How to price your product | Naomi Ionita (Menlo Ventures)

Naomi Ionita (00:00):
Do not set it and forget it. I see companies do this, where they labor over designs and features. And they build this perfect product that's delightful to use. And then pricing's sort of plucked out of thin air, and then they don't revisit it. This was Evernote. It was many, many years before we went back and overhauled the pricing. So, think about your pricing just like you do your roadmap. Every 6 to 12 months, there's probably something meaningful that you're launching for users. So, treat that as an opportunity to revisit your monetization strategy and making sure you're compensated appropriately.

Lenny (00:32):
Welcome to Lenny's Podcast. I'm Lenny. And my goal here is to help you get better at the craft of building and growing product. Today, my guest is Naomi Ionita. Naomi was one of the first early leaders in product life growth and monetization, having built early teams and infrastructure over a decade ago at Evernote. She was also an early contributor to Reforge when it was just getting started and helped create some of their early programs. She's also VP of growth at Invoice2go. And currently, she's a full-time VC at Menlo Ventures.

(00:59):
In her work as a full-time investor, she gets to see what works and doesn't work across many companies. And one area that she spends a lot of time on is monetization, when it's best to start charging for your product, how to decide what to charge, and how to evolve your pricing. And that's what we spend the bulk of our conversation around. We also touch on a really interesting framework Naomi has been developing that she calls the Modern Growth Stack, which is essentially all the areas that new starter products can help take the load off your plate and help your product grow. Naomi is awesome, and I'm excited to share this episode with you. With that, I bring you Naomi Ionita right after a word from our wonderful sponsors.

(01:36):
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(02:47):
This episode is brought to you by Notion. If you haven't heard of Notion, where have you been? I use Notion to coordinate this very podcast, including my content calendar, my sponsors, and prepping guests for launch of each episode. Notion is an all-in-one team collaboration tool that combines note-taking, document sharing, wikis, project management, and much more into one space that's simple, powerful, and beautifully designed. Not only does it allow you to be more efficient in your work life, but you can easily transition to using it in your personal life, which is another feature that truly sets Notion apart. The other day, I started a home project and immediately opened up Notion to help me organize it all. Learn more and get started for free at notion.com/lennyspod. Take the first step towards an organized, happy team today, again, at notion.com/lennyspod. Naomi, welcome to the podcast.

Naomi Ionita (03:45):
Thank you.

Lenny (03:46):
Did you know that you're one of the very few VCs that I've ever had on this podcast, and so you're basically representing VC kind here? How do you feel about that?

Naomi Ionita (03:54):
Wow. Well, thank you. I think early growth folks like us have a unique bond and a lens on startups and investing. So, my operating background is something I lean on every day and has actually informed a lot of the thesis areas where I spend time now as an investor. So, hopefully, we'll bring it all together in that capacity.

Lenny (04:15):
Awesome. That's exactly what I was just going to say, so I'm glad that you covered that. And so that's a good segue just to... Let's get into your background briefly. Can you talk about some of the wonderful things that you've done in your career both at Reforge, which you'll touch on, and growth stuff, and then your VC life now?

Naomi Ionita (04:29):
Perfect. So, I'm a partner at Menlo Ventures. I focus on early-stage SaaS from seed to series B. I started my career in engineering and consulting before getting into tech back in '06. Fell in love with product. Did some new product development at a big media company before business school. And while at business school, I spent time at the Design Institute at Stanford. So, this was an opportunity to kind of bridge my analytical background with this refreshing view on human-centered design and learning from the founder of IDEO.

(04:56):
So, brought that with me then to Evernote back in 2011, early days over there. I was there from about 10 to 100 million users. And over that arc, I shifted from more of a core product role to starting our growth product function. This was super organic. I started just collaborating with colleagues from across the business, come up with hypotheses, do user research, run experiments, drive metrics. This was a new way of building product back then. This was a decade ago, so the acronym PLG had not been coined yet. And I really just thought of myself as a user and data-driven product person.

(05:33):
After Evernote, I joined a bootstrapped mobile SMB company called Invoice2go. It was the top-grossing business app at the time. There, I built teams across product, data, growth engineering, design and research, and again, focused on product-led growth and monetization. Over those two jobs, I found myself doing a lot more advising and speaking on the side on these topics. And my board members used to farm me out to their companies to help their founders think through things around product growth and pricing and various topics like that. And Reforge came together at the same time, so I would come in and speak on topics through that community. So, that really accelerated my transition into venture. I realized how much I love having that portfolio view of the world and helping founders look around corners. So, I think it's an incredible privilege to get to do the work that I do.

Lenny (06:22):
One thing you mentioned is Evernote. I don't know how much you can talk about this, but they just got sold, right? Someone bought Evernote. And if I think back to Evernote, it feels like they could have been Notion, which is killing it right now. Any thoughts on what maybe they missed and didn't turn into Notion along the way?

Naomi Ionita (06:39):
Yeah. We're going to clear some cobwebs here. It's been a while. But one challenge that Evernote really struggled with was this evolution from single-player to multiplayer to team to enterprise. It's a chasm that a lot of bottom-up SaaS businesses struggle to cross. Evernote was philosophically antisocial. It was meant to be your second brain, kind of your personal tool. And I think that capped the company's growth potential. I always used to say you can't retrofit collaboration. You have to be collaboration-first. And a lot of companies now really take that for granted. But back in mid-2000s, this was kind of a new way of building product. And so we missed that bridge.

