Today’s episode is with Giancarlo 'GC' Lionetti, the former CMO of Confluent and VP of Self-Serve Growth at Dropbox. (GC also previously spent 6 years at Atlassian, as a sales engineer and product marketing manager for developer tools.)
He describes his career as more of a maze than a ladder, and this functional diversity combined with his deep experience at standout B2B companies gives him a unique perspective. In today’s conversation, we dig deep into why he advocates for a hybrid go-to-market strategy that brings together more traditional selling with modern product-led growth.
We start by mining lessons from GC’s time at Atlassian and Dropbox, including his takes on the differences between their business models and what it takes to make a multi-product go-to-market motion work.
Then we dive right into his advice for a hybrid approach, covering everything from his litmus tests for picking the right metrics, to the structure of his weekly meetings. GC explains how he sinks tons of time into understanding the customer journey, mapping out the delta between reality and the ideal vision.
He also shares plenty of pro-tips about pricing, packaging, and activation, as well as a broader diagnostic framework that he’s developed to evaluate a company’s go-to-market strategy. We wrap up by focusing on team building for a hybrid go-to-market strategy — from hiring profiles to team structure.
It’s a great listen for founders, product and go-to-market leaders, with tons of examples of specific impactful experiments he ran, metrics that did or didn’t work out, and common traps that he sees teams falling into.
You can email us questions directly at [email protected] or follow us on Twitter @firstround and @brettberson.
Giancarlo Lionetti
GC: Most of the time when people talk about these quote unquote different motions, they talk about them as an or you either have a product led motion or a human led motion, but the truth is you have a company go to market. And as part of that, you're actually really catering to your customers in the way your customers are trying and buying through different mechanisms, right?
Whether it's through the product or through humans, they're inextricably linked, they aren't different parts or pieces to the puzzle. They actually are connective tissue.
Brett Berson: Welcome to in depth, a new show that surfaces tactical advice, bounders and startup leaders need to grow their teams, their companies, and themselves. I'm Brett Berson, a partner at first round, and we're a venture capital firm that helps startups like notion, roadblocks, Uber, and square tackle company building.
Through over 400 interviews on the review, we've shared standout company, building advice, the kind that comes from those willing to skip the talking points and go deeper into not just what to do, but how to do it with our new podcast. In-depth you can listen into these deeper conversations every single week.
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for today's episode of in-depth. I am really excited to be joined by John Carlo lionetti most recently he was the COO of con. Previously, he was the VP of growth at Dropbox, where he led their self service and monetization efforts. And before that GC spent six years at LaSeon as a sales engineer and product marketing manager for developer tools.
What stands out to me is this isn't a career path you hear about very often in tech, as he puts it. It's more of amaze than a ladder. This functional diversity can bind with his deep experience at some of the most special B2B companies in the last 20 years gives him a really unique perspective. In today's episode, we dig into why he advocates for a hybrid go to market strategy that brings together more traditional selling with modern product led growth.
We start by getting into lessons from GCs time at Atlassian and Dropbox, including his takes on the differences between their business models and what it takes to make a multiproduct go to market motion. Then we dive right into his advice for executing on a hybrid approach, covering everything from his litmus test for picking the right metrics to the structure of his weekly meetings.
I thought it was particularly interesting to hear GC explain how he sinks tons of time into understanding the customer journey, mapping out the Delta between reality and the ideal vision. He shares examples of how too much experimentation at Dropbox impacted the customer journey and walks us through the process of running this mapping exercise with his team.
He also shares plenty of pro tips about pricing, packaging, and activation, as well as a broader diagnostic framework that he's developed to evaluate a company's go to market strategy. We wrap up by focusing on team building for a hybrid go-to-market from the hiring profiles. He looks for to getting the team structure right to designing the interview process.
In my view, GC share some really tactical advice here that any founder product or go to market leader will learn a lot from, there are tons of examples of specific, impactful experiments. You ran metrics that did or didn't work out and common traps that he sees teams falling into. I really hope you enjoy this episode.
And now my conversation with GC. Well, thank you so much for joining. We're excited to do this with UGC Ryan
GC: on. Thanks. It's awesome. Being.
Brett Berson: Uh, interesting place to start our conversation. And I'm super excited for this one might be to talk a little bit about some of the insights you've gleaned from the different roles that you've had.
And I think unlike a lot of exact sir leaders that often have a much more linear path to whatever function they're leading. You've been an account manager, sales engineer, you've touched product marketing, you've led growth, and you've held sort of the more classic title of COO at some of the most special B2B companies that the last 20 years I'm interested.
If there are any insights or lessons that you take for maybe each one of these chapters of your career, my guess is that as a VP of growth or CMO, you might have a different view of that role coming up in a much more classic go to market
GC: funds. So the way I describe my career to most folks is my career has been less of a ladder and more of a maze.
And I really think that's relevant in today's new go-to market world, because there are now so many different pieces that make up your go to market. And if you think about it, and you think about the trajectory of my career and the different roles I've held, this is especially early days. It didn't really matter to me what role I was linked.
As long as I was having an impact on the customer and revenue, those were the two most important things. And I could learn about different aspects of the go to market from that. That was good enough for me over time. You need to start bringing those pieces together, but if you actually look at those different roles across my time, all the way from Atlassian to more recently confluent, they actually do have a connective tissue.
It's really started off. Almost a very sales centric point of view, and then moved into a more marketing point of view and then moved more into combining both of those disciplines in more of a growth in CMO role. But there's connective tissue there between many of them. And I could jump into maybe each one of them, if that's relevant to some degree during my time at it last year in Dropbox and confluent to give you a little more insight.
Yeah. That
Brett Berson: would be great. And I'm curious how one informs the other in the sense of, do you think about marketing differently than other marketers because you started in more of a classic AAE capacity.
GC: Yeah, totally. I think you hit the nail on the head that one does inform the other and actually changes your point of view of another role that you may take in the future.
And so let me kind of break it down for you a little bit, like edit last year, my journey there was quite unique. I was their sub 40 million. Many of the folks listening to the podcast today may know them as the X billion dollar giant, that is considered a product led growth machine. And when I was there, we were really trying to figure out that model.
And I was a sales engineer, and then I went into product marketing, a little dirty secret is we actually tried sales with me there as well, but I held a really diverse set of roles. I call out three things from my Alaska new career that I think were relevant to future roles. First is I developed this incredible respect for what I call our customer funnel.
