Achieving Low-Cost Growth For Your SaaS Business: Sustainable Strategies from HyperGrowth Partners

So when you think about hypergrowth and reaching hyper growth, what does it look like? Is a question I often get. And obviously if you think of the obvious examples, the Shopify, the Twilios, the Slack, just want to show a bit 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 10 to 100 in one year and to winner couple of bits. 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 we'll come back to it. So obviously when you see that, you're like how can I grow as fast as rev? And so those four let's say components which I would summarize it to. So yeah, low cac, scalable strategies, a growth team with engineers, super duper important. If you do not have engineers, I would question whether you're a growth team. You're probably a demand gen team and if you have questions, let's cover that 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 going to do things differently if you're using the same tool and the same org chart, same resources. I don't think there is a 10x marketer in most companies. That's not a thing. All right, so you need to have a different mindset to the fourth point. That is using different resources and different tools. That is how you create that competitive mode. And it's very, I'm very intentional on the ladder on the point 2, 3 and 4. So let's go through like the first one, the scalable low CAC structures. Let's look a couple of examples. Generally I'm going to pull out one of the examples which works really well for sales led SaaS businesses and that's outbound. It's not like your, I think in the US you'd say it's not your mother's outbound is what you would say. It's high scale. Modern outbound has extremely good tacit an extremely good scale. So the way you're going to do that is you're going to build an understanding of your entire target market, what we call the TAM target accessible market, sorry, total addressable market. So your total addressable market and you're going to map all the companies, you buy the data for all the companies in the market and then you buy all the contact data, you score them, inject that into a database of yours, you run some personalized copy and you add it to 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 Marc Tech 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 predict leads, the technographics data, the website visit data. These days you have six sense, you have a climate that does that, right? All that tells you which companies within your TAM on your database are expressing by 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 segments. There's an old slide. It's like 2018, 2019, maybe five years old, six 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 during your mid, your perfect icp, right? And you power chat dynamically. You pull an AE into that chat and you send an email to the right buyers of the company. That's your day. Still does not exist in a single platform. That is a competitive mode. A good example of using technology to solve to create competitive modes. Good example of using engineers, ops engineers to build ads. How do you build a temp? I'm going to pull an example from the Ramp playbook. They used to have multiple vendors. They had like five or six different vendors. They had the Zoom info, the, the Clearbit and all of that, 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 European company that aggregates all the vendors into one API, into one platform, one cost. And so rather than having to buy the credits, sign the contracts, go to legal with all 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 contact at the best price. So basically that's what they do. 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 going to last. The point of technology advantages that they never last five years, bugs, they could last 12 months. And if you don't have that 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. I'm both an investor, but I've tried using things like Cavus, which does deep fakes for SDR videos. And so instead of having the sdr, this is, hey Caitlin, I'm G from Hypergrowth and I'd love to talk to you, which works, but it's expensive to have those videos at scale. They built a deep take 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 will drop. All right, so there's reversing to normal. The point is try this, try the next new thing, be on the lookout, aggressively look for new technologies. For example, I've been doing marketing growth for a while, but when I go at Sastore in September, NSF 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 either the small boobs, the small vendors, the young teams, and I'll just have a coffee with them if you understand. And most are not a fit for me But I'll always find a few gems in there. In terms of email playbooks, this is what I used to do in the past decade, 2010 to 2020, we would buy the data from it, inject a couple of 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's like the Persona specific play. Those were very simple lists of, 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 forecasted predicted outcome. And that worked fairly well. This is not 2010 anymore, my friends. We've moved on from this. We're now in a world of AI. All 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. I have the pleasure of showing you two examples from rev. Actual examples. I am sharing them because people who have received them have shared them on LinkedIn. 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 of 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 very personalized. Okay. And you can see what the person has posted on their own on LinkedIn. 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 were part of a small demographic and you have something in common. So there's kind of a relationship, there's something there and you've taken care of writing something constant, 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 this 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 one or two sports team. And people love their sports team, that 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 three. 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 will take a demo with me and I'll give you a $50 gift card. $100 gift card has a much slower 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 that has built a database of all upcoming college games and competing teams, the likelihood of outcome, so you can pick the right bets. So this is a sports betting algorithm happening there. So 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 intense signals from companies about, you know, changing the crowd cards. So if we can't intend signals, we're going for the best excuses, personalized excuses. Very, very relevant. All this is powered by GPT and this, this is the modern approach. Sorry. So that, that is, I'd say, what you should all be focusing on if you, if you want to build the modern approach and let me cool. Okay, so with that said, I want to show another example of a G.