(07:20):
If companies do that well, it benefits every metric. That bridge from single-player to multiplayer. Acquisition goes up. You grow organically through referrals and shared workflows. Retention goes up because now you have these shared workflows that are incredibly sticky. Employees are accountable to each other to say, "This is how work gets done." Design in Figma, roadmap planning and ticketing in Jira are linear. It just becomes the default platform. And modernization goes up. Revenue scales with usage. And so the more people using it, the more they use it. You start tripping the wire on paying more and more over time. And so Evernote really struggled in crossing that chasm from the prosumer tool of choice that employees wall-to-wall were using, but never became this larger high-ACV contract from a sales perspective.

Lenny (08:06):
Yeah. It's always easy in hindsight to see what could have been better, what could have worked out, what didn't work out. So, what are you going to do? You mentioned monetization. And I know that you spent a lot of time with founders working on pricing, monetization, especially using monetization as a lever for growth. And so I want to spend some time there to pick your brain about what founders and growth teams can do and how they should think about monetization in terms of growth.

Naomi Ionita (08:06):
Perfect.

Lenny (08:31):
And then you also have this cool concept that you've been developing that you call the Modern Growth Stack, which is kind of this play on modern data stack. And so I want to spend some time there.

Naomi Ionita (08:40):
Perfect.

Lenny (08:40):
Cool. So, to dive into that first topic of monetization, if you think about when you're starting a company, what are some of the biggest challenges you face? Start building a product, especially a B2B product, I always think about pricing and trying to figure out how much to charge, how to charge, your pricing model, how to evolve your pricing, when to charge, all these things. And so I know that you work with founders helping them figure these sorts of things out. And so maybe a first question here is just what do you find startups most often miss or get wrong when they're starting to think about monetization?

Naomi Ionita (09:12):
There's a lot to cover here. I'll cover a few missteps that I think are most common. One is waiting too long to monetize. Another one is underpricing. And this isn't just setting the base price too low, but it's also leaving money on the table by not offering different plans to cater to different segments. And the third one is all too often with pricing, people set it and forget it. So, this idea that when your product development work is never done, neither is your pricing, and you need to combat that along the way. So, those are three areas I think we can cover here.

(09:47):
Maybe starting with one, I can jump right in, I think waiting too long to monetize. The beginning of a startup's journey is all about creating something of value. Right? That's the whole point. Hopefully, founders have some unique market insight or some authenticity around a pain point and some novel solution that's going to change the world. So, that business value is really critical. But the other side of the same coin is being properly compensated for that value as a business. I understand the vulnerability of being a new startup. You just want people to use your product. And I view that early free beta user feedback loop as an R&D cost to make sure you're building the best possible product and that they're driving a lot of value.

(10:28):
But I see companies way too long to make that shift from building a product to building a business. And I think that's the true signal of product-market fit, is ultimately having people open up their wallets and pay you, so looking for people to get to that end goal. And so again, these things aren't mutually exclusive. You're going to create business value, but you're going to be compensated for it and prioritize your roadmap over time so that you're building based on what people actually want and are willing to pay you for.

(10:55):
So, when you don't monetize, I think you're doing yourself a disservice. The things that I see as the pain of leaving money on the table, you're inadvertently cheapening your product. People attribute a lower dollar value or a $0 value to what you've built. You're missing out on critical feedback loops to understand what people are willing to pay. And you're shooting your future self in the foot because this is the other problem, is at some point you're going to start charging, and you're going to experience some backlash. So, it's nice to get ahead of that. A few things to think about, kind of food for thought around delaying and kicking the can down the road from a monetization-

Lenny (11:29):
So, just to reinforce that, your general piece of advice is if you're building a B2B product, start charging immediately. Don't give it away for free. At least have some... You could probably give it away for free but make it clear, "We're going to charge you this much soon." How do you think about that?

Naomi Ionita (11:45):
Yeah, I don't think those are mutually exclusive. So, this isn't to say that I don't like freemium models. Evernote was the darling of freemium over a decade ago. So, I'm still a big believer in that. It's more a question of where you put the paywall. How much do you give up for free? And then how do you price and package a paid version of your product? So, freemium is all about getting that top-of-funnel excitement, getting people to build habit formation. You're collapsing time to value. You're building habit formation. You're building all these champions to use your product. But the idea is to shepherd them along into a paid version of your product and to, again, not delay the idea of, "What should our premium features even be? What should that paid plan even look like?" Again, going back to the misstep at Evernote, I think there was always a premium plan, but it didn't really bridge into enterprise. So, we can talk more about that.

Lenny (12:35):
This is kind of a tangent, I know, because you have these two other pieces of underpricing and setting it and forgetting it. Been talked about, but do you have any advice for deciding what goes into freemium and what-

Naomi Ionita (12:44):
If it gets you to the aha moment, that path to habit formation, that has to be free. That's the core utility of your product. And so the idea is that in that first session or first day, someone's getting to see the delight and saying, "Oh, my God. I'm never going back to the old way. This is how X gets done." If you're looking for some virality or network effect, that's the other thing. Your free users, you might not be getting revenue from, but the idea is that they help you manage CAC. So, these are folks that are driving organic growth for you and helping reduce the incremental cost of your next set of users. So, that's another part of the math equation to think about in giving up revenue.

Lenny (13:23):
You also have this model that you didn't mention that you mentioned in a previous chat we were having offline of this idea of day one versus day 100, stuff people need on day one versus what they need down the road. Do you still believe in that? And what should people know about that?

