Messaging Module Teaser with Zach (Octave)

All right. Yeah. It's three minutes after. I agree, Ben. Let's, let's kick this show off. So I'm going to give a few minutes of introduction about Go to Market Engineer School because this is essentially a teaser of one of the modules, the second module for Go to Market Engineer School. I will try to keep it somewhat short and I volunteered to wear this funny hat in exchange for you listening to kind of how Go to Market Engineer School works and how it's different. And then five minutes or so from now, I'm gonna hand it over to Zach, who's gonna lay down some knowledge and then take some, some, some questions at the end. Sound good? And I think everybody's on mute, but so that's good. Sometimes we get some crying babies or folks fire engines in the back, but I'm awesome. All right, let me try to share my screen here. Boom, boom. Okay, so you guys can see this. All right, so yeah. I'm Jared Waxman, co founder of Go to Market Engineer School. Thank you so much for, for joining today. I want to start with something that I hear over and over from people and that is people in GTM growth, sales and and rev ops roles. They tell me that they know that AI could help them go to market more quickly, more effectively with less manual work. But they're struggling to really catch up with the pace of how fast these tools are evolving. Whether it's CRM hygiene or building personalized outreach at scale, or being more responsive with customer conversations, or let's say creating high value content, whether it's for social or high value assets gated or content that just lights up the LLMs. With AEO, we know this is the promise of AI and we see the top 1% of folks doing it and posting a lot on LinkedIn about it. But we want a smooth on ramp for people to learn that I know something that I wanted and I want for my peers. So that gap between what's possible and then what's what the modern tools afford us to do and what folks are actually doing is huge. And Go to Market Engineer School exists to help close that gap. Great. So we believe that Go to Market Engineering, it's not just a new buzzword, although it is a great one. It's really a shift in how modern revenue and growth functions work, to be honest, and so combines tools, data, workflows, automation, messaging and combines into a coherent engine. So there's tools like Clay, Octave, air, ops, cargo, N8N. And with these tools you can build a lot. Your stack may Be different, that's fine. You learn the patterns, you learn how these things are put together, the different ways that these workflows can be built across these tools. But not just connecting the tools. It's really understanding how signals play into your go to market engine and how you use those signals in different ways. Go to market Industrial Engineer school is really about giving you hands on training, real frameworks, building live and give you tool credits and peer learning. So it is. Who is it for? It's ideal for growth operators, for folks in rev ops for marketing and sales folks, agency operators, basically anyone who wants to scale their impact.

So.

We'Ve got some proof from our last cohort. Nine out of 10 graduates said they recommend the program to peers. Thirty percent of our participants landed a new role within about two months of the course. Today's agenda I mentioned I'm doing this little overview here and then Zach's going to lay down some knowledge, show some workflows, tell you a little bit about what you would be learning and what we'd be building hands on in the cohort and then we'll take some questions. What makes go to market industry a little bit different Is cross tool fluency. It's like a taster. It's like a whiskey taster or something like that. Stack integration, learning how these tools kind of work together. It's hands on. It's project based. It's a little bit of theory but mainly doing and getting stuck and debugging led by Experts whether they're CEOs or head instructors or or people running agencies or outbound agencies. You get free credits for the tools that should last you two months while you're building and learning. You don't have to worry about burning through your credit card. And then you get a slack community with the other students and the instructors and TAs to help. The structure of it. Last bit here. The structure of it. There's five modules. Let's kick off with Clay talking about research, enrichment and scoring and that leads nicely into Zach's module about defining your ICPS messaging personalization. And then we go into cargo, a different way of doing workflow automation in GTM and. And that's going to be a good section.

And then.

