LIVE Workshop Wednesday: Secrets to Sustainable Low CAC Growth after Series B and Beyond with Hyp…

not too long, write down and come up with the tough questions, the real questions. Challenge me. Let's make this useful. Okay, let's make this interactive. And then it's going to be super valuable for everyone. So this— with that said, let's, let's get started.

Yeah. Gee, I'm actually going to ask some questions for you first. Does that work?

Okay, go for it.

Okay, so how would you define what you do in your day-to-day role?

Yeah, so in the day-to-day, I'm these days an advisor, all right, which means I'm helping B2B startups, B2B SaaS startups grow faster. I am heavily involved with a company called Ramp in the fintech space, one of the best companies you know, in that space ever. And other than that, I'm a co-founder at Hypergrowth Partners, where we do advisory with companies from the Series A to the, you know, Series D and exits. There's like 20, 25 amazing VPs and CMOs who do advisory through Hypergrowth. So that's, that's what I do. And prior to that, I used to be a growth operator. I led growth at companies like Segment, Swift, uh, Gorgeous, um, and, and many more.

Great. Okay. Well then our second question, what projects are you working on today you're most excited about?

So today I'm, I'd say I'm trying to create a, um, a growth framework that, uh, applies to, uh, many companies at once instead of doing like, very pinpoint accuracy and customized growth frameworks. I'm trying to create something which I could deploy, not one-to-one, but like at multiple, many, many companies. Obviously, as you can imagine, that's linked to the work I'm doing in advisory so we can scale. All right. But that's, that's really what I'm working on. I have a lot of unique wins at unique companies. How do you replicate those wins reliably is the question. If you can do that, then you unlock incredible value.

Awesome. Okay, well, hopefully we'll hear about that today. And then in the last 12 months, what's been the hardest thing you've worked on?

I think as, as everyone here, probably macro, the macroeconomic. I mean, I'm, I'm not a magician here. Like, I live in the same planet, same planet, same world as everyone here. And it's been tough. And I think we need to recognize that we've— I've had less budget than before, less headcount. And so I've had to be even more creative. That's, that's the challenge that I face, that everyone faces. The entire macro is challenging, and still we need to create growth and we need to find those pockets of opportunities and help our companies win. That is my challenge. I think that is everyone's challenge.

Yeah, I think there will be a ton of questions on that today. Well, with that, I will hand it over to your slides to get things rolling.