Naomi Ionita (13:36):
I do believe in that. That was tied to... We had done this experiment at my last company, Invoice2go, where... Typically on the demand curve, the higher you raise the price, the average revenue per user or ARPU, the lower the conversion rate. So, these things are inversely correlated. And we were able to do this rebalancing of our pricing and packaging so that we actually doubled our upgrade rate from our starter plan to our pro plan.

Naomi Ionita (14:00):
... We doubled our upgrade rate from our starter plan to our pro plan while also increasing the price of the pro plan. So, to actually get twice as many people to upgrade while paying something like 30% more for that new plan is pretty rare to get the compounding benefits of that. And what we did was thought a lot about what is a day one premium feature? What is a premium feature that you can get value from the very first time you engage with the product? That's different than your day 100 features. Those are the ones that represent more advanced functionality. Maybe they're ones where the value is derived from having a certain scale of data in the platform.

(14:37):
And so, those you shouldn't waste cognitive load for your users to have to even understand or try to appreciate when they're first getting going. Push those into a more advanced pro version of your product, and monetize them down the road through an upsell. So, big believer in how do you really keep pricing simple? And we've all seen those SaaS pricing pages where there's a laundry list or just a gnarly matrix of features and functionality. So, do what you can to think about that journey for a user and how they're going to continue to increase value with your product over time, and how you can map your pricing and packaging against that journey.

Lenny (15:13):
I really like that framework, because it's so straightforward and simple. As you use it, you'll need more enterprise features innately, because you're sharing it more widely. Your head of security's going to be like, "What are you doing with this thing?" Your finance team's going to be like, "Oh, how do we pay for this thing?" And so, that's a really nice simple way of thinking about what to put in freemium in your free plan versus not. So, glad we touched on that. Okay, so we were going through the three things that companies and founders do wrong when they're starting to price. And so, the first you said was they go too late and I tangentized us, so I'll give it back to you to keep going through this.

Naomi Ionita (15:53):
[inaudible 00:15:53] This is by far the most common issue. And so, one framework I like to use here is matching price to value. When you do that, you create alignment with your user. So, this entails picking the right value metric. So, this is the unit of value that they derive from using your product, and it creates this natural escalator, because as people use it more, you get paid more over time. SaaS was historically built on a seat based model. That's been historical SaaS pricing. And now with the rise of PLG, we've seen more of these usage based approaches gaining speed, so that's pretty exciting to see. Whether it's number of API calls or messages sent or terabytes of storage used or words written, this usage-based approach really matches price to value over the lifetime of a customer. The other thing that happens when you match price to value is it helps you understand who you're building for, and it lets you target different customer segments.

(16:46):
In doing that, you're able to better serve each segment, but you're also able to maximize revenue for the business. Evernote always had a business model. From its beginning, it had $45 a year for an annual subscription. And this set the foundation for the company and tens of millions in revenue, early revenue growth, but the approach was suboptimal. So, as a growth team, we started doing surveys. I was really curious to understand why people converted from our free version to our premium subscription. And one of the most popular answers without fail was, "Well, I just feel guilty. I use it so much. I get so much value from it that I just feel obligated to pay." And take that in for a second, because if guilt is one of the main reasons why people are paying you, then your free version is too good, and you are leaving money on the table.

(17:36):
So, a single premium tier is often a mistake, and you're going to be leaving money on the table for specific segments, and it's important to drill down and understand who those are. Our additional research helped us understand that brand-new users with low perceived value of Evernote looked at it like their Apple Notepad app that was pre-installed on their device. And so, they couldn't understand the idea of paying $45 for Evernote. But then we talked to avid users, and these were people that were cross client using it on desktop and mobile, every device they had. They were using it for work and personal, they were leveraging OCR capabilities and the web clipper, and it was truly their second brain. They could not imagine life without it. And these people were floored that they were only paying $45 a year. They told us that they were getting hundreds of value from Evernote.

(18:28):
Here, the perceived value for avid users was far outpacing what we were asking from them. And this intuition and research really led to a bifurcated strategy of having different plans for different personas based on the value they got from the product and their willingness to pay.

Lenny (18:45):
That makes sense. When I heard you say that it costs $45 for a year, that sounds way too low. So I could see how that sets the pattern for Evernote just not making enough money over the long term. Cool. And then the third was that you don't evolve your pricing, right? That's like the third biggest mistake.

Naomi Ionita (19:03):
Yes. So, do not set it and forget it. I see companies do this where they labor over designs and features, and they build this perfect product that's delightful to use, and then pricing plucked out of thin air, and then they don't revisit it. This was Evernote. It was many, many years before we went back and overhauled the pricing. So, think about your pricing just like you do your roadmap. Every six to 12 months, there's probably something meaningful that you're launching for users. Treat that as an opportunity to revisit your monetization strategy and making sure you're compensated appropriately.

Lenny (19:33):
What advice do you have for founders around just how to decide in your initial price? Clearly Evernote didn't get that correct, and I'm sure you've learned a lot from that and then other companies you've worked with. How do you actually decide what to start charging?

