Lunch with Benchmark Capital: The Playbook to Evolving Your Product Genetics

Benchmark's Miles Grimshaw argues that scaling past product-market fit requires measuring adoption depth, not just revenue. He points to Benchling, Airtable, and Segment as examples of companies that grew by focusing on power users and building integrations that create ecosystem effects.
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Please welcome to the stage Miles Grimshaw, General Partner, Benchmark. Good afternoon, everyone. It's great to see so many in person and in the Bay. So today I want to talk about evolving your product genetics and continuing to expand the peak potential of your company. But first, where does this metaphor come from? Product-market fit can often be talked of like a new magical chemical reaction. A special combination of atoms is found, and now it's time to scale production. Or it can be talked of a little bit like an assembly line. You've built a fantastic new design, the new product's there, you've got some— the first versions of it. Now it's time to scale. I think these metaphors can lead to a fairly mechanistic view of scaling and of the journey post-finding product-market fit. It really leads to the supremacy of the spreadsheet at even a couple million of revenue. My metaphor for finding and, and the journey post-product-market fit is more that of a dynamic biological system in which your product DNA really encodes a set of traits that you hope will attain peak fitness in the market. Your product DNA really is what sets the frontier of what's possible for the business. Now, just because you're tall doesn't mean you'll be a great basketball player, but it certainly helps. And it's that product DNA that I think ultimately shapes the, the complexion of the business down the line. How sticky is the revenue? How much sales and marketing? Is required, how much natural expansion is there in the base of the customers, and the like. And I think instead of just focusing on the spreadsheets, it's important to keep attenuated to that product success. And so today I want to share a few strategies of how we've kept product evolution at the forefront of some of the companies I've had the fortune to partner with— some horizontal companies I've served on the board of like Airtable, Lattice, and Glide, some vertical software companies like Benchling, and some very developer-centric ones like Segment. So the first pillar I wanna share today is that of measuring product adoption, not just revenue. Very quickly post early success, I think B2B teams can start focusing exclusively on classical revenue metrics, and those product metrics can start to fall by the wayside. And I think that's a mistake. And a fun analogy I like to think of that at the end of this year, unfortunately may not be relevant anymore, is that of your Instagram feed versus your TikTok feed. Your Instagram feed, up until they start to change the product now, is that of your stated preferences. You've said, I want to follow these people. It was an opt-in relationship. That's like a customer sale. A customer says, I want to buy it. Where can I sign? Please give it to me. Your TikTok feed is your reveal preferences. It's what actually gives you the dopamine rush. It's what actually gives you the energy. It's what actually is successful. I think of that as your product metrics. Is the customer actually using it and getting the proper fulfillment from it in the way that you'd hoped? And so I think great teams ask themselves, is the product delivering on the full potential of customer value, not just measured by revenue? And so a few ways with some of the teams I work with, we've done that. BenchLink has a wide suite of tools for life science research labs, everything from single-player tools to whole teams to departments. Early on, as we started to have some success, we created this idea that we even tracked at the board level of a golden land. And, and we said, alongside obviously the revenue that we're trying to attain, we really want that adoption to have the complexion of many, several people in a team using it and using the core database and core collaborative products that, that we aspire to have them adopt to make the central system of record. If they were just using one of the single-player tools, it wouldn't drive this metric, which is what would realize the full potential of the product. At Airtable, you might think this is a typo and I meant to type MAUs, which is what makes it kind of a fun one. Uh, but it isn't. It, it stands for multi-user actives. And at Airtable, you can use the product as a single player. You can have great success in that way. But the full potential of customer value is when you're really using it collaboratively. And so we track not just revenue and we tracked MAUs, but we really had at the forefront this idea of multi-user actives and measured that and, and, and evaluate our success on that. A very different one with a, complex graphic that I took from one of the early Segment board slides that we worked on together. Segment, if you don't know it, is a data platform of which— on which to sort of centralize all of your customer data. And there are many ways you could send data to us, or we could send data back into other systems. Four big pillars of that were the web product, the mobile product, your cloud, a cloud source like Stripe, or your warehouse. There's a lot going on in this graphic. There's a representation of the many different ways you you could integrate us. And at the center is you using all