Okay, let's get to one. So today I want to talk about kind of exactly that, so the low-CAC scalable tactics, um, but more the earlier, earlier to growth stage. We'll cover a bit of both. All right. So very quickly, as a self-intro, so please feel free to call me G. Obviously, the French name is a bit longer and not super important. But I've worked at a bunch of great companies over the past 20 years. Some names you'll recognize here on the left-hand side. And more importantly, I've been repeatedly at stages of high growth from 50 to 300 employees in like, you know, 12 to 18 months. There's some years where We grew the ARR more than 5x year over year. And obviously I'm also an investor in many, many companies. Generally though, what I like to say is if you are in marketing, if you are in growth, I guarantee that you're using at least one, if not multiple tools where I'm involved either as investor or an advisor. So as I said, in London, if you ask, if you think, if you ask, does G have a bias? Like, absolutely. Like everywhere there's a bias, I can just say I am the bias, right? I cannot remove myself from the bias because I'm just involved everywhere. But with that said, at Hypergrowth, we are collective of advisors, VPs, CMOs. We work on equity basis, common stock. We're very aligned with the founders. We work for companies like I talked about Ramp. There's also Vercel and Maze and Honeycomb, amazing companies. And we think of ourselves like investors, but we invest our time. We're sweat equity investors. So when you think about hypergrowth and reaching hypergrowth, what does it look like is a question I often get. Obviously, if you think of the obvious examples, the Shopify, the Twilio, the Slack, I just wanna share a bit like where I've been involved so I can probably put my experience, my expertise in context. You can see here Gorgeous, Drift, and Ramp in context of the best SaaS companies that went public. And you can see here that obviously Ramp is the outlier that went from like 10 to 100. In one year and to win a couple of bits. So like, how is that even possible? But all of these companies have one thing in common, and that is not me. That's not what I'm going to point to. They have in common a growth team. They have in common a growth team that takes risks and is looking for outlier effects. That is very important. Please put a Post-it there. And what— we'll come back to it. So obviously when you see that, you're like, how can I grow as fast as Ramp? Right. And so there's those 4, let's say, components which I would summarize it to. So yeah, low CAC, scalable strategies, a growth team with engineers, super duper important. All right. If you do not have engineers, I would question whether you're a growth team. You're probably a demand gen team, right? And if you have questions, let's cover that. All right. Aggressive marketing stack. If you're not looking for the new and upcoming tools, the cutting-edge platforms— to put it another way, if you're using Marketo as your core platform and your only platform, how are you going to differentiate from all your competitors? How are you gonna do things differently if that's, if you're using the same tool and the same org chart, same resources, right? I don't think there is a 10x marketer, you know, in most companies. That's not a thing, right? So you need to have a different mindset. This is the fourth point. That is using different resources and different tools. That is how you create that competitive mode. And it's a very, I'm very intentional on, on the ladder, on the point 2, 3, and 4. So let's go through like the first one, the scalable low cash strategies. Let's look at a couple of examples. Generally, I'm going to pull out one of the examples which works really well for like sales-led SaaS businesses, and that's outbound. It's not like your I think in the US, you would say it's not your mother's outbound, is what you would say. It's high-scale modern outbound, has extremely good tech and extremely good scale. So the way you're gonna do that is you're gonna build an understanding of your entire target market, what we call the TAM, target accessible market. The total addressable market. So your total addressable market, um, and you're gonna map all the companies. You buy that data of all the companies in the market, and then you buy all the contact data. You score them, inject that, uh, into a database, uh, of yours. You run some personalized copy and you add it to a motion. Now that feels fairly similar to what you could have done in the past. But let me show you what the outcome can look like. This is the MarTech stack that we're talking about here. The MarTech stack, and that is like a couple of years old, but still very relevant. In this case, this is entirely for outbound. You see all of the intent capture. So the third-party intent, the G2 Crowd, which is now commonplace, but also the Hiring data from PredictLeads, the technographics data, the website visit data. These days you have Sixth Sense, you have a— it does that, right? All that tells you which companies within your TAM on your database are expressing buying intent, are likely to respond positively, to convert. Those are the ones, that's a sub-segment you want to email. And all of that then gets scored in the middle here. Enriched and then outputs automatically to obviously emails, outbound email, that's the point, but also to advertising audiences, to gifts, to power dynamic live chats, to change the website. There is, as of today, this slide here is old. This is like when I was at Segment. This is an old slide. It's like 2018, 2019 maybe. 5 years old, 6 years old. There is still, as of today, no tool, no platform that enables you to do this off the shelf. And that is why this is still a moat. If you're capable, as of today, of having an anonymous visitor come on your website, you detect through the IP, the domain, the company, you score it, you know it's a high-fit company, you're in your mid— your perfect ICP, right? And you power chats dynamically, you put, you pull an AE into that chat and you send an email to that, to the right buyers at that company. That today still does not exist in a single platform. That is a competitive mode. A good example of like using technology to solve, to create competitive modes. Good example of using engineers, ops engineers to build that. How do you build the TAM? I'm going to pull an example from the Ramp playbook. They used to have multiple vendors. They had like 5 or 6 different vendors. They had like the ZoomInfo, the Clearbit, and all of that, right? A lot of the vendors in order to get the company data, but more importantly, the