Naomi Ionita (19:45):
Yeah, there's a full pricing process here, so I'm happy to walk through it. The idea here is understanding who your customers are, why they pay you, what is it that they want or value, and how much are they willing to pay you. I'd encourage you to put together a pricing committee. This is not a single-threaded exercise that lives in one department or another. This very much is a cross-functional exercise. If you are a PLG company like companies I worked at, this was the product growth org that I ran. So the combination of PMs and data scientists, folks like that to iterate on pricing. If you are an enterprise SaaS business, of course, sales and finance and rev ops play a role. Think about who that committee should be at your company, and commit to being that cross-functional team that really owns and iterates on pricing over time.

(20:31):
Then, they are responsible for talking to customers. This is by far and away the most basic thing you can do to just increase those feedback loops and understand how much you can push the envelope on pricing. You do that with surveys, with interviews, there's some questions that we like to use around understanding the relative prioritization of features. Going back to that laundry list of features and matrices on a pricing page, it's very rare that people convert equally across all of those features. There's typically one or two that are the main points for conversion. So it's good for you to understand the relative rank there and how to reconcile some of your pricing and packaging accordingly. So, we would make a list of our features that we had and maybe new things we wanted to build and have people rank them as a must-have, nice to have, or not necessary that help us understand the relative prioritization.

(21:23):
You can also get at it with a hundred point question where you give users a hundred points and say, "Spend them across these different features." And the more points you give a feature, the more value you're assigning to it. This is to get to the demand or the features and functionality that you've created. It's step one. It's understanding what people will actually want and making sure that they're not just saying everything but the kitchen sink, but they're actually getting a good sense for what's most important to them. And then the other side is understanding their willingness to pay. I'd say the easiest on-ramps here for companies to start digging into that is to use Van Westendorp's method here. I don't know if you're familiar with that. You're nodding a little bit.

Lenny (22:05):
Yeah. Yeah. Comes up a bunch on this podcast.

Naomi Ionita (22:08):
Oh, great. So I might be repeating myself here, but...

Lenny (22:10):
No, this is great. This is how we learn. We hear it again.

Naomi Ionita (22:13):
If you take the packages that users designated as nice to have and must have, you make that collection of features in the survey, then ask them, "What's such a cheap price that you start to question the quality of the product?" Ask them, "What's a good deal or sounds like the right price for this package?" Ask them, "What's expensive, but they would still pay?" So you're starting to get to that level of discomfort. And then ultimately, "What's prohibitively expensive? What would people just say, 'Okay, that's it.' You've crossed the line of how much I'm willing to pay here." And by plotting those four curves, you start to get a sense of how to inform your pricing. That's a great way to marry the questions around demand and then the questions around willingness to pay.

Lenny (22:52):
Awesome. I wish that survey name was simpler to say, because I can never remember exactly to pronounce it, but you got it. So Van Westendorp.

Naomi Ionita (22:52):
You got it.

Lenny (23:01):
So, say that you got a price, you launched with something. How do you think about and how do you suggest folks experiment with pricing changes? And then, what impact have you seen from making a pricing change, either in terms of revenue or growth? Because I know you work with a lot of startups on these sorts of things, so I'm curious. How big of an impact can you see from pricing changes?

Naomi Ionita (23:22):
Oh, it can be huge. Our friends at OpenView do a really good job of pumping out content and doing these great SaaS benchmarking surveys. They did something recently that showed that roughly half of companies that instituted a pricing change saw at least a 25% increase in ARR. So that's a pretty massive step function improvement in your revenue from something that doesn't require massive technological overhaul. I find that most companies regret not doing it sooner. ProfitWell is another group that I have friends at and have a lot of respect for them and the content that they've put out. They did a survey once on I think it was over 500 SaaS companies, and they looked at for a 1% improvement on acquisition, retention, and monetization, how did it impact a company's bottom line? And they found that the impact with an improvement on monetization was 4X that of acquisition.

(24:13):
So, this idea of how can you efficiently improve your business monetization is really underappreciated as a growth lever. Definitely something people should be thinking about. That's part of my goal of doing this podcast, is making sure founders are compensated in a way that they deserve. So, let's hope everyone makes a little more money after today. And I've seen a lift upwards of 10X on revenue, but it's sometimes hard to parsh just the pricing change, because usually it can be coupled with big product changes, a rebrand, a lot of PR, the launch of a new plan, like a team or an enterprise plan. So, it's hard to sometimes understand just the pricing change in isolation, but it really can be pivotal.

Lenny (24:54):
Cool. And when you think through the pricing changes that you've seen, is the impact often from raising the price just broadly? Is it segmenting more intelligently? Is it changing freemium versus paid? Is there a bucket you think of, like "Here's generally where the biggest impact ends up being?"

Naomi Ionita (25:13):
Yeah, it comes from doing it holistically. I think it's very rarely as impactful if you just pick a new price or just launch a new plan. I really think of it as rebalancing pricing and packaging overall. So it's doing this whole exercise of understanding what people actually want, what their willingness to pay is, and mapping it to that user journey like we talked about from single-player mode to multi-player, that first other person you connect with and have a workflow with, spreading it to your whole teams and ultimately spreading it wall to wall across an organization. So it's a longitudinal view of the user lifecycle and thinking about your whole business model holistically.

Lenny (25:53):
I don't know if you can talk about any of these, but is there a company or an example that comes to mind where you did a pricing change and just talking about what they changed just to make this even more concrete?

Naomi Ionita (26:02):
I have a specific story there with one of our companies, Envoy. This is a fun one. He was just getting started. This is Envoy, the visitor registration tool that I'm sure a lot of people have used, especially before COVID.

Lenny (26:16):
Probably mostly in SF, so I imagine folks in other countries don't know about it. Maybe describe it.