What that means is when you look at your funnel today, ultimately there's a lot of what we talk about, whether it's on a different podcast or blogs, et cetera, like the core metrics. I was obsessed with what I call micro conversions. And at year that was really extreme because they didn't have what we know as human letter sales as part of their funnel, the Inhumans in the process, but ultimately they weren't selling.
And for me, that was important and a big eyeopener for my career. Every step that a customer went through in that last year funnel was important to getting them to a monetization moment and to ultimately give that last year and money. And that was huge. And I became a student of that model in this and these micro conversions.
And I wanted to know everything that a customer did during that journey, but also the metrics and the impact that those things were having. So that was first takeaway. Second was I learned that humans were necessary in the selling process during my time at Alaska. And that's probably counter-intuitive to how people think of their business model, but humans were really the key to what I would say, optimizing the model that they had.
Almost everything we did from a human perspective was to learn. And we took those learnings and built it back into our machine. And that machine could include everything from our marketing to our growth, uh, stuff and all the way to products. And so when you really think about that, there's this incredible feedback loop that's informing our go to market and our business model that was very relevant there.
And then the last thing I'd say I learned is just a very data driven approach at LaSeon was. Incredible in creating these foundational KPIs and metrics that the whole organization understood even very early days. And I believe that still exists all the way till today. And we had a really good sense of what was driving the business from a KPI and metrics perspective.
So those are three key things that really informed, I would say the rest of my career. So if you think about my journey at Dropbox, ultimately I went to Dropbox as more or less like an IC and my aspirations. There were to figure out how to bring together what they call their bottoms up or self-serve business.
And. That's kind of like the buzzword of 20, 20 and 2021, but that was also something at last year and was pioneering very early days and many, many years ago with that though, when I was at Dropbox. If you think about that experience, it was quite unique because Dropbox had this incredible freemium business model, all the aspects of the customer funnel, metrics, data, all those things were as important at Dropbox as they were at at year.
But we were trying to bring it all together into what I call building a machine. And with that, that was part of my role at Dropbox and becoming the VP of growth there over time, I started off there as a party of one taking many of these things that I learned at at LaSeon and trying to translate them into the Dropbox world and building on this freemium motion.
And so things like building a more operationally. Efficient go to market model, especially from a bottoms up perspective. Second is building out a more human centric motion to inform your growth product and sales motions. Third is building a very, very data driven approach to how we ran our go to market and ultimately how we were able to inflect the business.
And that's some of what I learned during my Dropbox days is in which led me to my role as CMO of conference.
Brett Berson: I don't know if you have any reflections on this, but the one thing that I've been intrigued by is obviously Dropbox and Atlassian are in different markets, but they do have a similar type of go to market motion.
At the same time, Dropbox has kind of flat-lined around a $10 billion market cap company. And it lasts. CN is almost a hundred billion dollar market cap company. And I'm curious, do you have any reflections on the why or a thesis as to like, what are the underpinnings of that and is any of it tied to the way in which the product is brought to market?
GC: Fantastic question. I will give you the full GC opinion on that, which is if you think about it last, this model, and this was even early days, the model still exists at last year's model was primarily centered around a particular audience. That audience was developers. And when you think about developers, that was core to everything at LaSeon did early days, but the beauty of Atlassian is model and ultimately, which is reflected in its pricing, packaging and product set is that they knew there was this ecosystem of different audiences and personas that surrounded this developers, project managers, product managers, designers, et cetera.
And they were able to create a world in which. Tools and products ultimately also cater to these additional audiences or these new audiences, but they were always connected to the developer. And I think that was unique for it lasting because ultimately the market was not just developers, which is a massive market, but the market went well beyond developers in the ecosystem around developers, which is very diverse and large as well.
And so from that perspective, I think at last year's audience and market was actually quite large. When you think about Dropbox, I think you could think about it in one of two ways. The first is you could look at it as a potential go to market challenge. Like could they, or we have done a better job with bringing Dropbox's offering to market in maybe a different way.
I think that's a fair way to look at it just because you've seen success maybe across other companies. I don't know if I fully personally believe that the reason for that is, and it's not just cause I worked there and was there, but I think Dropbox has go to market. Always been instilled is incredibly efficient and incredibly focused and incredibly predictable.
And those are the things that make it special as a company beyond just like awesome product that it is and the viral nature of the products. But on the flip side, I think maybe the question to ask, which I'm going to parallel this now to Atlassian was although Dropbox had a broad market, it's the question really for Dropbox may have been, was that market big enough?
Was it maybe 10 billion is how big that file sharing market was at that time. And now Dropbox is I think doing a great job of trying to expand beyond that file sharing market. So for Dropbox, it wasn't necessarily about the core audience that they were going after, but maybe it was the fact that like the actual final sharing market wasn't as big as everybody thought it could be.
And there's many reasons for that, um, competition, different products coming out there that are tangential.
Brett Berson: There were a couple of things that you shared around the idea of the role of the human and the go to market as it related to the first chapter of your career and it Lassie and that I want to get to, but before we talk about that, you just made me think of an interesting thing, which is how do you think about the go-to market machine as it relates to multi-product?
And so can you talk a little bit about what do you have to get right. To make a, multiproduct go to market particularly earlier on in a company's life, not when it's a multi hundred billion dollar company, but when you're aggressively trying to grow and maybe new products are in the tens of millions, not hundreds of millions of ARR, what does that machine look like?
GC: So I'll give you two, if not three areas that I think are incredibly important and relevant, the first is when you're moving into a multiproduct family and this even is relevant across skews as well, when you have a single product, but when you're moving into a multi-product family and you want to create that machine in that go-to market for your organization, the first thing I often think about is the consistency across pricing and packaging.
If you really study it last year, this model, whenever they introduce a product to the market, it looks very similar. Two other products in their portfolio. And so what that means is pricing is similar. Skews are how you move up in options is similar. So they develop this very consistent view of the world that they try to map to each of the offerings that they're bringing to market.
That makes it incredibly simple. If you think about that from an internal perspective and how to operationalize around that, because what you do for in Atlassian in terms for JIRA, you're ultimately doing for confluence and you're doing for any other product in their family set, or maybe even any other product that they build or buy.