contact data, the best coverage of contact data, not 40%, not 50%, When you have the good email outbound campaign, good performance, you want 80, 90%. And that is an example of going back to what I was saying earlier of the cutting-edge platforms. They found these guys, Waterfall, a European company that aggregates all the vendors into one API, into one platform, one cost. And so rather than having to like buy the You know, the, the credits, sign the contracts, go through legal with all of the different vendors. They pay one team and that team disseminates the data requests to all the vendors, buys in bulk, has great prices, brings back, responds with the best contract at the best price. So basically they're just, that's what they do, right? It's unknown for now. I'm giving you this tip. It's unknown. It is cutting edge. And for now, it is giving you a competitive advantage. It's not gonna last. The point of like technology advantages is that they never last 5 years, right? But they could last 12 months. And if you don't have that, you should get, and you're doing outbound, you should get onto it or something similar. But you should always be on the lookout for things like this. Personally, I'm on the lookout for the next thing. Like, I'm both an investor, but I've tried using things like Cavous, which does deepfakes for SDR videos. Right. And so instead of like having the SDR, this is like, you know, hey, Caitlin, I'm G from Hypergrowth, and I'd love to talk to you, which works, right? But it's expensive to have those videos at scale. They build a deepfake of my face and they reproduce the video at scale. Does it work perfectly? No, it doesn't. I'll be honest, it doesn't yet. But the day it does, am I going to use it? Absolutely. Absolutely. And then eventually the market will get used to it. And so the conversions would drop. All right. So there's a reversion to normal. The point is, try this, try the next new thing, be on the lookout, aggressively look for new technologies. If, for example, like I've been doing marketing growth for a while. But when I go at SaaStr in September, NSF, right, actually in the Bay Area, you'll see me roaming the booths and talking to the small new vendors. And many CMOs don't do that. I go talk to the teams of like either the small booths or small vendors, the young teams, and I'll just like have like a coffee with them to understand. And most are not a fit for me, but I'll always find a few gems in there. So, okay. In terms of like email playbooks, this is what I used to do in the past decade, 2010 to 2020. We would buy the data from Clearbit, inject a couple of like personalized tags. I'm sure you've all done that, right? There's some unique things you might see here. You can see there's like persona-specific outcome as the, you know, in the middle here. and there was like the personal specific play. Those were very simple, uh, lists of, um, let's say merge tags that we would compute based on an ICP and industry. And we would have like a spreadsheet of sorts and would automatically merge the right, uh, forecasted predicted outcome. And that worked fairly well. This is, this is not 2010 anymore, my friends. We've moved on from this. We're now in a world of AI. All of this is now much better done with AI platforms. So let me show you where we are. And I have the pleasure— I'll skip through this and I'll go to— there you go, to this. Excuse me. I have the pleasure of showing you two examples from Graham. Actual examples. I am sharing them because people who have received them have shared them on LinkedIn. So obviously it's already public. What you can see here, and I'll annotate here for a second, in this first email, this is, this is very American. This is somebody using their origins as a way to reach out to a prospect with the same origins. In this case, it is Persian to Persian, and you can see they're injecting the information about Persian dishes. And so it's, it's very personalized. Okay. And you can see what the person has posted on their own on LinkedIn. Right? They loved it. Why does this work? Because it feels personal. Because it feels like somebody has looked at you, has immediately identified that you're part of a small demographic, and you have something in common. So there's kind of a relationship. There's, you know, there's, there's something there. And you've taken care of writing something custom. You've gone through efforts. And that elicits reciprocity. That one works great. On the side here, let me clean that up actually. And let me go to the side here. This here is another email, completely different. In this case, no background to create reciprocity. In this case, the automation, because all of this is automated, has sent an email to this guy called Mark. About his college sports team. Again, very American. Most CFOs— the target demographic is CFOs. Almost all CFOs in the US have gone to college, probably all like 99.9%, whatever, right? And all colleges in the US, most have a 1 or 2 sports team. And people love their sports team, their college sports team, and they follow them. We use that, use that, and we give them an opportunity to bid, bet, I would say, on the outcome of the upcoming college sports game for free. They're betting for free, right? It's like, we've tried different versions of that, free lunch, a gift card. Now, this has a response rate of above 10%. What's interesting is that just sending the email, "Well, take a demo with me and I'll give you a $50 gift card, $100 gift card," has a much lower response rate. Though the actual take rate is higher, because in this case, your team could lose. But this is personalized. In the background here, what's happening, which you might not realize, is that there is a team of engineers The last night that has built a database of all upcoming college games and competing teams, the likelihood of outcome. So you can pick the right, the right bets, right? So this is a sports betting algorithm happening there. It's a little pet project from somebody over the weekend, right? And the entire automation. Okay. It is small volume. But it works great. It works great. Why do we do those things? Because in this program here for this demographic, we rarely have intent signals from companies about, you know, changing their credit cards. So if we can't read intent signals, we're going for the best excuses, personalized excuses, very, very relevant. All this is powered by GPT. This is the modern approach. Sorry. So that is, I'd say, what you should all be focusing on if you want to build the modern approach. And let me go back here. Cool. Okay. So with that said, I want to share another example of a—