Naomi Ionita (26:20):
Yeah. So, if you visit an office instead of just signing in to that piece of paper in the lobby with your name and your email address and what time you checked in, it is a digital iPad based way of checking in and sharing information with the person you're visiting. And so, in talking to Larry and getting a feel for his evolution around pricing, he tells a story that I love. He was meeting with a big hospitality company, and the conversation was going really well. This prospect was really leaning in and excited about using Envoy, and the conversation shifted to pricing. So in that moment, because Larry was feeling some good vibes, he decided to 10X the price that he was typically charging people. So, just in the moment he decided to just go for it. Go out on a limb, and ask for 10X the typical price.

(27:13):
And in that moment, the exec said, "Okay, sure. Sounds good." Not a minute of hesitation, not a second of hesitation. And what he learned in that moment was that, one, he was wildly underpriced. It was very clear that he hadn't even thought about what the ceiling was. But the truth was he probably could have pushed it even further, considering there was no hesitation. So, what I encourage users to do, especially in these enterprise conversations, is to continue to ask for more, to understand where the upper bound might be, and to understand that it's okay sometimes to lose some deals due to price. Something on the order of 20 to 30% is reasonable so that you can get a sense for where the limit might be. The vast majority of companies are definitely undercharging like we discussed. So, go out on a limb like Larry at Envoy, and you can see that sometimes you can...

Naomi Ionita (28:00):
... like Larry at Envoy and you can see that sometimes you can 2X, 4X, even 10X your price.

Lenny (28:07):
That's an awesome story and it touches on exactly what you said where people often underprice. I imagine it's strategically smarter not to go straight to 10X and maybe go two or three X until people start pushing back because you lose a lot of data there. But that's one way to just zoom to an answer.

Naomi Ionita (28:22):
Yeah, they're all feedback loops, so I think there's some incrementality to it. But you got to understand who these different segments are, and if you don't have enough data points, it's hard to really understand how to continue to optimize.

Lenny (28:33):
Any other tips that you want to leave listeners with around pricing or monetization, or even testing pricing? Anything there before we shift to our second topic?

Naomi Ionita (28:43):
Yes. So we talked a bit about research methods and different surveys you can do to help inform your pricing. And with Enterprise, it's all about continuously asking for more. But if you're a PLG company and you have a public facing pricing page, I'd encourage you to experiment. This is something people shy away from, and frankly, there haven't historically been great tools for companies and infrastructure to be able to do this work.

(29:08):
So at Invoice2go, we invested very heavily in some internal pooling. We had a whole metering and human management and experimentation system in-house. It was a big growth engineering undertaking. And with that we tested different value metrics. We tested different quota limits, price points, promotions, you name it. We tracked the consumption of our pay as you go model and looped that back into the product so we can nudge users along the lifecycle to get them to convert, or upgrade or renew, once quota limits were reached.

(29:38):
So there's a lot there. I'm excited about this new wave of modern tools to actually help you do this and not sync a bunch of engineering time into building something in-house. So that's something we can talk about in a bit. But that investment was very worthwhile. We had huge revenue gains by being able to iterate in a way that was more streamlined.

(29:57):
There's some things to watch out for though. It's hard to test pricing. There's a lot of different variables to isolate. So you've got to make sure you're bringing a consistent test experience to the in product experience, your pricing page, maybe mobile app stores or lifecycle emails that you're sending.

(30:14):
One trick you can do is we would segment these tests by geo. So we would do some tests in Canada or Australia before rolling out in the US. That was a nice way to just put some constraints around our experimentation.

(30:28):
And the other thing you really have to think about is the long-term nature of pricing experimentation. So knowing if you succeeded and failed often requires understanding the implications on churn. Let's say part of your test is year one discount. You need to understand how users perform in year two and have a sense of the trade-offs around user growth, retention, ARPU. So all of these things are different levers that you want to optimize over time.

Lenny (30:56):
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(32:13):
There's a question I wanted to ask you, and maybe it's too big of a question to answer simply, but it's this question you just raised of trading off revenue versus growth. That's one of the most common trade-offs founders have to make. Do you have any just general thoughts, advice there? Is there one you should generally index on? What have you seen works best? Which kind of direction should you lean, growth or revenue, for your, let's say, B2B company? Like early stage?

Naomi Ionita (32:40):
Yeah, if you know that you have a bridge to move up market, then giving up the long tail of individual users can be very worthwhile.

(32:50):
So I think Figma is a great example of that. This was a company that took a while to monetize. And even having free usage at the individual level, that was the way to just drive insane community and love for this product. Designers around the world just fell for this product overnight. But this idea that once they were using it in a more corporate setting, once they were collaborating with more people across the business, they were tripping a wire to pay. And so what happened there was you had this massive top of funnel of individual users, but knowing that design is inherently collaborative, you're interfacing with engineers, you're interfacing with PMs, with marketers, with researchers, with execs, more than half of Figma users weren't even designers once it was embedded in the enterprise. And so this idea of these compounded growth loops that you got by interfacing with so many different parts of the company and making design truly collaborative and in the browser, they were able to just have this exponential curve on monetization once they shifted into more of a team or enterprise based package.

(33:54):
So that's a good example of saying, they were willing to trade off on monetizing the individual because they knew that it would be so sticky and would go so wall to wall within a company.

