the two things obviously uh go hand in hand, right? Depending on how much you automate and use your AI agent, your your human capacity needs change accordingly, depending on your business policies, so on and so forth. Um one of the things that we find um that's quite uh compelling is as people have gotten more sort of comfortable with the idea of this transformation, you see companies move from uh maybe starting off where AI was uh answering questions for the end user to where it's actually taking actions. Oh, you want a refund, you need a new card, you want to make an exchange, you want to change a subscription, you have a pricing question, whatever it is, it's actually taking taking a lot of actions on behalf of the customer service team. So the humans are still very much part of the equation, but their role keeps evolving along the time. And and we see that to be a constant at least for for a long time to come.

SPEAKER_01 30:38

It's interesting because earlier you touched on this too, of how your headcount has stayed the same for CS, but their roles have evolved. So it it almost rewrites the way you you learn and grow in a company too. Absolutely.

SPEAKER_03 30:51

Absolutely. I've uh I mean this has been maybe one of the uh, you know, when when um when sort of the advent of all software going to SaaS and cloud-based, I think was a big move in the customer success space about how do you actually make a customer successful and how do you think about it, right? I think this is yet another, another wave where we've had almost every team needing to change or upskill or be involved in a different job than they had been previously. Uh and we've seen customers go through different parts of this journey themselves, right? Like you've had some customers that just want to try and figure out and play a little bit with the AI agent and try to figure out how do they build their path, and you've seen large-scale transformations as well. And so being able to support all of that from a go-to-market perspective has definitely required um, I I'd say people taking on different roles. And um it's it's uh it's actually been a fun journey for the uh entire employee base, I'd say, because it's a learning journey, right? And that's always the best that there is.

SPEAKER_01 32:09

Yeah, exactly. And everyone's learning together too, which is a unique time for everybody.

SPEAKER_03 32:14

Yeah, learning, sharing knowledge, um, and and we learn even with the way all of our customers are rapidly adopting AI. That there's there's so many lessons in that for us too.

SPEAKER_01 32:26

Definitely. Well, we've talked about how you made the transition and how you launched FIN in 2023. Now, what has that done from a revenue perspective? I believe in your first year of FIN, you went from one to 12 million immediately, but you have you have continued to grow from there. So love to hear more about the numbers behind this.

SPEAKER_03 32:46

Yeah, and so uh fin has had an incredible amount of growth. We should we're we're on track in a few months to be able to uh cross 100 million in revenue on Fin itself and growing. The the growth rate is accelerating. It's been um uh and it's been across companies of all sizes and shapes, I'd say. We have with 7,000 customers, you can imagine that there's uh smaller footprint in the self-serve, but also extremely large customers that we have um using our product.

SPEAKER_01 33:19

Brilliant. Well, can we just see the continued growth? And prior to Intercom, you know, you spent over seven years at Atlasia, and you spent almost four years growing Airtable serving as CMO. What have been some of the greatest lessons throughout your career? The common threads that you've pulled through from those experiences here to today?

SPEAKER_03 33:38

Yeah. Uh so I've been very fortunate because both of those are incredible companies, first and foremost, and they are such amazing places to both learn and grow. So uh one common thread, if you'd ask me to, it would be the idea that you can actually build enterprise-grade software and uh provide that level of service to your customers while still deeply caring about consumer-grade experiences and building with a product-first mentality. So it goes without saying Atlassian's like the purest form of sort of that self-serve. The buyer journey totally maps your product usage. Um, you know, very simple, transparent pricing, no discounts, no negotiations, just you try and buy, and that's how the customer. And so there was an incredible focus on the buyer journey and that ease of use that was that was amazing. Airtable, on the other hand, went from massive PLG success to be able to harness that and take that to the enterprise. And so it was like building an enterprise motion over a PLG uh business. Same thing again, right? When you think about change management and governance and starting to invest in all of that while ensuring that what feeds that business and sort of the discoverability and action activation that become very important in the PLG journey still stay front and center as important uh to the company. And now I'd say that Intercom with Finn has let me take that to a completely different level because one of the things we mentioned is this interplay between product and go-to-market, like moving hand in hand in order to do that. The product taking the weight that it needs to in order to help grow in the customer's um sort of workspace, right? It's the self-manageability portion of it and the ability for customers to actually take control of their own destiny with the AI agent. And then the go-to-market motions that actually can support that with the kind of partnership that we provide. So I think um that that that's been definitely the common thread in all of them, which is you can aim for that enterprise footprint and you can help provide that level of service, but the ease of use and the activation energy that you put in a product that everybody can adopt. Atlassian used to say, you know, we're not for the uh Fortune 5,000, we're from the for the Fortune 500,000. And that always uh resonated. You know, the companies with that aspiration of we'll serve everybody and we'll we'll make this this next standard has been um has been truly amazing.