Gee, I think right now I'm only seeing like the—

Sorry.

No problem.

Stop this a second. I have Chrome going crazy and I'll just relaunch the slideshow.

No, not a problem at all. We do have some questions in the chat we can go over while you're putting your slides up. There are some questions about What the company name is for that deepfake video?

Ah, yes. I'll write it down in the chat. It is called Tavus. T-A-V-U-S.

Perfect. And then questions about that email you were showing when it came to the personalization of Syracuse and Persian and those types of things. At what scale can that be replicated? Does it have to be one-on-one? Like 1v1? What is the background to that?

Yeah, I would recommend doing things manually at first, trying it out to see if the audience reacts well. This could be a dumpster fire. I mean, would I have tried the, uh, uh, let's say personal origins in an email? Absolutely not. Just for context, do not do that in Europe. You will get sued through your eyeballs if you do that. It's a very, very bad idea. Okay. But the team in the US told me that is, this is absolutely correct. This is great. It's gonna work. Let's try it. I'm always for trying new things and see if it works and creates the right, I'd say the right connection.

Great. Okay. Thank you for that insight.

Sure.

Cool.

Awesome. Actually, let me skip to two things. One, which is what's the team what the team looks like to build those kind of experiments. And this is the org chart I recommend. You have a VP of Growth, head of VP, doesn't matter. And then there is per channel, a, the equivalent of somebody who is a channel specialist, in this case, an outbound specialist. In the middle, you're going to have the growth PM, who is, I'd say, prioritizing the work of all growth teams, right? And then you have this outbound pod just here, which has, let's say, a growth marketer, a growth analyst, and the access to engineers. Okay. The overall growth PM manages all the resources allocation. And focuses the engineers to work either on an outbound project, a paid project, SEO project, right? That is the structure that I recommend that enables you to create those kinds of, say, aggressive experiments. So just to close, so we can move into the Q&A, the mindset I'd recommend having is that of the angel investor, the early-stage investor. Okay, it's you need to ship a lot of small experiments in order to have a few outliers. I don't think that you're gonna come up with like, uh, the one experiment out of one that's gonna work great. I, I don't do that. I can't do that. I've been doing that for a while. But if I try 20 things, I'm very likely to have 1 or 2 that are strong outliers, as the examples that I shared just before show. Okay, so you need to have multiple, multiple bets. Okay. The way to think about that is to separate the growth marketing team from the core product and core marketing. You're not better than those teams if you do growth. All right. You're just operating differently. You are the early stage investor. You have a lot of things cooking at the same time. You do not have a lot of information. You have hypothesis and you measure solidly, whereas marketing cannot afford to fail. Marketing needs to succeed almost every time. Growth's job is to fail. That's the job— fail 70% of the time to find those outliers. I hope it's— and the same thing is true for like the split with core products. So just to summarize the takeaways here. The right technology stack. Okay. Scale, always scale will bring you the low cap. Okay. Your growth team, you should have a growth team. It should be, you should ship like a product team, work like engineers with the engineering mindset on a marketing surface area with dollars as the KPI, North Star, right? And if you are Beyond the Series B, which is where I tend to focus these days, success comes from continuing to take those risks. Most companies who slow down for the Series B is because they revert to the traditional approaches. They become safe. You're safe, you're dead. You need to take the risks. So with that, um, I think we're about halftime. That's great. Um, let's move into the Q&A and have a couple of more appendix slides. Um, If there's questions, I can just pull them out.

Perfect. Okay, you can— oh, if you want to keep those up just in case we need to pull them back up, that's fine then.

I can just go here so we can see each other. Yeah, everybody. Yeah.

Okay. Yeah, we're all friends here. Let's see some people's faces. Our first question has to do with your first key takeaway. So, Jane, if you want to unmute yourself and ask.

Sure. Hi, everybody. Thank you for the preso. I'm curious, you mentioned a bunch of tools, so I would love to just pick your brain more on what tools are top of mind for you right now and what you think is an ideal martech stack to be leveraging. I'm sure it depends, but you probably have a core stack that you would recommend.

Yeah, absolutely. And thanks for the question. Obviously, it does depend. I do recommend these days having, in the context of a B2B SaaS startup, obviously, having one good way to capture user activity. Obviously, I was at Segment. I love Segment. Your mileage may vary. One good way to enrich your users with additional data. I love Clearbits. I've mentioned a couple of others there. One good way to build a prospect, and I think of the tap, right, of the entire, of the total addressable market, a couple of folks there, let's say on the company data, you might want to go check out, you know, the usual suspects of like the ZoomInfo and others, they tend to be expensive. You want to go for cheaper, it's possible to go to people in the labs, exact buyer contact data. Obviously, I mentioned a waterfall. And so all that is like building databases, understanding. And then you want to have an action suite. All right. So like once you know who's who and, and what they're doing, how do you act on it? All right. And then we're going to cover all the channels. I tend to have a view that I pick the best in the breed for each channel. I'm not a big fan of like large suites because I don't think that gives you this competitive edge. So, you know, you want to go for like outbound. I love AmpleMarket. You want to do some— so there's tools for every, let's say, sub-channel. There. So I think that, that, that's a good core. There's one thing which you need to do here is the orchestration. So how do you orchestrate all of that? And that, that feels massive. I just named like, I don't know, 10 tools, right? You need something like a CDP to orchestrate all those tools together. It can be your own, it's fine. It can be something like a, a, a Census or a Hightouch on top of your warehouse. I recommend that. If you want something a bit more low touch, you can go check out the guys at getcargo.io. They are in YC right now and they're building something that is very future, I'd say, looking. That's great. But the orchestration is where you create the value as a marketing team, right? Because you, you won't have something modular when you replace the components. That is, I think what's most important.

Well, thank you. Super helpful.

Of course.

Okay. Our next question comes from Ernesto, if you would like to unmute yourself.

Yes. Hi. Thank you so much for this. Specifically around that org chart that you presented, you know, what stage of company is that really aimed for, both in terms of like, I guess, funding stage as well as like overall team size?

Yeah. So if you think of growth teams versus stages, I recommend not having one before you have product-market fit. Your definition may vary. I can see Jason here, he has a couple of great tweets on product-market fit. But if you don't have product-market fit, you don't need a growth team. You need to build product, you need to do the basics to penetrate your early adopters. I have a personal view, that every market, almost every market, has a small percentage of early adopters, people like me who are just excited to buy any new technology. Can be 5%, can be 10%. If you can't break into those people who are ready to put the credit card down just to try the next thing, you don't have— you don't need a growth team. You don't need to scale. You need to be able to get the right message to get those people to buy. Growth useful beyond that to be able to reach your entire market at a low CAC and a high scale. So initially you're gonna have something like a 3-person team. I would recommend somebody who's like a growth PM/analyst, generally with like a banking background or a consultancy background. It's really metrics-driven. An engineer, front-end engineer generally, and a marketer to do all the copywriting and maybe work with a couple of freelancers on like the, um, on the design, whatnot. That is sufficient. Those 3 people is sufficient for you to start doing some experiments, build some PLG products, do some changes to the, uh, to the front of the signup, to the onboarding, to the nurturing. That is, that is sufficient. Do not skip the engineer, please.