Lenny (34:05):
Got it. So your feeling is if it's a multiplayer PLG-ish product, you probably want to optimize for growth. Let it just take over and not go charge as much as you can immediately, versus say like a sales led B2B enterprise-y product, maybe they're focused on revenue immediately versus making it feel cheap. Is that right?

Naomi Ionita (34:27):
And I think if you do have a few free users, crafting it as more of a sweetheart discount, like more of a year one discount, but getting paid over time. I mean, again, I am a big believer in having some early users being your design partners and really giving you that tight feedback loop to make sure you're building the right product. So it's not that you should really optimize for revenue on day one. I mean, it is a journey, but I just oftentimes see companies just take too long. Or in Evernote's case, I mean the free version was just too good. So that's just something to consider, where to put the paywall and be really, really strategic about that.

Lenny (35:02):
Just don't optimize for guilt in your paid driver.

(35:07):
So you're talking about pricing testing and I was going to ask what tools you found that are useful for testing pricing. And that's probably a good segue to talking about the modern growth stack. Would that fit into this concept of modern growth stack, testing your pricing?

Naomi Ionita (35:21):
Yeah, let's do it.

Lenny (35:22):
Okay, let's do it. So just to set it up, there's this term modern data stack that I think it'd be useful for you to explain because not everyone is aware of that, and you've kind of been thinking more about this adjacent idea of a modern growth stack. So can you just talk about these two things, and then we'll lead to some questions there?

Naomi Ionita (35:37):
So the modern data stack is basically a collection of cloud native tools to more easily move and manage data. It consists of a fully managed ELT, data pipeline, a destination for that data. So a cloud-based data warehouse, like a Snowflake or Redshift, data transformation tool like DBT, and then finally a platform for visualization on top, so people can access the data. The play on modern data stack was very intentional. I think of the modern growth stack, or my core thesis area right now at Menlo, as the evolution of what you do with the data. So these are the workflows that the data enables to drive the business forward for product growth and revenue teams like I used to run. It's the modern replacement for infrastructure that teams like mine built or bought. When you're responsible for driving things like activation or monetization or retention, there tends to be a lot of these internal tools that are built because you're really powering cross-functional teams to do this work. It's not mapped easily into legacy departments.

Lenny (36:39):
Awesome. And the general idea here is, there's so many more tools now to help you grow with the data stack. There's just all these tools now that make it so much easier to collect data, use data, make decisions off data, and you're finding the same things happening with growth. What are some of the tools that you found to be super helpful? I know you're an investor in some, you're not a investor in others. It'd be good to just talk about, here's just like a bunch of cool tools and how do they fit together as much as possible to help you grow your startup.

Naomi Ionita (37:05):
And I want to reinforce some different themes before I get into some layers of the stack because I think it's important to frame the benefits of the modern growth stack. So one is data, two is workflow, and three is impact.

(37:18):
So starting with data, the modern growth stack companies really are powered by these smart integrations and the automation that you get as a result. So with this proliferation of SaaS, it's created this need for more data access and interoperability. We've all felt that pain of siloed data. Modern growth stack companies leverage reverse ETL companies, like Hightouch or Census, to break down these silos and help companies, or employees across the company, access data and be more productive. So that's a big data theme with modern growth stack companies.

(37:49):
The other theme that they unlock is around workflow. Here, it's really the enablement of people and process. So rather than employees sitting in their departmental silos, modern growth stack companies build bridges between them. So by unlocking data access, the business side can often self-serve and be more self-sufficient without relying on an engineer or a data scientist to run queries or stitch together data sets for them.

(38:16):
The other thing here is lots of growth work is inherently cross functional. So the efforts to drive growth requires new tools and collaborative workflows like we're discussing. Without purpose-built software, many teams like mine felt no choice but to build in-house. So we spent sacred hours building and maintaining tooling for experimentation, personalization, billing, monetization. These were resources that could have been reallocated to building proprietary features for the business had we been able to buy something purpose-built.

(38:50):
And finally, these products really drive impact. So the idea here is driving hard ROI in the form of cost reduction. So automation means time savings, and oftentimes, that can be mapped directly to cost reduction for a company. But they also help product and growth and go to market teams better engage and monetize customers. So they're driving hard ROI in the form of revenue impact too. I'm really compelled by companies that can drive hard ROI both across cost saving and revenue generation. And I think that ROI story is even more compelling now in a softer macroeconomic climate. You just have to be able to continue to retain sales and pricing power, and I think that's derived from a strong ROI story like I described.

(39:35):
So those are general themes and consistencies across the companies that I get particularly excited about. So happy to talk about a few layers in the stack, and I think you might be familiar with a few of these as well, especially based on your growth background at Airbnb and tools that you probably build yourself.

Lenny (39:54):
Yeah, exactly. That's what I was going to say, that so many of these things are just coming out of startups that have built these in-house. And then they're just like, "Hey, I could start a company doing this and provide it to all these other companies." And so I just love that there's all these tools coming out that just make it easier to build startups and grow startups, and do less work, and have less people. Just reminds me of the number one app in the App Store at this point. I don't know if it still is Gas, which is just like four people, and it's higher than TikTok and YouTube, and all the things, and Facebook, and it's four people. And so it just shows you the power of what tools can do for you to build new startups and disrupt people, and companies that have been around for a long time.

Naomi Ionita (40:33):
And you have to help companies do more with less now. There's a lot of frozen budgets and that's a good way to break through. So I love that these companies can do that for the buyer.