SPEAKER_01 36:36

That's incredible. Or there's some kind of pivotal stories along the way from Atlassian or Airtable that looking back now at your career were formative ones for you.

SPEAKER_03 36:47

Yeah, I I I I mean there there'll be so many, but I think the sort of focus um and non-negotiable focus like a company like Atlassian had on user journeys, don't do not put sort of humans where you can actually build something that the the entire customer base can actually take advantage of. And so making it as easy to use, looking at every touch point that we thought almost added friction for a customer and helping remove those touch points really in the go-to-market motion itself, how to think about um digital education, those those become became extremely important. Um, and in Airtable, how do you actually take the community and the virality that you get in a PLG motion and take that to the enterprise and help spread the product within the enterprise? And so how do you think about land and expand between different functions in the enterprise based on all of this rich learning around discoverability and virality that you've had from the customer base? It's been another sort of learning to take and think about once again education and usage and adoption once you get uh a customer to start using the product, which has been an uh an incredibly um useful way to think about uh expansion, honestly, because um, you know, you know, making it most easy for the customer and giving them all the tools that they need in order to be able to expand.

SPEAKER_01 38:29

Incredible. And you had to hire a lot of incredible people at both companies and now at Intercom too. And like we've talked about, the skill set of an employee matters so much because suddenly everybody's being asked to do things they've never done before in a new environment, learn new skills, take new roles. What are some of your kind of key, key focus points when you're making a hire and recommendations for anyone who is looking to hire people that can make that AI transformation journey? Yeah.

SPEAKER_03 38:58

Um, one of the things I mean, we all look for um, you know, folks that get that that understand the lay of the land can get the job done. But we've not I've not gone back ever and thought about, you know, I need people from a certain company or who've done something in a certain specific way because there are no playbooks today. You you want folks that can sort of discover it, builders by by heart. Um, and there are ups and downs on the journey. So I think the grit and the determination to to take it forward. And so you're looking for folks who can think first principles, think out of the box. Um, you know, they they aren't extremely reliant on an old playbook. Oh, this is how it used to work, because the rules of the game have changed. And so, you know, being able to think on their feet and be able to rediscover like the new rules would be uh an important component of that. So if I had to say it's that grit and resilience that that we look for, um, and um I've uh I've we we all sort of like at the leadership level, you end up um almost always like leading so many different functions that it's not I I I I actually don't find myself to be an absolute A plus expert in every single thing. But when you do hire the absolute A plus expert to be part of your team, then you know that together you can actually make a comprehensively amazing team. And that's always been the focus, which is hire people that are really, really strong at what they do, think through first principles. And when you bring that group together, you you get to see sort of the explosive results. Uh yeah, we get to see the bit.

SPEAKER_01 40:45

Yeah, definitely. The magic in a bottle happens. Yes. Are there any very specific questions or ways that you gauge the grit for people? Like I'll give you an example. Christina Arcuda, where she was the ninth employee at Stripe and she's now the CEO at Lanier. Like she looks for excellence in any domain. It could be in Lego construction, it could be in literally anything, but like that very specific excellence in something, because the premise and hypothesis is that it transfers where it's transferable. Yeah.