And that consistency is incredibly important, especially if it's a new muscle. Second is you have to really understand how it fits into your overall product makeup. So oftentimes what can end up happening is you'll end up building or buying a product that doesn't naturally fit with maybe your current audience or an audience that's connected to your current product set.
So it's really hard to some degree upsell or cross sell this new thing that you're putting out in the market at last year was fantastic at connecting those dots saying, okay, there's a developer we're going to build or buy another tool that caters maybe to that audience or an audience that's connected to the developer.
And I think early days, that was very deliberate. And again, it made it almost over-simplified that multi-product approach. Because again, internally we understood it and externally it was very easily understood. And then the last thing I'd point out early days in bringing a new product on board is focused.
I almost hear this time and time again, where you almost pivot your whole organization to that new product, or you do the opposite where you put something out in market and you just kind of wait and see what happens and you don't put enough attention on it. It has to just become naturally part of your family of products and how you're instrumenting your go to market.
And early days, that's very difficult to do. That's the truth just cause you're probably getting used to building for one product in one motion, but ultimately you want to introduce that new thing into your audience, but also introduce that new thing internally and how to work around
Brett Berson: that. Maybe we could start by talking about, because there are a lot of similarities to the work that you did at Dropbox and it lasts.
And how you think about what great looks like when we're talking about a modern hybrid go to market. What does it look like when it's working? Well? What does it look like when something's broken in some way?
GC: So when you think of a hybrid go to market, to clarify that I'm going to start with a couple ways to view the world today, the first way people view the world today is what I call a very product led motion.
What that means is you lead with product. You can use your product as the adoption funnel or the monetization funnel. So what that means is people go, we'll use the product, learn from the product, try and ultimately could buy through the product itself. The second motion that we talk about is what I'll refer to you as human led.
So human led is when you have human interaction as part of the process, ultimately for most of us, we know that as our very traditional sales model, you can have an inject humans at different points in your funnel, but there's a human led motion to what you do. How I think about it is both of those are important.
And most of the time when people talk about these. Quote-unquote different motions. They talk about them as an or you either have a product led motion or a human led motion, but the truth is you have a company go to market. And as part of that company go to market, you're actually really catering to your customers and the way your customers are trying and buying through different mechanisms, whether it's through the product or through humans, they're inextricably linked, they aren't different parts or pieces to the puzzle.
They actually are connected to. And so to answer your question directly, when you think about what good could look like in terms of hybrid go-to market, it really centers around KPIs. You want to make sure there's connective tissue between your product led KPIs and your human led KPIs. And oftentimes you're trying to figure out how do these motions connect, and there is some experimentation that's part of that.
But the example I can give you is you really want to think through what are the tipping points for your customer to go from potentially a free user to a paying user, which could be through a self-serve or very transactional emotion to a potential enterprise deal. And your KPIs need to actually reflect that.
One of the metrics that I point out there from a very tactical perspective is. When someone's in their product led journey, what is the conversion rate and what is the thing that could take them from what either is a small deal or a free user to a qualified, potentially larger deal and into that human lead funnel.
And if I give the example of confluent, when we created our cloud product at confluent, the first thing we did was we created a free offering. We created a way for users to try the product in a way that was very natural and frictionless. The second thing we did, we created emotion is what we call pays you go.
So what that meant was these users got to a point where one, we were ready to monetize them, but two, they were using it. It's in a way that was monetized bubble and they would pay as you go. And ultimately that meant you could put in your credit card and use the product and continue to use it in particular for most users was in production or at scale.
But what we realized during that process was we weren't tipping or flipping these customers over to our sales motion because ultimately the motion that we created really was relevant in more automated way. But what we also realized was if we could get signal on how they were using the product, there was natural breaking points of taking them from a pay as you go motion to a more what I would call human led motion and how we did that is we actually experimented with ultimately like the amount of throughput that they were using, like how much, and how often were they using the product?
And if they were using it in a certain way, then we would say, okay, they're actually ready to talk to a salesperson because they're using. Past a point, not just in a point of production, but they were using it at a certain scale. And that's something you can experiment your way into as far as picking the right KPIs.
So that's one thing I'd call out. Second thing I'd call out is just around like how you organized your teams. And so what I mean by that is it doesn't mean that everybody necessarily needs to report into one leader, but your org design and how you think through your hybrid motion is incredibly important.
If you think about your current go to market model, and maybe you're introducing something that's product led or something, that's human led where I've seen it work. And what has won is creating almost like these pod structures that include what I call a diverse set of people from the company. And that diverse set really comes from people from different teams, whether that's product management, whether that's sales, whether that's growth, et cetera, and they're meeting on a weekly basis, they really are reviewing the funnel end to end because again, in most cases, A lot of what you're doing on the product led side could and should feed what you're doing on the human led side.
And so really having this common framework of when you meet what you talk about, the tactics you're doing to push different parts of the funnel, this is incredibly important for folks to understand, as you start to build this hybrid or more complex, go to market motion across your
Brett Berson: teams. Super interesting.
Can you share more on in terms of the pod structure who is there and what does that look like? Either? If the main touch point is a weekly meeting, if I was watching one of those meetings that you are running, what sort of going on and what are folks talking about?
GC: I think about the meetings and his pod structure.
I'll give you two ways to think about it. The first is you want the main DRIs and the DRS usually come from the KPIs that you're measuring to be in the room. And the folks that are in the room in most cases are someone from your growth side marketing. Product management, data science or revenue analytics, and in some cases, different operations teams.
So that could be sales, operations, business, operations, marketing, operations, et cetera. The reason this is important because really when you think about a hybrid go-to market, each person in that room, Owns a piece of the go-to market pie there, whether they're building an experience in the product, whether we're selling in a particular way or wherever we're running a specific experience with a growth team, they all have a piece of the go-to market pie in this hybrid go-to-market market.
And we would structure the meeting in the following way. The first is. We'd review the common KPIs that we all agreed upon previously. So there is a set of KPIs that we go through weekly and ultimately everybody in the room is expected to at the minimum, understand those KPIs, but also be able to interact and talk about their specific KPIs.
So there's an owner and a DRI for each of these KPIs. The second is we try to give each other an. On what is happening in different parts of the funnel from a tactical perspective? What experiments are we running on the growth side? Are we changing any messaging and positioning? Are there any launches coming up?