We have a follow-up question in the chat. Um, could the growth team report to the VP of marketing? At a smaller startup.

Yeah, and that makes sense. I think that makes sense. It's very, it's dependent on the VP of marketing and is difficult to maintain. I'll explain why. As I said, the marketing team is focused on shipping new products and campaigns at a high success rate, almost 100%. If a VP marketing or marketing leader fails, botches 2 or 3 major launches in a row, that person's out. Let's be honest here, that person is out, right? And you're going to tell me that within that person's team, this can be a sub team whose job it is to fail 7 out of 10 times, and that's going to be okay? That is tough. So that requires a really good, I'd say, agreement, alignment around the company that there is a small team that's going to like fail a lot in order to find possible outliers, and everybody's going to celebrate that, but he's going to have expectations for the other teams. I'm just thinking over time that creates friction. So it's possible, but it's challenging, creates friction. Eventually you probably want to split it out.

Yeah, definitely an awkward team happy hour, it sounds like. Ernesto, did you have an additional follow-up question there? Sorry, I think I may have cut you off.

No, no, that, that was really it. Thank you. And I was really trying to understand what that growth engineer was, but it sounds like it's that front-end engineer that you're talking about to be able to kind of help run those experiments.

So I think it's case dependent. If you're in the PLG business, then you probably want like a front-end engineer to build, let's say, to bring to the masses the product. If you think of PLG, there's something which we didn't discuss. PLG and sales-led are looking to build the same end goal. It is lowering the CAC. They're just two different strategies to get low CAC acquisition. PLG, you're just having like a super wide funnel where the audience users self-select and say, yes, this is the right product for me. And so PLG means you have like almost $0 CAC. Right? And the product is almost free to serve. In the case of like sales-led, like you're just looking for low-CAC strategies, but you have a sales team. And in fact, like it's not that different. Like the channels and strategies are very different, but the marketing strategies are very similar. Okay. And so if you have PLG, you probably want to go for a frontend engineer. If you have a sales-led, then you're a lot more in ops, in, in, you know, data ops and you probably want an ops engineer or a backend engineer to build this whole like TAM outbound automation and all of that. Great.

Thank you.

Great. Okay. Our next question. What percent of prospects do you model as being in market at any given time? How do you adjust the playbook to make sure you get them later if they aren't in market today? but are later?

Yeah, that's, I mean, that is very market dependent. I've used a lot of intent signals. So for example, I'm good friends with the folks over at G2. G2 is a great data source. They're a great team and they sell the data on which companies are looking at your competitors and are looking at your category. Right. That's a very good first approach that tells you, you know, immediately, because you're not going on G2 because like you have like, you know, you're in the train and you're just looking at Facebook and say, oh no, let's look at G2 right now. That is not what's going on. Right. You're looking at G2 because you're in a buying process, because you're doing an RFP or something similar. And if you see a company checking 2 or 3 of your competitors, it's very obvious your sales team should get on the call. Okay, you look back 6 months because they sell historical data that tells you the number of companies, and you can thus calculate the percentage of your market that is looking at competitors. Okay, there are other vendors like G2 that tell you similar information. You can look at hiring signals, all right, um, through LinkedIn or other places. You can look at technographic signals, um, So for example, I'll give you an example. Like when I used to work at Gorgeous, we would look at which technologies are often associated to migration opportunities. And so in the case of Gorgeous, in, you know, in the e-commerce stack, there's a couple of other players like Klaviyo, for example, where if there's a company that's on the buying spree and they're just re— they're reworking the entire stack, the MarTech stack, and they see that buying Klaviyo, like, we know there's a really good chance they're open to conversation about changing their help desk. All right. And so that gives us that information. So we can start stacking all those signals up. And that gives us a pretty good perception. It's harder in finance, for example, where people don't openly go on Twitter to, you know, talk about their finance software and finance problems. But eventually you do find ways.

All right, thank you for that answer, um, and all the examples as well. Our next question will come from Matt, if you want to unmute yourself.

Hey, um, this talk has been great so far. One thing I'm really curious to hear about is what you see the role of the SDR team as for B2B enterprise companies that, that have fully implemented a growth team. Like, what would you send there? What wouldn't you send there? Get rid of it entirely? What do you think? Where does it Yeah, that's a great question.

I, I don't think the SDR team, as we know it right now, will look anything like it is in the future, in the next 2 years, to be honest. There's the obvious advent of all the AI platforms to create, you know, content and email, some of the stuff that I shared. But there's a but here. All what I shared only works up to a specific size, like mid-market. Beyond that, for now, everything breaks. There's no data platform for, let's say, large enterprise org charts that enables you to know who's the champion, who's the buyer, who's the decision maker reliably. The end is too small anyways. You don't want to take the risk. This is very deep. It's deeply personal. You gotta create the, the pathways, the connections, the, um, that for now is not automated and I don't see anyone working on it. So I think the SDR will reduce, SDR team will reduce in size. There will be two key functions. One is, um, unique copywriting, the stuff that you saw earlier in the ramp examples. Uh, they do come from humans that wrote a manual version and saw huge lift. Then the growth team automated that, and that's fine. That's fantastic. Second function, enterprise sales, enterprise penetrating enterprise accounts. There's no point in trying to automate that, and it's too small. The risk is too high, too much data. So still for now and for the foreseeable future, very human.