SPEAKER_03 41:15

Um, I I think quite uh similarly, I think I I but I look for excellence, um, but also look for a learner's mentality, right? Um a little bit of uh dissatisfaction maybe with status quo. Okay. And so that's what I'm kind of looking for in stories when when when people share those stories is um you know it's it's perfectly amazing to get get to c come across people that have just excelled. Um but in the in their journey when they can pick up the nuggets of the learnings, um, the mistakes, um, or how they made their own pivots, that becomes important uh in in that. And so looking for uh learners and people that that are always a little bit uh ready to agitate the status quo and and do better and do better. And that's what uh yeah, I love it for.

SPEAKER_01 42:11

I love it. So you're looking for an aptitude for learning. What about yourself from a learning side? How do you absorb information, especially right now in the age of AI, but how do you learn? Do you go to podcasts, books? Like what's your go-to?

SPEAKER_03 42:23

Um, podcasts, definitely, uh, because you get uh sort of uh practitioner learning and learning in real time, if you will. Um while I might share the story with you at the very same time. I know if we were to speak next year, there would be some evolutions, more learnings, more things to follow. And so you you get to see sort of that that in podcasts that help. There, of course, um, there are of course time-tested books that you can always go back to. And um, I I I probably have a couple of those on my shelf as well. I learn a lot from my team and I learn a lot from our customers. We have so many different sort of uh Slack channels and ways to gain insights from what's happening on the field with our customers in our conversations. Um and it's not just about learning about how they think about customer service or learning how they think about FIN or the adoption. It's how they're thinking about AI in their companies and how they're thinking about transformation. Um, and so it's uh I mean the day-to-day job, uh, as I said, maybe I I'll add that to the reason why I feel we're so fortunate at this time too to be in these positions, because it's just uh you get to learn alongside with everybody as they're making this transformation.

SPEAKER_01 43:43

Super cool. I feel like you're you're actually the perfect example of that because you saw the PLG velocity from Oblacian, and then you learned and transitioned to the PLG to enterprise, and now you're owning the transition to AI. So you've really lived through three different huge motion adjustments and led through these times. Yes, yes.

SPEAKER_03 44:03

It's been uh it's been and with incredible teams. That's been the amazing part of it, be doing that journey with incredible teams and incredible companies. And when you say that though, I I also do realize um this is my little go-to-market uh hack. Yeah. If you will, just follow an amazing product. Perfect. Follow an amazing product and and let it carry its weight. And then, you know, it's it's um my my job is impossible without that one ingredient ingredient. And with that one ingredient, it's just phenomenal.

SPEAKER_01 44:40

Yeah, it's true. I think you can hear that mirrored from a lot of people who who have you know been behind successful products and said it's a lot easier to sell, not to discount their success by any means, but it's just you get that you get that momentum with it. Yeah, which is great.

SPEAKER_03 44:55

Yeah, and and I mean the that's something that you also want your teams to recognize and and leverage really uh to the best that they can. So that that's an important component of it for sure.

SPEAKER_01 45:07

Yeah, great advice. And what about if we zoom out a little bit life more holistically? Do you have any favorite quotes or models that you would buy? Not quote. I'll I'll get back to the books question.

SPEAKER_03 45:18

Yeah, yeah, yeah.

SPEAKER_02 45:18

We can bounce around. Yeah, yeah.

SPEAKER_03 45:20

All right. Um so I mean two that are on my um bookshelf that I do go back to is the uh Hard Thing About Hard Things by Ben Horbitz. Yeah. And I find that to be um just such an honest look at leadership and at leading when there are no playbooks and making the hard decisions. And when you see it from that vantage point, there's so much admirable about uh about that and the lessons learned there. Um the other one is um John McMurna's qualified sales leader, which is an incredible way to to sort of learn about really selling value, deep qualification, deep inspection um, and uh selling uh for the customer with the customer around the value that that you're able to deliver. So I think there are a couple that I definitely recommend um leaders to go through. Excellent recommendations, definitely.

SPEAKER_01 46:17

Well, Archana, this has been fabulous. Really appreciate the time, the insight, incredible, incredible transformative journey, and a huge congratulations. Thank you so much. It's been such a pleasure to chat today. Yeah, absolutely.