Is there anything new or different that we're seeing or doing on the sales side? Do we need to change something on the backend from a data perspective or an operations perspective in our tools or infrastructure, and you really talk about. Every week and every week may feel excessive to some, but ultimately what I've found over my career is having these weekly check-ins, they don't need to be as deep, every single meeting will allow you to talk about these things and really not miss what I consider is the details and the devil's in the details with these hybrid go-to market strategies and plans and execution.
So from that perspective, I would say that you have to develop a way to do that on a weekly cadence. The last thing I'd say we did that I think was really important and that you would notice in one of those meetings is we spent a lot of time understanding the customer journey. And so we did this during my conference experience and we did this during my Dropbox experience.
We structured a part of this meeting to really understand every step that a customer went through and the interactions they had at those steps, because the truth is what happens in your product. Could impact a sales conversation that you have or what messaging you give a user could impact something that their experience in the product or a sales conversation they're having as well.
And so there was these different aspects of the customer journey that was important to understand, not just from a DRS perspective, but I wanted everybody in the room to really understand it because it could impact their part of the journey. So those are a couple of things I'd call out in terms of that meeting and what she'd like to realize and notice in a meeting like that.
Brett Berson: That's really interesting in terms of constantly coming back to the customer journey, how did you go about discussing that? Did you do it in reverse in the sense that you chose a new customer and backtracked and walk step-by-step through their journey? Or how did you actually explain that in the meeting
GC: hunter.
When you think about customer journeys, they're pretty complex. In most cases, when you talk about the customer journey, the first thing you get is a little bit of a cringe like, oh, do we need to map everything out? What if we don't even know every part of the journey? What if we can't measure every part of the journey, but I think it's incredibly important to do that, especially for those of you listening on the podcast today, early days is understanding every interaction a customer's having along the way.
Good or bad. It's almost like you want a document. What I call the factual journey and that's incredibly important. So the first way I'd say that we did, it was, we did work our way backwards in exactly how you just described it. Everything from when a customer closed one or potentially even when we lost them in backtrack all the way to the top of the funnel.
So where did they actually come from? We wouldn't know if they came from a paid ad. What experience did they have? And then what were the experiences that converted them to a paid user? But there's another part to this. That's incredibly important, which is no customer journey or no customer funnel, at least in the organizations that I've been at is perfect.
As you start to map out these customer journeys, you'll realize both the goods, but you'll also realize the beds. And what we spent a lot of time doing is also mapping out what we would call our ideal customer journey. And so over time, what you'll realize, you'll create this, go to market. You'll create this customer journey that has legacy and has to some degree, even some baggage to it.
And there's probably good reasons why you created or changed or added or subtracted from your funnel over time. But really what ends up happening over time is those changes in those experience could become pretty disparate and to some degree almost broken. And what I really tried to do was help people understand what's our ideal journey.
And then what's the Delta in between. And how do we explain. And test our way into what we would consider a better journey and making sure the experiments and tests prove that what we were thinking, whether it's through intuition, through customer interviews, and even maybe what our data was telling us was the right thing to do.
And so the way it answered that really. We mapped out the journey from when a customer purchased backwards. And then the second piece of that is actually starting to map out what you would consider your ideal customer journey as well. A fun example I could give here is at Dropbox. When I first got to Dropbox, they were roughly a $400 million company.
We were a business that was focused primarily on consumers, starting to go into the teams, business side of things. And over my journey there, we became a very experiment, focused team. Everything was about running experiments, running them at scale, and the truth is running them in volume. We wanted to learn as much as we could and impact the funnel in responsible and positive ways.
And when I got there, we were probably running. About 10 experiments, a quarter across different parts of our funnel that can include the website that can include onboarding that can remain include churn experiences. By the time I left there, if you ask me at any given time, how many experiments we were running, we were roughly running anywhere from potentially 50 to 60 experiments across different parts of the funnel.
In some cases, maybe even more, if you think about that, that has a huge impact on the customer journey because you're changing different experiences across multiple parts of the funnel. And what happened over time was, and I would consider this an area where. It's hindsight, we ended up actually creating journeys that were pretty disparate or broken because there was all these experiments that happen.
And we weren't connecting the customer journey from all the way from let's say, when they entered our funnel to when they purchased. And so as we started to do that with this exercise of building up a factual journey, and then thinking through the ideal journey we noticed along the way that we had broken many pieces of our funnel, they actually didn't make sense whether it was something as simple as the designer, the aesthetics of it, or like the messaging, or potentially even the call to actions.
That was something we had to course correct over time because we came so proficient and good at experimenting, but we actually forgot about the customer journey, a little. bit I think that was one of the bigger learning lessons for me, especially as you're thinking of your hybrid go-to-market as well, is that you can and should experiment across your funnel.
But you also have to take a step back at times and understand that how that's impacting the customer journey, whether the test or experiments you run have an incredible impact, or maybe not as good of an impact. What
Brett Berson: are some examples just to bring it to life. When you're talking about these, go to market experiments, you sort of share it, I think, in the high level, but are there like three to five that come to mind?
That's like, when I'm thinking about really good experimentation and maybe some of the unlocks
GC: you've had. The cell phone question. So this is when I'm going to get animated during this. There's a couple areas that I would say that were impactful experiments for the team, and they all describe them in Dropbox terms.
But I would say that they worked everywhere, that I've been at that's at last, and then that's confluent. And I'm going to get really tactical here because I think this is a fun topic. The first is what I call your money pages across your website. So when you look across most websites, and if you actually look at metrics for Dropbox in particular, we had a couple of months.
The first money page was our homepage. People came into the funnel, dropped in and signed up for the free thing. The second money page was our plans page. And so that was where you would learn about the different offerings for Dropbox, whether it was something free or something that you would have to pay for the third money page was kind of like our trial pages in Dropbox's terms.
So they had a free product and they ultimately had a way to try different products in particular, our business products. And what I learned across those from a very tactical perspective was, and this one's pretty straight forward. Simplicity mattered almost every experiment that we ran, that simplified things like our messaging, that simplified things like our positioning, that simplified things like our pricing or packaging that made it much easier for a user to understand almost always won And I'll give you a. Perfect example here. We had one of our money pages was this Try page for Dropbox business. And we had an incredible amount of traffic, both flowing through that page and converting on that page, but we believed our conversion rates could be higher. And we actually learned this through a team that we had Self-Serve Assist which if you think about self services, that is a team that ultimately is on the chat modal that's on your website.