Speaking of that personalization level, How do you ensure that you're not intruding on personal space or it's not offensive? You mentioned something working in the US that would not work in Europe. What type of testing do you do with that, etc.?

So it evolves over time. There's one thing I like to bring back, which is, so I've been around for a while. For better or worse. And I remember a time when personalized ads were perceived as creepy. I know people saying, oh, like, I went to like this e-commerce website. And then I went to the New York Times. And the products I did not buy were there in the ad. That's creepy. They're following me on the internet. Right? That's like 2012, 2013. Right? People were freaked out about it. These days, don't care. It's commonplace. Like, that's, that's just the way things are. So things change over time. So what is creepy, you know, 5 years ago might not be creepy anymore. The boundaries evolve and in both directions, I might say. So you gotta like, you gotta try. I tend to again, do things at a fairly small scale. I'll give you an example. We recently did iMessage automation. Okay, so it's not just text, it's actually the blue bubbles, like iMessage automation at a high scale to see, is that a good channel? It is more disruptive, it is low cost, less text, but why not send a couple thousand? The answer is much higher response rate and obviously much higher complaint rate, right? But does that mean that we should not do it? We found a way to use that channel in a way that is efficient. We used it for the people who respond to email in a positive or neutral way saying, "Oh sure, I could meet in the future," and then ghost us. When we have that, we have the implicit agreement that if they don't at some point say no, we should follow-up and a human person would do that. A human SDR would chase them on, you know, LinkedIn and whatnot. And there we have extremely low complaint rates. So my rule of thumb is, if your positive and neutral response rate is higher than your spam and unsubscribe rate, you're creating more value than you're destroying value in the market. You're doing a good job. Right? It's an— I'm not saying it's perfect. It's an easy rule of thumb. That's mine, pick your own. But mine is you create more value, make more people interested, then you make people annoyed, that's okay.

Yeah, I think that's a theme of life too. All right, our next question. How do you advise CEOs on how much to allocate to marketing budget overall, especially with tighter budgets today? What framework do you see in 2023?

I, I, yeah, okay. I don't know that I'm the one who's speaking here. Most of the times that comes from the board, from the investors who are giving, I mean, most of the people here I assume are working in companies which are VC funded and if not VC funded, they're looking at VC benchmarks. So it's kind of the same. And in that case, like you're looking for some efficiency metrics. in the acquisition. It's very simple. Like, you look at payback times, at CAC to LTV, like there's a lot of benchmarks available out there. I would say generally, the benchmark I tend to follow for companies above a million in revenue— gets weird below that, but above a million in revenue, like 1 to 10, it's a dollar of ARR for a dollar of spend fully loaded. Within that, fully loaded means with headcount cost. Within that, so sales and marketing and all the, all what is required to like serve the customer without building the product, that's excluded. And so within that, within that dollar, there's about, let's say, a third that goes to marketing and a third that goes to sales and a third that goes like to the rest, right, to admin and whatnot. So you get about $0.30 on the dollar is what I would recommend. And that is like top, top quality. Yeah. So, you know, if you can— but yeah, that's what I recommend. Yeah, that's it.

Thank you for the response and tying it to numbers so clearly as well. Our next question comes from Manik. Let me know if I said your name wrong. Sorry.

No, this is great. Thank you for all the information. Geez, very insightful. I'm curious, sort of, is there a distinction in your mind between products that have a bottoms-up sales motion versus a tops-down sales motion? For example, in developer tooling, particularly in the cloud space, everything has sort of transitioned from like a VP of IT to actually engineering team deciding what they wanted to use. And also, I noticed that, you know, um, one of your, uh, in your introduction, in your bio, you mentioned honeycomb.io, which would be actually a perfect example of this kind of reverse motion where you're not reaching out to the VP of IT. Um, and yes, how would you think about that versus, um, yeah, so Yeah, I mean, that is a challenging motion.

I think that there's two separate things there. One is the PLG aspect, which means that you are building products where the cost of serving the customer is extremely low. You can afford to like serve a very high number of people who are not paying in order for them to gain conviction, buy a, you know, paid version of the product and/or invite other people that creates some like viral loops, higher K-factor, and that offsets the cost of serving the product. You're not paying for the acquisition, you're paying for serving the product. As I said, it's very similar. Now when it comes to engineering, I'd say my personal examples are in Segment, which is also very similar. We have like this momentum of like what we call the single-player mode. Can you make a single user— can you create value and make a single user like happy about the product without having to go through all of like legal and security and whatnot? That is the challenge. Okay. Because if you can't and you don't have a PLG product, because then you get to get your entire like sales motion in play in order to like deliver value. And you have this like often like this, this blank page problem. Which is very real, which is like engineers sign up, there's nothing they can do because they need to connect a warehouse and not going to connect a warehouse without going through legal security. Right. So that is the core challenge is proving value at— for a single user. And often that comes by stripping part of your product into singular components which can be valuable for that specific user and say, well, I love this thing. I want more of the same, more of the team that does the same. Right. So that's, that's a question because can you do that or can they come with like the data and access that they have? Okay. So PLG for engineering products means making a single user happy, avoiding the blank page problem. And similarly, it also often is a problem of open source to cloud. It's a huge problem that we're facing in many companies who are building very strong open source products, huge adoption, but then are having a lot of trouble going from open source to paid cloud services. Yeah.