And then we take another look at it and how one of the things you can do in n it n where NN really shines. And then finally we wrap up with talking about content entering optimization ll optimization with air ops. The structure of it structure of the course. We have a Wednesday two hour whiteboarding session, live lecture, instructor led it's from 8 to 10am Pacific. There will be a recording available if you have to miss one or two. And then we have Async homework for you and a series of live debugging sessions led by TAs. They're an hour each. We're going to have multiple time slots throughout the next few days. You'll have the weekend to work on some of these builds. We'll have another couple of sessions of debugging on Monday. So you're gonna struggle on your own and then you're gonna come in with a small group of folks and a TA to tell em where you got stuck and get help getting unstuck. We're gonna tag these as either beginner or intermediate. So you can kind of pick what level you're at and be with peers that are kind of working at your same level. Also just to note, we have substack with a podcast. You should check this out weekly newsletter and we're dropping some great podcasts, interviews with top leaders in this space and we have a better market engineer job board as well. And the course itself is 1850. These are a bunch of things that you get in it and you can go to our website. We have an upcoming schedule and we have some more webinars next week with Cargo and with Air Ops and talking about N as well. And then if you are interested in the course, great. The last day to register is coming up. It's on the 22nd. And if you're not able to join but you want to just continue learning these webinars, awesome. Join us and we'll have recordings as well. And that's it. With that I'm going to kick it off to you, Zach. I'm going to stop my screen share here.

All right, awesome. Thanks everybody for making some time. Really appreciate it. Hopefully you join us in the full school. But also hopefully today we want to leave you with something valuable too. So we'll get a little bit hands on. I'll show you a little bit of Octave and Octave is free to get started. So hopefully you can leave with with something that's useful. But to give you a little bit about myself, my background is in sales. So 15 years ago, which is crazy to say now I was an sdr. I've held a variety of sales roles, growth roles, BD roles, but always kind of carrying a bag. I say, you know, even as a founder, today I'm just carrying the biggest bag I've ever carried in my career. So I, I consider myself a seller first. I see Some people on the call I've actually worked with at companies before, so that's awesome. But yeah, I've worked in a lot of different stage and size companies, so places like, you know, LinkedIn, Dropbox and DocuSign, also very large orgs, you know, like VMware and also, you know, smaller startups with nine people where I met my co founder. So give you kind of the, the backdrop for Octave a little bit. You know, where, where this all started was, you know, something I felt for a long time as a salesperson that I didn't think was necessarily solvable. And that was that there was so much kind of tribal knowledge and information required to be successful in selling and positioning whatever company I was working for that just wasn't accessible anywhere. And you know, not a groundbreaking thought. I'm sure anybody in any sales and marketing role has, you know, felt that experience wherever they've worked. And I think that obviously changed when we all saw, you know, generative AI for the first time. And probably everybody had that holy shit moment where you go like, oh my God. Whether it was a case study or an email or something, that you could just punch in a little bit of a prompt and get something back. I think where we started to get really excited was not just that oh my God, I can get this content, but can we use generative AI to actually store some of this data that didn't have a home before? And what I mean by that data is things like your Personas and their pain points and the different use cases and the business problems you solve. Like, do we have an opportunity with generative AI to store that in a new way and to make that knowledge more accessible to actual workflows, you know, not just stuff that you'd have to sit in a webinar like this and learn from somebody else at the company and hope it downloads into your brain and then you be kind of the repository for it at the end of the day. So that is kind of where Octave started. And you know, we found a really cool opportunity in B2B go to market. Because I think a lot of people haven't necessarily appreciated the depth of complexity. Probably everyone in this room, but maybe I'm speaking more to the world at large, you know, the depth of complexity and nuance that exists in your go to market. And you know, I, I always joke that like, I think there will be a killer AI astrophysicist before there's a killer AI seller. And it's because, you know, the LLMs, they have these incredible, you know corpuses of knowledge to train on, especially in the, in the hard sciences. Right. And that's. You always see the, the benchmarks when they release a new model, they're always around science and math and things like that that have a kind of ground truth that doesn't really exist in sales. There's nowhere for an LLM to go and learn. Like, hey, we've had this Persona who's kind of a. They're an influencer, they're not the decision maker. We met them at a happy hour, they're in this industry, in this use case and hey, chatgpt, like what do we do? It will be a yes man, it'll give you a sensible answer, but it's really not grounded in any source of truth. And oftentimes that source of truth is the experience, is the knowledge, the data we have as an organization. And so this is maybe a bit abstract. Hopefully I'll make it concrete when we see some of the product. But like Octave is trying to capture a lot of this knowledge and this important kind of context that exists in your organization and make it actionable. And at the end of the day, what we're trying to help you do is, you know, organizations now I say we're kind of rich in data. You have every type of enrichment possible. You have firmographics and technographics and you have website intent and you can mine call recordings in your own CRM and you have all this data. And then if we just think about, you know, kind of the campaign use case and you think of the other side of that pipeline, the old world is a whole library of static templates that look like Mad Libs. Right. And there's kind of no way previously to ever have enough templates or to be sensitive enough to the data in a way that you could create really good messaging. Right. So think of Octave as like we are trying to be that prism in the middle where you can feed us that data and we can be really sensitive to it and grounded in. We know what you sell, who you care about, the problems they have, all of those things that are the rich context you need to really get the most out of AI. And then we can 3D print everything on the other side. So that's my big high level. Hopefully some of you stuck with me on that journey and I didn't lose you all. But don't wait till the end for questions. Jump in, Jared, I'll let you kind of monitor the chat and tap me on the shoulder. But before we kind of get our hands Dirty A little bit. Any thoughts, questions? Messaging, Octave, the company or otherwise? Sounds like a potentially no.