I think right now I'm only seeing like the. No problem.

Stop this a second. I have gone 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. Questions about what the company name is for that deep fake video.

Yes, I'll write it down in the chat. It is called Tavus 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 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, 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 this is absolutely correct. This is great. It's going to work. Let's try it. I'm always for trying new things and see if it works and creates the right, let's 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. If you have a VP of growth, head of VP doesn't matter. And then there is per channel, 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. 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. 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. That is the structure that I recommend that enables you to create those kinds of aggressive experiments. So just to close so we can move into the Q and A. The mindset I 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 going to come up with like the one experiment out of one that's going to work great. 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 one or two that are strong outliers as the examples that I shared just before showing. 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. 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. And I hope this and the same thing is true for the split with core products. So just to summarize the takeaways here, the right technology stack scale, always scale will bring you the low cap. Your growth team, you should have a growth team. 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. If you are beyond the Series B, which is where I tend to purpose 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, let's move into the Q and A and have a couple of more appendix slides. If there's questions and I can just pull them out.

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. How do you think about that in general? And then two, 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 six months they're willing to buy a ramp or in nine 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 1090 and 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 joining prior to people engaging with my funnel. There's a lot of words for that. Now people call it a dog funnel. It's similar to the intent signals we talked about and that is becoming pretty good. We're pretty good at understanding who's in market now and who is about to be in market. So for example, if you look for a Gorgis a 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 want to say that has not worked. You cannot accelerate the buying cycle. I tried that. I'm going to be very specific. Ad segment. We're really good at predicting who's about to be deploying warehouses. And we thought, hey, let's start drip, nurturing them about segments. You know what, they're not ready. They're not ready, like mentally not there yet. You can't just sell them on the next thing if they haven't done that. Education. Right. But what you can do is identify them, put them on the time 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 can scrape who's using Intercom or Drift. That's very easy. You can see that on the website 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 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 in 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 and truly analyze their loss rates and their loss moda. Most don't. Most want to focus on the win and hitting the plan. How. How often do you see people do that? Well. And what's your best advice to kick kick your team's ass so you can focus on those analytics like a Drift.

Yeah. I remind everyone that every stuff I work, I only work with underdogs. That's my thing. That's like the thing I love. Right.

And.

We need to. If you look at Reamp, Reamp 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 what we're competing with. That's the goal. And if you look at a drift, like thinking that we compete for Intercom, like directly, sure. But like, how many websites just don't have a chat? 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 to look into that every time.

The last one, and then I'll let you go. Unless you want to grab anything else. But going back to my initial question, because this will be helpful. The point about learning over segment drift and gorgeous note 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 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 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 going to be nine months on average until we close them. What do we do for those nine months?

Yeah, okay, great question. So you'll be relieved to hear I do not send breakup emails, nor have I ever done them. My emails. We strive that almost all of our emails provide value in the first email, which means I almost never talk to 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, that is uniquely valuable. Let's just go back quickly for the gorgeous example, the course example, we had at the time built a 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 two days, we would automatically screenshot that sent 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's just the message and it's true. So it's factual. You should do something about. It's verifiable, it's there on Instagram, and it's actually helpful. It so happens that Gorgeous eventually does integrate with some of those things, and so it can help you handle that. Right. And so, sure, there's obviously a parallel, but what's your first answer there? Thanks. It's a.

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 a hundred thousand dollars in six 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 of it. I'm a big fan of a combo of two things. One, it's a buyback. So some form of a buyback. You're paying for the remaining amounts 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, most of the churn you can see it's linked is onboarding Churn. 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, for the poc. Completely free. If the customer commits to a list of onboarding tasks. All right. Month by month, there's three 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 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 going to realize. And 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 entire 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 on voting. Churn.

Yeah. It's a great one. I did not know drifted. And 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 un unvoiced objection out, I found it's magical. I find it's magical. Magical.

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

All right. Thanks, G. This was great. Awesome.

If you want more magic from G come disaster annual, he will be there. So make sure you buy your tickets and come to San Mateo.