All right.

Thank you.

Great. Okay. Do we have any more last minute questions?

Can I ask mine?

Of course.

Caitlin. Hey, Gia, curious how you think— I put a question, but there are a lot of it. A lot of the growth playbook and the outbound playbook, all these pieces assume, almost assume all customers are in market, right? But traditionally, I think in marketing, we hope that 10% of customers are in market, right? Either in market or close. Or switchable, right? Or switchable like we're just— how do you think about that in general? And then two, so how do you think about the playbook longitudinally? Because you talked, for example, about, hey, if I get one more sub than I lose, it's worth it. But what if you break that relationship that in 6 months they're willing to buy Ramp or 9 months they'll switch from Zendesk to Gorgeous? A lot of the growth in outbound doesn't seem to think about how to access them down the road other than classic drip marketing? So what's state-of-the-art thinking here of the 10/90, what to do about the 90?

Yeah, it's a great question. So on the first one, I'll say I've done a bunch of tests on understanding the user journey prior to people engaging with my funnel. There's a lot of words for that now. People call it the dog funnel. It's similar to the intent signals we talked about. And that is becoming pretty good. We're pretty good at understanding like who's in market now and who is about to be in market. So for example, if you look for a gorgeous— an e-commerce company that hires a VP of success, that's opening a job, sorry, for VP success, is very likely to be in market in a couple months. That is very reasonable. So we know that, right? Now, what's interesting is I've tried in the past multiple times to use that information to accelerate the buying cycle. And I wanna say that has not worked. You cannot accelerate the buying cycle, all right? I tried that. I'm gonna be very specific. At Segment, we were really good at predicting who's about to be deploying warehouses. And we thought, hey, let's start drip nurturing them about Segment. You know what? They're not ready. They're not ready. Like mentally, they're not there yet. You can't just sell them on like the next thing if they haven't done that education, right? But what you can do is identify them, put them on the timeline and say, hey, we can start seeding some useful content, be top of mind, provide value now so that we have 100% coverage on those people when they come in market. And I actually built a metric a specific case when I was at Drift, because it was obviously chats, you know, you can scrape who's, you know, using Intercom or Drift. That's very easy. You can see that on the websites. And I, we looked at of all the companies we predicted would be in market, which ones ended up buying Drift, Intercom, or somebody else. And the answer is we became really good at predicting, predicting who would buy a new chat and we pinpointed all the ones we predicted and that we did not talk to as a failure of growth and marketing. And now all the ones that we talked to but bought somebody else as a failure of sales. Right? And that is, if you can do that and your product is exposed on a browser, I would strongly encourage you to do that. It's very valuable because then you know, hey, why did we miss that company? Like this company just bought our competitor.

Yes.

What happened? Why do we not know about it? What signal should we have seen? Did they hire somebody? Did they buy, you know, a relevant technology that goes with it? And so you need to be able to map all that. You can't accelerate the buying cycle. You can just be top of mind in the before cycle or the next cycle. Generally, insight.

Yeah, I think only what do you for advice for folks here or later, I find only the best marketing teams and sales teams truly analyze their loss rates and their loss MOTA. Most don't. Most want to focus on the win and hitting the plan. How often do you see people do that well? And what's your best advice to kick your team's ass so you can focus on those analytics like at Drift?

Yeah, I remind everyone that every startup I work, I only work with underdogs. That's my thing. All right. That's like the thing I love. All right. And we are, we need to, if you look at Ramp, Ramp has less than 1% of market share. We're not competing with Brex. That's a mistake. We're competing with Amex. Okay. That's who we're competing with. That's the goal. And if you look at a Drift, like thinking that we compete with Intercom, like directly, sure. But like how many websites just don't have a chat? That's the, that's the real goal. That's the real goal. And so every time we're looking at the market, we need to understand who's doing and buying something else. So I am pushing the team to understand how far we are from being dominant and being very realistic about those loss rates. Yeah, I agree. I think you need, you need to look into that every time. Okay.