(40:44):
So one that's come up a bit and gotten a lot of airtime recently is product-led sales. This idea of companies that serve PLG businesses and harness the power of all that product usage data to inform the customer facing team around which accounts are most upgradable. It's really free money when you shine a light on an account that nobody was paying attention to and some inside sales team can drive a large account expansion. So I don't know what better ROI you should get than that.

(41:14):
And there's a bunch of companies that are doing this. Endgame happens to be one that I work with. They have customers like Figma, Loom, Calendly. There's other players too. I think Pocus has done a phenomenal job of building content and community to help inform the market around the power of product led sales. So there's just a lot of goodness about all the players in this space really waking everyone up to this opportunity of layering on sales to a product led motion and how to maximize revenue along the way.

Lenny (41:45):
I'm an investor in both of those actually, and I'm going to, just in the show notes, note the one I'm an investor in because I'm investor in a lot of these companies, it turns out. And we've invested in a few, so I'm just going to keep it simple and I'll write in the show notes. Here's ones I'm an investor, just to avoid.

Naomi Ionita (41:59):
I love that. Double- dipping means you're a believer in the category as well.

Lenny (42:03):
I am.

Naomi Ionita (42:00):
... tipping means you're a believer in the category as well.

Lenny (42:03):
I am. I love it. There's so much school stuff happening there and I'm really excited. Yeah.

Naomi Ionita (42:08):
Yep. Cool. I think another layer in the stack is experimentation. So this is really critical infrastructure, in my opinion, for these cross-functional product data growth teams to A/B test hypotheses and understand their impact on the business. How do you know if you make a change in the product or your pricing, whether you succeeded or failed without having infrastructure like this along the way? Category creators like Optimizely really paved the way. I was an early buyer of Optimizely and they targeted marketing personas, and it was just game changing to be able to start to A/B test things and bring hypotheses to life.

(42:44):
I'm also biased as an investor, but some of the modern tools here, like Eppo, which offers experimentation for the modern data stack. So unlike Optimizely, which focused on more kind of click through metrics, Eppo ties directly to the metrics in your data warehouse. So tying an experiment result to things like subscriptions or revenue or margins, really like board level metrics that you're trying to move. They make that full trip really convenient and understand the impact on those business KPIs directly. So it's a lot of automation around the experimentation, results. And analysis they used to live off to the side in Excel or Jupyter Notebooks now is automated away with Eppo. I think you're familiar with that one.

Lenny (43:29):
Yeah, we definitely didn't plan this, but Eppo's both a happy sponsor of this podcast. I'm also an investor in Eppo. Go Eppo, but this was not planned.

Naomi Ionita (43:38):
Well, this is Airbnb roots. [inaudible 00:43:41].

Lenny (43:40):
Love it. It is. Yeah. It's my colleague.

Naomi Ionita (43:42):
[inaudible 00:43:42] was an early data scientist at Airbnb.

Lenny (43:45):
Exactly, I worked with him at Airbnb and he was amazing and I had to invest in anything that he built. He built an awesome thing.

Naomi Ionita (43:49):
Yeah, but exactly like you describe, I love these founders that have steep authenticity around the problem because they built it internally and now they're commercializing it for the masses. And so the story of chain Eppo is a good one on that dimension. And there's other players too. I'm also a big fan of Amplitude and a buyer of that tool as well, and I love a lot of the team there. So if you do not have a data team or a data warehouse and you still want to leverage being able to do behavioral kind of ad hoc analysis or experimentation, that's a great tool for you as well. So a lot of different ways to solve this problem in the market.

Lenny (44:22):
Also, a happy sponsor, go Amplitude.

Naomi Ionita (44:25):
Cool.

Lenny (44:26):
I love it. This is great. Hitting on all my favorites. Okay, let's keep going. What else have we got?

Naomi Ionita (44:32):
Well, I talked a lot about billing and monetization, so I'd have to talk about that one. I think platforms for managing, billing and iterating on your pricing and packaging, this is just such a big need. I think these will transform business models. For SaaS in particular, most companies have been seat-based like we described, so the historical incumbents like a [inaudible 00:44:54] really serve that model. But in this shift to more usage based, there's new entrants that are servicing companies in that dimension. And there's also lots of sort of clunky workflows when you think of bridging from engineering to product and growth to finance or RevOps.

(45:11):
So there's a lot of just streamlined workflow that these new tools can offer. Some early breakout players in the world of usage-based billing are Metronome and Orb. There's also more room to handle the full monetization infra-layer. So for example, I like how Orb marries the billing component with the data infrastructure to actually inform what your pricing and packaging iteration should be and help you forecast and optimize revenue. So there's other players that are doing different components from this journey of the metering piece all the way through to the experimentation piece, and it's been really, really fun to get to know players in that space. And I wish I could have been a buyer of them many moons ago.

Lenny (45:57):
Not an investor in these yet. And so that's cool. Quick tangent, do you have a strong opinion on pricing models, usage based versus seed based versus something else? What's your guidance to founders? Is this the way to go, usually one of them, or is it super dependent? What do you recommend?

Naomi Ionita (46:12):
Yes, this is a similar answer I had before. I don't think that they're mutually exclusive. And so if you look at all the companies that in different pricing models in SaaS, a small sliver less than 10%, around roughly 5% have just pure natural escalator kind of usage-based model. The vast majority have a hybrid approach. And so what I mean by that is they're typically some good, better, best subscription model where there's some consumption component across each tier, like some quota limit for your given value metric. So in Slack there might have been number of messages sent or Dropbox number of terabytes of storage. Invoice2go might be number of invoices. There's some dimension that's been sort of packaged in with a given pricing plan, and once you reach that limit, it is a trigger to get you to upgrade to the next plan over, or sometimes there's overages that you can pay for.