four, which really was the full power. You put us at the center of your customer data, and we were deeply embedded. Now, as you can probably tell from the shading, not every customer, not all of our revenue was in that magical center, but we kept attenuated to that along the journey and asking ourselves, how can we drive more and more of the customer base to that center? And so as you start to scale and find early success, I think it behooves you to ask, "Is the product really delivering on that full potential of value?" A second idea I want to talk about in strategy is that of good customers versus bad customers. If you think of mechanistic scaling post-product market fit, revenue's revenue. But if you think of it more as a dynamic evolutionary system, revenue and different customers have very different value to you. And so which customers will really pull the evolution of your product further ahead? One of the great ways to do this is to ask which are the market-leading companies in your industry? Which are the ones that are really pushing the forefront of the industry forward and that will pull you along with them? Not only will they demand excellence of your product, but you will get insights from them that none of your competitors can get. And that will give you an important edge. There we go. Sorry. I think Stripe is a prime example of this. Early on, they might have actually started trying to sell to, I don't know, Bed Bath Beyond or the like, but they didn't. They really focused on digital native leaders, companies like Shopify and Lyft, who are setting the forefront of what was possible for the digital economy. And pulled excellence from their product. BenchLink, we sold the research software we talked about to life science research teams, and we really focused on the innovative new drug discovery companies. One of our first big enterprise accounts, still an important one today, was a company called Regeneron, which while they didn't invent the COVID vaccines, they did invent the leading COVID antibody treatment that the former president actually took when he got COVID. And they pulled excellence and demanded the future from our product. And even a more simple example, Lattice. We really focus on about 50 to 2,000-person companies. But we were focused on that and tried to not let drift happen that would demand our product got pulled in different directions. And so maybe some of you are a smaller company than 50, and you'll tell me that we're actually kind of annoyingly expensive for you. And that's on purpose. We're not really trying to win you, but if you so choose, okay. And also aggressive sales reps have come along through the years and wanted to retire as much quota as fast as possible and brought us a 5,000-person account. And by and large, we've turned them away because that's not where we've really wanted to find our success. And if we have those customers, they'll pull us in a direction that isn't where we want to be focused. And so if you think of it as this, like, evolving dynamic state, those feedback loops that will drive that are are really most powerful when you put the right customer at the center. To be customer obsessed, which everyone obviously aspires to, important to ask who we're being customer obsessed on. Another pillar I often think about with the teams is how can the product get better as we get bigger? Social companies, social networks, marketplaces, they have this in their DNA naturally. They don't have to think about it. Software companies tend to have more silo customers, they're more individual, and so it's not as natural, but I don't think it's impossible, and I think it's always worth keeping at the forefront in that moment post-early success. One of the great ways, and obvious ways to do this, is that of sort of shared data or shared integrations. Chainalysis is a product that is used to try and understand and take action on nefarious transactions on various blockchains. and they have all of their users and all of their customers contributing to that shared dataset across their customer base, continuing to improve it, making the product get better as they have more success. Segment— we built the broadest integration library, and we spent a lot of time making it easy so that other people could build integrations to us, bringing us into their products and building that ecosystem faster than we ever could. All of that made us better as we continue to succeed. And even Lattice, which you think of like a very insular experience, it's ultimately your performance management software. As we've built out engagement products and now launching a compensation product, we anonymize that data and allow you to intelligently compare across that customer base, making the product actually get better as we succeed and have a larger base. Another way I think about this is the metaphor of a city. You've probably noticed sort of centers of gravity emerging around the world, and we think about it very natural. It's an organic phenomenon. Why does Silicon Valley have a density of technology companies? When you look even with inside a city, why are bakers or butchers kind of all in the same area, all in the same streets? Why is there a fashion district where most of the fashion houses are? Economists have a fancy term for this, as they always do, called the agglomeration effect, and it's used to describe that organic evolution. And the nature is one of the marginal participant in that industry, in that ecosystem, wanting to be there versus somewhere else. And I think a software company can