Last one and then I'll let you go. Um, unless you wanna grab anything else, but going back to my initial question, because this will be helpful. The point about learning over segment drift and Gorgeous Nose is that you can't accelerate the buying cycle. It's very profound actually. So what is state of the— and we're all about ready to vomit from breakup emails, right? If I get one more breakup email, I'm— and now I literally just spam them in Gmail in the hopes that they can't reach anybody. Like I didn't used to be passive aggressive, but now I I put them in spam into my Gmail. What is best practices here from a marketing perspective? How many contacts? What's— how can you do this better so that it works? How much value to add? What type of content? Anyhow, think about, I mean, how can you measure some and say, hey, it's gonna be 9 months on average until we close them. What do we do for those 9 months?

Yeah. Okay. Great question. So you'll be relieved to hear I do not send breakup emails, nor have I ever done that. My emails, we strive that almost all of our emails provide value in the first email, which means I almost never talk about my company in my first email, almost never. People don't care about my company, my product, they don't care about me. Okay, that's not the, that's not the top thought for the day, to be honest. Okay, which means I try to have my teams come up with something If possible, it is uniquely valuable. Let's just go back quickly for the Gorgeous example. The Gorgeous example, we had at the time built an Instagram scraper which would monitor the negative comments, posts on— sorry, the negative comments on Instagram posts about brands we would monitor. And if the brand had not responded within 2 days, we would automatically screenshot that, send to the head of marketing and say, hey Jason, there's people saying negative things about your products and you should just like, you should handle that. And that's it. That was the, that's just the message.

And it's true.

So it's factual, like you should do something about it. Two, it's verifiable. It's there on Instagram, right? And you know, it's actually helpful, right? And it so happens that gorgeous eventually does integrate with some of those things and can help you handle that. Right? And so sure, there's obviously a parallel, but what's your first answer there? Thanks. I said, hey, thanks. It's cool. Thanks for pointing that out. That's it. I'm just trying to create value in order to get reciprocity. And if I do that, I'm doing a pretty damn good job as a marketing salesperson. If you can do that at scale, you win. Got it.

Okay. One last one. Caitlin, can I have one last one and then we break? This is just another meta one. That's really helpful. And One I've talked about a lot lately, and I'd love to hear your thought from a marketing perspective, is switching costs. Switching costs. Let's take Ramp. Okay. Yes, I can switch to Ramp from a competitor, but you know what a headache it is with all the recurring charges I have, the integrations with my other systems. Now, Ramp's not— Gorgeous is maybe a more interesting example. Okay, I want to go from Zendesk to Gorgeous because it's focused on e-commerce. But what about all the records I have? What about the money I've put in Zendesk? What about the switching costs? And I feel like I challenge folks all the time for fun, sales reps and sales executives. Okay, what will you do? How will— okay, I'm interested in your product, but I don't got time and I don't want to pay $100,000 in 6 months to do it. So how are there— is there state-of-the-art thinking on how to incent the switching?

So I'm— and we might have different opinions. I'm a big fan of a combo of two things. One, it's a buyback. So some form of a buyback. Yeah. You're paying for the remaining months of the contract to offset some of the switching costs. The cash part, or it's not the human cost. Okay. Yes. The second part is that I've tried, and Drift did that the best, is most of the problems of most of the churn, you can see it's linked, is onboarding churn. It's that you didn't onboard the customer properly, right? They just didn't do what it takes to, like, you know, get to the success of the product.

Yes.

Okay. What we've done, we've figured out, is we make the product free for the POC, completely free, if the customer commits to a list of onboarding tasks. All right. Month by month, there's 3 months and there's those things. And they seem easy when you sign the contract. They're not. You need to go through legal and security and all of that. But if they do those things and they fail and the product does not work for them, they don't get the value, we just pay them back and say goodbye. We did that at Drift. It was amazing. People did not believe the product value. I don't know, we're with Intercom, it works great. This value is not gonna realize. We told them like, I understand you don't believe us. You do those things, those playbooks we recommend, you put the chat with that playbook on these pages and it doesn't create the lift, The product's entirely free. You're off, you're off the hook. Right?

I love it.

When you do that, when you do that and you're really convinced about the product, obviously the product needs to work. You do that, the people will realize, wow, like they're really committed. I should try this thing. And it reduces your churn, which is the biggest problem onboarding churn. Yeah.

It's a great one. I did not know Drift did that. And I, when I used that playbook the other, on the sales side, I found that— whoops, can you guys still hear me?

Yeah.

I found that there's a middle segment that's like an almost, and I am surprised how much that commitment of standing— of not paying if you don't do these things or hit it, it will tilt people over, right? It doesn't address the activation issue, right? But there is this segment that is— they're almost going to buy the last day of the month, they're almost going to buy here, but they don't want to be ripped off, they don't want the game, they don't want to deal with the headaches. And if you take that, that that unvoiced objection out. I found it's magical. I find this magical. Magical.

Magical. Yeah. All right. We'll stay on that word. Magical is the word.

Magical.

All right.

Thanks, G. This was great.

Awesome. If you want more magic from G, come to SaaStr Annual. He will be there. So make sure you buy your tickets and come to San Mateo. If you're looking for more Workshop Wednesday magic every Wednesday, Wednesday after Wednesday, next week we have Insider. Thank you again, G. Thank you all.

Bye.