(47:02):
So I don't believe that you should just be seat-based or just be usage-based. I think one challenge with purely usage-based models is that's not always how CFOs want to buy. I think buyers sometimes want predictability. They want to be able to budget for your tool, and I've lived that. I remember using tools like Mixpanel and Segment and even Jira to an extent where I was paying a cheap amount to get going, and all of a sudden I realized we had grown quickly and I looked at all of our SaaS spend and I was blown away by how much more we were paying. So it's the other side of this... I'm advocating for people getting paid and compensated for the value that they're delivering, but there can be a breaking point. And so how do you think about packaging a fixed and variable component so that people can more predictably buy your software?

Lenny (47:48):
Any other layers of the stack that you want to touch on slash which would you be most excited about in the future? Do you think people should be paying more attention to that maybe they're not paying attention to?

Naomi Ionita (47:57):
I mean, I wouldn't be doing my job as a VC if I didn't mention Generative AI right now. It's really having a moment. So there's a bunch of breakout applications there that sit within this theme of the modern growth stack. When you think of using AI to create images or text or code or audio or video, these capabilities change the way teams work. So writing a blog or writing copy for an ad, SDR is doing their work and can outbound sales efforts. There's just a lot of these touchpoints where it's humans kind of tinkering and iterating and laboring over every word. And if the machine, if AI can tell you what's going to be a more performant version of something, that's a very, very hard ROI exercise there. You save time and hopefully you've improved your performance across the various marketing or sales campaign.

Lenny (48:48):
Where do you think AI will be the most help on growth in terms of growth? Do you have an idea there?

Naomi Ionita (48:54):
I think what I described around marketing and sales, just because they really touch the dollars. It can be this ROI story around saving time, but also driving revenue. There'll be plenty of really effective examples within things like customer support. I mean the cost savings potential. There's going to be massive. We'll see what happens in engineering, which generating code. I think there's a lot of areas where it is going to touch the enterprise, but from a modern growth stack standpoint, I think something that's really revenue generating and can point to attributable ROI on that dimension is going to be pretty relevant to where I'm spending time right now.

Lenny (49:32):
I'm excited. Any last thoughts before we get to a very exciting lightning round?

Naomi Ionita (49:37):
I'm happy to hand it over to the lightning round here.

Lenny (49:40):
Well, we've reached the very exciting lightning round. I'm only going to have four questions for you. I'm going to ask them pretty quick. We'll go through them fast, whatever comes to mind. No pressure. Question one, what are a couple books that you've recommended most to other people?

Naomi Ionita (49:56):
My buddy Madhavan from Simon Kucher's wrote a book called Monetizing Innovation. This is a great read. He and others there have done pricing engagements with hundreds of tech companies, so there's a lot of stories and practical tips there. I often gift that one to founders, so I can't do this whole talk without giving a nod to my friend, Madhavan, and his bible.

Lenny (50:19):
Awesome. I just recorded an episode with Madhavan, and so that's a great pick. Question number two, favorite recent movie or TV show that you really enjoyed?

Naomi Ionita (50:28):
I have little kids, so I don't know if this is going to be as interesting for folks, but we like Story Bots on Netflix. They're these little cartoon characters that answer kids questions. So people sort of call in and ask questions and they do a whole episode on why is the sky blue? How do airplanes fly? How do I see? And I inevitably learned something from watching those. So those are very kind of playful and educational shows. I critically need a new-

Lenny (51:00):
No, those are... I don't know the answer to any of those questions. I need to watch this. Okay, so question three. I'm looking at my notes and I've never asked this question before, so I don't know where this came from, but I love it. Who's been the biggest inspiration to you in your life?

Naomi Ionita (51:14):
I mean, this one's pretty easy. For me, it's my parents. They're from South America originally and lived on three different continents before immigrating to the US for graduate school. It's a pretty cliché American dream, but they came here with nothing. Just this idea of building a family and taking advantage of the educational and professional opportunities in America. They progressed through school and building their career in three different languages with no financial support, no entrenched kind of resources or networks to lean on, and I just can't imagine doing that. Just the stress or cognitive load of kind of restarting your life in whole new geographies and cultures and languages and just betting on yourself and figuring it all out along the way. So my drive has always been rooted in their story and I'm forever indebted to them.

Lenny (52:03):
I need to ask this question more often. That was an amazing answer on the spot. Naomi, we have reached the end of our chat. Two final questions. Where can folks find you online if they want to learn more, maybe pitch you startup ideas, contact you if they want to ask you questions, and then finally, how can folks be useful to you?

Naomi Ionita (52:23):
I'm a partner at Menlo Ventures, so you can find more about me in the firm at menlovc.com or else on LinkedIn or Twitter. My DMs are open.

Lenny (52:33):
Amazing. Naomi, thank you so much for being here.

Naomi Ionita (52:35):
My pleasure. I look forward to talking to more folks who are building things across workflow automation, data AI, and the modern growth stack. So thank you. It's always a pleasure.

Lenny (52:48):
All right, DMs are coming in as we speak.

Naomi Ionita (52:50):
Thanks, Lenny.

Lenny (52:53):
Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving review as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at lennyspodcast.com. See you in the next episode.