They're the team that's talking to customers about questions that they have, but a very customer success customer service oriented team. And the one thing that this team was telling us was, Hey, when people come to this trial page, we ask them for a team. name And they really didn't understand why they were trying the product.
The truth is maybe they thought that other people at the organization, if they put in their team name and the organization that they were at, that they were going to know they were trying the product, but they're like, Hey, I just want to try the thing and see how it is. And then I'll come in and say, By just removing that team name, field.
We probably had a 15% uptick in conversion, and I know that's not a crazy number, but in Dropbox volume, that was actually an incredible number. It's actually millions of dollars. Second fund example. I'd give you our plans page. We spent a lot of time when I say a lot of time, we probably ran hundreds of experiments on our plans page on the Dropbox website, we spent a lot of time really trying to hone in on understanding the users that came to those pages and what experience we should drop them into.
And I think that's relevant when you even talk about the hybrid go-to market. Like the question we always try to answer is what type of user on you are you and how can we best fit you into the best plan for your needs? And then ultimately our go to market would match that. So that means you can go through a product led motion or a human led motion.
Some things we did, there were everything from changing the design of the. To giving you more or less information. One of the pro tips that I throw out there for many of you that are designing different plans, pages or SKU pages is customers love FAQ's. So any time that we added more clarity, even through FAQ's, let's say at the bottom of the plans page or to the side of a plan's page, it always won.
It always was worth its weight in gold. The next thing I call out. Pricing pricing is your friend and your enemy. As you go through this experimentation and making this tangible a lot of times when customers come to your site, especially in like volume-based businesses, they're just trying to figure out how to try the thing and ultimately how much the thing costs.
And if you're not clear on your pricing and packaging, and it's confusing for a user, even the definition of how you charge, if people are confused, they will. And what we learned, uh, over time in particular, in my Dropbox experiences, the more we can make pricing, not just friendly from our perspective being inexpensive, but giving you value, but explaining the value of that pricing and how pricing actually worked.
And it became easier for them to purchase essential or at least try the products because they were more trusting and it was comfortable and clear as part of our privacy motions. Those are a couple that I'd throw out there that might be easy to implement to some degree for many of you and ultimately paid dividends for Dropbox.
Brett Berson: That's awesome. Flipping back to what we were talking about a few minutes ago, in terms of KPIs and the connective tissue between human led and product lead, maybe just tell us the story of the KPIs that you landed on at something like at LaSeon or confluent or whatever example to make it clear. Like if you're getting it right, what would a set of KPIs look like that really acts as that connected
GC: to.
When you think about KPIs, the one thing I'd throw out there is you want your KPIs to be digestible for everybody in your organization. And the litmus test for that for me is if you walked up to anybody on your go to market side of the equation and ask them a question, like, what is our activation metric?
What is the thing that helps drive users behaviors? And what are we trying to drive as part of user behaviors? If someone can't answer that or it's too complex for them to answer the truth is you're going to have trouble driving that metric because they don't understand it. So with all that said, when you think about the core KPIs that are connective tissue in this hybrid go-to market, the first is simply put how many people are going from your product led motion.
And what's the conversion rate of going from that product led mode. To this human led motion, like how many people are to some degree moving from that one experience to the human experience. The second is paying close attention to what I call activation, but I'm going to separate activation into two buckets.
The first is onboarding activation. So what does it take for people to get comfortable with your product, understand your core features and offering maybe even get to some of the aha moments, but that also doesn't mean they're going to be ready to purchase or potentially participate in a sales conversation.
They're just learning how to use the thing. What is the metrics or monetization onboarding activation is what I call it that actually get them to the point of potentially purchasing or at least leading to a sales conversation. And if you think about that in, at Lassie, in terms, and this is probably dated in terms of the definition there.
But if you think about that at, in it lasts in terms like for a product like JIRA, the core onboarding activation metrics, where something like create a project in JIRA, create an issue, have others collaborate on that issue that didn't necessarily mean you were going to buy JIRA. That meant you were using JIRA in a way that could lead to somebody potentially getting to a monetization moment.
That's really critical because you may want somebody to not only create a project in an issue and collaborate on that issue, but you may want them to move that issue through the workflow. You may want them to create multiple issues. You want to make sure you're really defining what these monetization activation triggers are to get users to that next step in their journey and that's to give you money.
And then again, that's part of your hybrid strategy is. When should we actually drive people to a purchase via the product versus a sales conversation? That's going to be critical to almost everybody's journey on the line. It's really figuring out what motion is best for that user. At that
Brett Berson: one thing I'm really interested in is how do you start or figure that out in the sense that you meet a company that has a million and a half in revenue, they're trying to do a hybrid go to market.
They're not particularly well instrumented. Where do you even begin to sort of get to the point where you're so fine grain that maybe in the consumer world that's sort of the classic Facebook eight friend thing where if you get to eight friends are going to be super engaged. I'm hearing you translate that into a new way of thinking.
In the B2B context, you talk to founders all the time, where do you start?
GC: Good question. So I think there's a key way to think about this, which is most companies don't have the fortune of an Atlassian or Dropbox early days where they have enough volume to test these theories enough and beat up on the metric enough to get the best metric that they could and the best definition that they could.
So here's oftentimes what I tell people is. One inform yourself through customers. So as you have conversations with customers and you should be really listening to what's really the triggers for them and the definitions that are taking them to that point of monetization. What are some of the key elements that are important to them in your product family?
You mentioned the Facebook eight people thing. And so that's one. You want to have these customer conversations, but the second one may be is. As obvious, which is the truth is for many of us where you're trying to build a business, there's a lot of unknowns and what ends up happening, especially with a lot of these different metrics in particular metrics like activation is probably the one I see the most.
You go into analysis paralysis, you try to look at data. You try to look at a bunch of customer behavior, but the truth is sometimes you just have to pick a metric and a definition and then measure that. That was actually exactly how we approached it at confluent. We try to understand how our customers were using the product, but ultimately we knew we weren't going to define the perfect metric on day one.
We knew we would have to iterate it. My theory is if you pick a metric and a definition, and at the minimum, if you're measuring it, you're going to figure out pretty quickly. If that metric is right or. wrong And then you could adjust it. There's some beauty and failing because it allows you to learn and get to that next step in your journey.