think with that mindset. How can we sort of be like that city? How can we be the place where the marginal participant in our ecosystem is most incented to sort of spend time spend energy around us and cultivating that mindset early. At Benchling, for some of the very early years, we really focused on academics and students. They were the in— the in— participants who ultimately would end up doing this professionally. And so we cultivated and nurtured, even though it didn't show up as revenue, a great student and academic ecosystem. And now we're cultivating, as many do, an ecosystem of implementation partners and integration partners where their success is advanced by locating and being around our center of gravity. GitHub and Shopify are obviously big examples of this now at great scale. GitHub students got trained in using GitHub before they went off into industry. Any open source project obviously most incented to be there, 'cause that's where the largest developer base was, leading to a breadth of integrations. And Shopify, There's a whole ecosystem of partners building templates and integrations and businesses built on top of it. It's almost like they're a city, and anyone who wants to be a part of that industry is really incented to locate there. Now, not all of this will show up as revenue out the gates, like it might not when your $5 million of revenue make you $6 million, you know, extra, add an extra million to the target next year. But it'll set this genetic foundation for even greater potential and push that out. The last thing I want to share is that of the second product arc. And I think this is a way to obviously radically evolve the frontier of what's possible for a given business. And you can start on it, and many have started on it earlier than you might imagine. Benchling, as I talked about, got started as a single-player product just for scientists. We've evolved into that of being used in a team, in a lab, in a department, by the entire function. And we've continuously focused, and you can see the rate of velocity, a product surface area that either expands the scale of the organization that we can serve into or other functions around the, the, the core set of scientists that we prioritize and the rate at which we've kept doing that along our journey. At Segment, we initially got started really building for engineers, the simplest way to integrate your customer data and have one central nervous system for that. Obviously, that can be used by marketers, and, and now is very much used by marketers, but early on it was really engineering and developer-centric, one simple integration for every integration. At about $20 million of ARR, we started focusing on what we ultimately launched at about $50 million, as the Personas product, which was really this way for marketers to actually have a single customer ID to use for retargeting or, or, or journey marketing, et cetera, which wasn't a constituent that we necessarily served out the gates. And we launched that at about 50, and it transformed win rates in the company against any competitor and was ultimately foundational to creating what became the customer data platform category. At Lattice, as I've talked about, we started just with performance reviews. And at about $3 million, less than $3 million of ARR, we made the crazy call with the small engineering team we had and focused tons of them, almost all of them, on building out the engagement surveys product. We launched that at less than $10 million of revenue and became the first company that was serving that mid-market to actually have both. And it transformed win rates and had a profound impact on our positioning and success in the market. And two other fun ones that I think about that are very different, a very horizontal company and a very vertical one, HubSpot and Viva, that have done very well, obviously. HubSpot, obviously, for those who remember, started as a marketing-centric product. And when they were about 70, they staffed a sales team, they actually made a small acquisition to start working on this. And as they crossed about $100 million of software revenue, they really launched it. And that sales hub now is close to half, I think it is, of their entire revenue. And Veeva got started as a CRM on top of Salesforce, built on top of Salesforce. And when they were only about 20% of subscription revenue, started working on their own product Vault, which was clinical trial data management and the like. And they launched it when they only had about $30 million of software revenue. So these stories, these second arcs that will really transform the frontier of what's possible can start earlier than you imagine. And I think it will push, starting to focus on this earlier, teams to not just ask, who can we sell to, but move back into that motion of, what can we solve for? What problems are out there that we can uniquely address? So I think if you think of product market fit as much more of this dynamic state, it'll incent you to keep focused on the software, not just the mechanistic scaling of the spreadsheet, and ask the questions of how can we evolve this product DNA to really expand our peak potential. And so some questions to leave you with: Do we have a good view into successful adoption, not just sales, of our product? Who are the customers we should be listening to and training our feedback cycles on? How can our product get better? How can our ecosystem get better as we get bigger? And what's our next product arc? Thank you.
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