And so what I tell people is to some degree, use a bit of intuition and say, look, how do we expect our customers to activate and use the product that gets them to a more monetizeable moment? And if you do that at the minimum, you're measuring something. And then by measuring something over time, you're going to see if that's the right or wrong direction and be able to tweak it from there.
Brett Berson: In the case of this idea of just starting with a metric and a definition. What was that when you jumped in at.
GC: It was pretty straightforward, which is one, if you think of a product like confluent, for those that maybe don't have context, it's very usage based. And so if you're not using the product and if you're not using it for a certain period of time, ultimately what that means is you're probably not.
Activated in any way. And so what we noticed and what our intuition was from talking to customers was customers that were kicking the tires really had bursts in their throughput. So what I mean by that is like they were using the product intermittently and then shutting it down. But for users that were using the product in particular, what we said was seven days, why did we choose seven days?
We felt like seven days could show us that you were using the product through the weekend. And to some degree with infrastructure products, there's kind of like the set it and forget it. So meaning like you're using it in a way that's ultimately most likely in production and you're going to set it and use it over the weekend.
So we chose seven days and throughput during those seven days consistent. And if you did, we actually considered you a monetizable organization just from that one metric.
Brett Berson: That makes total sense. One of the things you talked about a moment ago was there's a lot of value in this, came back to sort of this weekly pod meeting of getting alignment around what the ideal customer journey looks like.
Can you give us some examples when you were thinking about and designing the ideal customer journey maybe at, at Lassie and maybe at confluent, what does that actually look like end to end? And
GC: you're mapping out your ideal customer journey. Let's say the truth is you want it to be very visual. So the first thing we did, we actually.
Took screenshots of the experiences across the board. So you can use, there's a number of tools out there. I won't pitch any tool, but ultimately there's a number of visual tools that you could use that actually can map this out for you in a very detailed, wearing a very visual way. I personally am a visual learner.
And so that's how I mapped it out. So the first thing we did was we actually would sit in a room at an offsite and ultimately map out a first draft of the journey pretty much end to end. The second thing we do is as we look through this ideal customer journey from a tactical perspective, we'd really try to figure out what metrics were involved in each part of those journeys.
So how do we measure it? Or could we measure all these different parts of the journey? Again, it's not looking for perfection here. It's more looking for, is it something we either measure today or could measure down the line, but it was also to give us into. How do we expect people to progress along the journey?
And sometimes what you'll find when you do that is there is what I call constructive feedback. Why would we measure this at this point in the journey? Maybe we should do it later. Maybe we should do it before. And the third is we actually would try to map the Delta between the current, what I call real experience to the ideal experience.
And that was really beneficial for us because it started to give us a sense of. How different was our ideal funnel versus our current funnel for Dropbox. When we created our cloud product, it was a new offering for us. It was cloud previous products were on-prem and we really had to rethink the customer experience because the majority of the experience for our users in the past had primarily been on their own machines.
So we had to create this really new experience for them. Um, and I'm also running. Everything that we did in the cloud. And so when we started off the journey, it was a pretty vanilla experience. We drop somebody into our products. We didn't do maybe the best job with onboarding. We were learning about the onboarding experience.
We were trying to figure out what they wanted to learn. We were trying to figure out the metrics, all the stuff that goes along with introducing something new, but over time, what we ended up doing and learning was mapping out this ideal customer journey and saying, Hey, if someone comes in the funnel and they're this type of user, what experience would we want to create for them?
And as part of that, and you can even see that in the product today, we started to create a richer onboarding experience. We started to create more intelligent questions to even ask in the product we started to create. I would say richer, contextual experiences. And what I mean by that is contextual experiences and products.
So you can learn, but also giving folks an opportunity to engage with a human or maybe other pieces of content that were not directly in the. There's an opportunity for you to reimagine how your users are going through your funnel. And then over time, what we did was we turned that into experiments. We tested these theories in our ideal funnel.
One
Brett Berson: follow-up would be, you talked about the process for you is mapping out the ideal journey in a visual way. I'm interested. Could you sort of expand on that a little bit in the sense of you map this entire thing out? And I was at that offsite with you, what am I actually seeing? Like walk me through what the journey actually is in the way that you think of.
GC: There's a couple of components. So one, if you're mapping out very visual journeys, again, you hopefully are doing it with a tool, but you could also do it on like a whiteboard. The first thing we would do was go through each stage of the journey. I'm going to use the acquisition phase as the example here, which is if you are acquiring a user and let's say confluence terms like we're acquiring a user, that's a developer, what would be their first experience with us?
One of the first experiences developers have with confluent is they're either learning Kafka, which is the technology that they use, or they're being introduced to something like data in motion, or real-time streaming. How this would look is we'd say we want them to land on a landing page. That's Kafka 1 0 1.
And then ultimately there would be fields under that. That would say one. What do we expect the user to see. To what do we expect the user to learn three what's the KPI that we're measuring. I'm oversimplifying it a bit, but those are the three things you would see for that part of the journey. The next step is as part of the acquisition phase is like, okay, if they were on the Kafka one-to-one site, what's the potential next step in that journey.
And that can be a treat. They could take multiple steps or go through multiple different paths. The next step would potentially be, Hey, we've now got them on this Kafka 1 0 1 site. How do we get them closer to our products? The next step could be sending them to a product landing page. Once they've interacted with the site in a, in a certain way, or the next step could be firing up our marketing channels for.
When they were on this site, could we retarget them with specific pieces of collateral? Because we know they're a developer and we know they came to this Kafka one-on-one site. So you can kind of create these digital experiences that bring them deeper in your funnel. And so from that perspective, that visual mapping, if you think about that for each step in your journey, I think is quite rich.
It can almost give you a roadmap of sorts of what you need to build and test in order to prove out what is the ideal customer journey for your customers.
Brett Berson: That's super, super helpful. And I like the way that you frame the three things you have to answer for each step in the journey, you sort of framed it as a pro tip.
One example was simplifying pricing pages and adding FAQ's regardless of where you've worked. It's just a play that you can run. It'll probably be beneficial. I'm interested. Are there other things that come up like that for you? That's this is your cheat sheet and you validated across different companies.
If you are not doing this, you might consider doing this because I found it to be very
GC: useful. Definitely. I can take you through my thought process when you're either advising for a company or learning about a company, there are some steps I take to really figure out to some degree even how their go to market work.
So I'm almost trying to guess at what they're doing. The truth is secretly. I map out their customer journey myself by just navigating everything from their website to their product. And I'm trying to figure out exactly how their customer journey works, because I think it gives me a real experience.
Like that's the experience that I'm having, which may be different than the experience that they're explaining. So let me go through that. The first is from ultimately an SEO and paid advertising perspective. I look at what they're targeting and the content behind those ads. So I try to figure out if a company is targeting, let's say, and I'm using a generic company here.
If a company is targeting something like. Um, let's use white boarding is the example. If they're targeting white boarding and that's something I searched for, and that's what the company is potentially about. If I go to an ad where they're pitching everything they do for white boarding, and I click on that ad, I really focus on the experience that a customer goes through there.
So what I mean by that is I look for the CTO. Are they sending them to a more self-serve or product led journey or are they trying to drive me to a sales conversation and it may or may not be the right thing. Maybe I'm not the type of user that should go to a sales person. So I may a question. Why do they have that experience for me as part of their.
Second thing I do is I go through their website and I try to identify what I consider the money pages. And then I also try to think about like, what are the right CTS for those money pages? So, as an example, if I go to a homepage, what is the primary CTA on their homepage? Are they trying to drive me to like a free experience to try the products or are they trying to drive me to a more human led experience?
And I really pay attention to that because again, that's going to impact the way I'm going to experience the company and the product. The third thing I look for, I try to identify most of us look at websites in the same way, which is we maybe read some of the headlines. We read some of the call to action.
So I try to get a sense of what are they trying to tell me from these headlines or their CTS, what can I learn about the company? What can I learn about the product ultimately in probably 15 seconds? Because most of us don't spend that much time on webpages. I do the same thing in the product journey.
So I spend a lot of time really thinking through, okay, they're presenting me with this onboarding experience. What are the three aha moments they're trying to impose upon me as part of that experience? So I will sit through the onboarding experience and say to myself, okay, what are the three things this company wants me to learn?
And are those the three things that are useful for me? Did they sell those three things properly on their website? If I don't understand those three things, can I contact somebody or have a conversation with somebody that maybe is not sales driven to understand what those.
Brett Berson: That's super interesting. So you've developed this diagnostic.
Somebody brings their car into the shop and you have the set of things that you do. And so I'm really interested in, I assume you've done this probably dozens of times now, this diagnostic. So what do you tend to find are the most common mistakes or you do all this work and then you meet, maybe it's the founder in an early company.
Maybe it's a go to market leader at a more mature company. What do you find yourself constantly telling people after you go through this.
GC: That's a fun question. So the first thing I find myself constantly telling people is your calls to action. Aren't clear what you're expecting a customer to do next.
If you ask somebody to like verbalize it to you versus what's happening, let's say on their website, or maybe even in product doesn't match what they're saying. So you're like, you're not matching what you want them to do, versus what you're telling them to do. The second thing I realized is, and this comes back to the hybrid go-to market model is oftentimes you're confusing the customer.
You're almost giving them too many choices on the paths that they can take. If you want your customer to always start off in your product, your CTA should reflect that your CTA should be like, look, try the free product. And then you can figure out how to layer on different things like a human led motion or education or whatever it is as part of that journey.
But oftentimes they're trying to. Give the customer, all those options off the bat, which I think is incredibly challenging for users, because they're just trying to make a choice. The other thing I would say that's obvious to me at times is they haven't defined their activation metric in, even if they haven't defined it, they almost maybe don't have a strong enough opinion on it or hypothesis behind it.
So when you get dropped into a product experience, what ends up happening is you as a user. You're not finding the value as quickly as maybe the company would hope because you're kind of sending them along a pretty generic onboarding path. And you're also not giving them an opportunity as a user to really experience the power and the differentiation that you offer from your product.
So ultimately what that does is it kind of leaves the user with like a matte feeling because you haven't defined it and you haven't been opinionated on it. The user actually has to try to figure that out on their own. And the truth is sometimes they don't. And I think that could hurt you. And the last thing I'd say is a lot of companies don't spend enough time learning from users that leave them or actually do it.
Try or by what we did an incredible job, I think at, at LaSeon and Dropbox in particular is, and I continue to be obsessed with this, which is you can tell when you're navigating an experience, if someone cares that you dropped out that caring doesn't mean they have to talk to you and sell you on something, it's more like, why was our experience maybe broken or not good?
Or why was our product not good? And I think what ends up happening is a lot of companies just don't spend enough time understanding why people left and actually taking the time to talk to them. I see that all the time. I think you could relate that to being an unopinionated or to really focusing more on why you're winning instead of why you're losing one of the things you just
Brett Berson: shared.
There was this idea of a good versus bad activation metric. I was hoping that you could talk a little bit more about that. Give examples of like a really good activation metric and maybe some that aren't as used.
GC: I'll give you the Dropbox example and this isn't to disparage Dropbox in any way, because I think their activation metric was fine tuned over time at Dropbox.
One of the key things that we constantly tried to think about was what is the best experience to give our users, to take them from a free experience to a monetized experience. So take them to in Dropbox's terms and what they call their packaging, our plus product, our pro product, or a business product.
And you were looking for signals. Ultimately, that means how are you using the product? And here's what ends up happening in a scenario like that, where you're looking at. Okay. Like what are the signals that suggest that somebody is a high value user or a monetized mobile user? You start to look at things like in Dropbox, How they shared files and who they share files with.
You start to look at things like activity with those files, where they coming in and out of the product and using those files in a particular way, you start to look at how many people they were sharing, what types of files they were sharing in responsible ways. But if you think about just those four things.
They were an and statement. So we created like an activation metric that said you are sharing with a certain number of users and it's potentially a certain type of file. And your activity is at this level, what ended up happening over time was those three variables. We were trying to drive all of them in different ways.
And the activation metric became a bit confusing and convoluted. We weren't actually sure. Which one of those was actually driving the behavior. Could it have been one of them? Could it have been all three of them now taking a step back, we kind of started to look at that and statement and we started to create an or statement.
So we said, Hey, is somebody in a more monetizeable state if they're sharing with a certain number of users from their domain. And it's a certain type of file, it's a bit easier to understand. Or maybe we're looking at people that are sharing what certain types of users and they have a bunch of activity on those files.
It didn't matter what type of file. So we started a tree of or statements that would allow us to get sick. And create experiences around how to better activate a user and ultimately for Dropbox that led to better monetization.
Brett Berson: Great. So to wrap up, I'd love to explore just a little bit about team building against this sort of strategy.
One place to start would be, let's say you were to wind back the hands of time and it LaSeon was starting today and you join the company and they have a million dollars in revenue. It's a 12 person team. There's no go to market, but there's real market pull and product market fit. And you believe that this is the right type of product pricing, et cetera, to make this hybrid concept work.
What advice would you give to the founder in terms of what the next year or two looks like from an org design hiring profile perspective to really go after
GC: that? Whenever I think of any growth team sales team marketing team. There's one key thing that I focus on, which is I'm looking for what I call puzzle solvers.
And these were always my best first hires. And what I mean by puzzle solvers is in most cases, early days, you're trying to figure out all these different aspects to your go-to market. And you mentioned this earlier, where you may not have some of the metrics. You may not have some of the people, you may not have some of the cross-functional teams.
You may not have some of the tools and you want somebody who can come in and who is trying to really piece together your go to market story. And when I look at their profile, in many cases, I'm trying to look for people that are almost like management consultants. They have a profile of really trying to solve.
Large complex problems. And the truth is they try to solve them in most cases, both in a consultative way, but also in a data driven way. And I think that's incredibly important early days, just because you may not have those things at your fingertips as you go later on, you'll get specialized. But I really feel like in the early days that that's one place that.
The second thing that I tell folks is diversity of skillset in particular, around your marketing and growth teams. And here's what I mean by that is if you look at the profiles, especially because growth is such like a broad term, it's almost nebulous at times is they can have skillsets that range from somebody who has more of a product or product management background, they could have a core marketing background, they could have a data background, et cetera.
The thing you want to create as part of these teams, irrespective of org design and, and exactly who people are going to report to is you want skillsets that compliment each other. I think we did that incredibly well at it last year, but this really almost formed me. I always called them like mini power teams.
And even to some degree connects to the pod structure I described earlier, which is you want people early days, especially for that first year with a diversity of skills.
Brett Berson: So on the mini power team, can you give an example of, I assume it's maybe five to seven people, what specifically are those people or roles, and you talked a little bit about the actual skill sets, but when you think about the best mini power team that you assembled in the last 10 or 15 years, can you share a little bit more about what that looks.
GC: So, if you think about these mini power teams, there's a couple areas that I try to focus on at any point in your hybrid go-to market. What do you need? You need somebody who's driving the metric, which in most cases for me was the management consultant type. And you need somebody who can understand the full story.
Second, you need somebody who could speak to the user or customer and understand who they were and what you should say to them. You needed somebody who can really build the right experiences, whether it was as something as simple as changing some of the experiences on the website from a conversion perspective or building in product experiences like onboarding, et cetera, and being a part of that, which is the product person.
And then the last is you want somebody who's looking at all those insights and really helping the team understand what's working. What's not building the experimentation framework, understanding the data, et cetera, and that will come from your data person. So those are four of the key ones that I'd call out.
And that really is how we structure the teams in particular at Dropbox.
Brett Berson: I wonder to follow up on the puzzle solver profile. Can you tell us a story about a couple of those people that you've worked with and maybe what they did before and was literally their last job is like they were working at McKinsey or you mean that in more of a broad sense.
GC: I'll give you the two different profiles of what I call puzzle solvers. The first is exactly how you just described it. I called them McKinsey types. And in some cases, yes, they did work at McKinsey or the like, and if you think about what they brought to the table, One was they brought a framework and structure to how they thought about solving a particular problem.
And I feel like those are worth their weight in gold, as you're just trying to structure your, go to market teams and figure things out. The second thing they bring is like an analytical mindset. And so what you'll find is many of these McKinsey types, then how to translate metrics into a plan or a strategy.
What you'll also find in this type as well, which is interesting is you'll actually find product marketers that fit this profile as well. So what I mean by that is they largely think about the customer and can connect metrics to how to drive that customer behavior, because they're constantly thinking through what's best for the customer.
And ultimately some of them do have a very analytical mindset in how to drive that customer behavior.
Brett Berson: When you've run a really good interview loop for evaluating this type of person, what does that process look.
GC: Good question. I would consider myself an unorthodox interviewer, but I think the process looks like the following.
The first thing we focus on in the first couple of interviews beyond what they've done, as far as their experience is actually presenting number problem. There's a lot of fun questions that you can come up with, but the goal is actually not about the question and you hear them any fun questions that come out of places like Google or whatever.
I try to give them a real world example of what we're doing at the organization today and what we're trying to figure out to be tactical. In that example, you know, let's say, uh, during my days at Dropbox, one of the big areas that we were trying to juice was how do we take this freebase and turn them into monetized?
Uh, pretty open-ended area, but ultimately what I wanted to do was have some of these folks walk us through, how would they create a structure and a plan around how to drive people from free to paid. And that was part of their interview loop. And then what we'd do is we'd actually take them through a project and kind of think through together and brainstorm ultimately, how would we take these users from a free state?
What would we need to learn? What are the KPIs and potentially even what are the experiences that we may want to create to take them to a monetized state. So we'd kind of give them a realistic puzzle to solve and get them thinking about and verbalizing how they would do that. And to some degree show how they would do that.
The third is we'd have them spend time, not only with folks on the sales and marketing side, but we actually had them spend a lot of time as part of the interview loop with both our product and data teams. We wanted somebody who could engage with those groups and who also could think a little bit more like to some degree, a product managers.
Brett Berson: Do you remember when you think about the Dropbox days of interviewing and designing this project around free to paid what an exceptional person did or what they came back with that you were super impressed with?
GC: In most cases, what they came back with that I was most impressed with was it'll tie it back to the topic that we discussed earlier, which is they actually started to map out the customer journey and think through the experiences as part of that journey, I could actually see the interview in my head where one of what I think was one of my best hires actually mapped out an ideal customer journey as they saw it and mapped out the KPIs that were part of that journey.
And they supported each area with some level of reasoning, whether it was data, whether it was something they learned to scouring the internet, whether it was talking to customers, et cetera. And I thought that was exceptionally powerful for me because I was like, oh, they really are trying to get into the mindset of solving this puzzle, but in a very operational and tactical.
Awesome.
Brett Berson: Perfect place to end GC. Thank you so much for all this time. This was awesome. Perfect.
GC: Well, I appreciate it.