Well, Zach, who do you typically get the most engagement from? Like who you know, who should really be paying attention to this, what kind of roles, what kind of companies?

The companies I would say typically that are most successful with Octave are generally speaking, you know, software and technology businesses. And that generally happens because with software and technology you usually have lots of different Personas, lots of different ways people can get value out of the product. Lots of use cases. Right. And like as soon as you have that type of matrix where you have Personas and use cases and different market segments, like that gets complex really quick. So those types of businesses are typically who we are most successful with. And then those that are of course focused on building a always on growth engine, I'd say that's a big part of it. Always doing cold outbound, always doing warm outbound. Making sure everybody PQL and MQL and their lifecycle marketing is always being highly tailored. You know, if you're looking to build that type of always on machine, you know, those are the, those are our happiest customers on both sides.

Cool, thanks.

Yeah. Anything else? Should we dive in a little bit?

Dive in.

Let's do it.

Take a look.

All right, anybody want to, we can do this live demo. Let's test us. Anybody want to throw out like a B2B SaaS company we all know about as an example? And I'm going to start sharing my screenshot. You tell me if you went on zoom. Yeah, do it on zoom. Okay, we are going to do. Let's see. That's dot us, huh? All right, cool. So what I'm doing right now is basically some of you have probably done this already, but I'm basically going to spin up a new instance of Octave and just kind of show you, you know, what we do. So right now we're identifying, hey, our product is Zoom. You can add more context if you have other documentation, things like that. Right now we're just going to go without it. And again, you can all do this stuff on your own for free and hopefully there's some value you can extract. And so what it's doing right now is basically, you can imagine we have some data and models we're using. We're going to do a live scrape obviously of the target company and then we're going to start building kind of these components. Like these are going to be basically definitions we load into the model to kind of build your own ICP Brain is One way of thinking about it. So we're going to assume here, for the sake of time, that we did a great job and we nailed this summary. But even if we didn't, I'll show you how you can further kind of fine tune your model later. And the big idea about this whole machine we're building is we want to make this really easy to keep up to date as your markets move and shift and you target new segments. And so let's just say cio, head of it, VP of collaboration and let's generate some more. Let's just see. So you guys can see you can generate more Personas, you can add custom, you can always add more later. Let's say workplace experience. That sounds great. And then same idea. What are use cases that our product solves? This sounds great, continue. And now you could add in, especially if you have notes here, a bullet point or two about what makes you most different. What do people do without you? That's great. You can also let the model take a first stab. So what we're doing now behind the scenes is basically creating like a definition for kind of each of those stubs in Octave's brain for your company. And so the value of that is you can think of we're kind of building a knowledge graph. Like what we've spent a lot of time developing is like how do Personas and pain points relate to use cases and relate to segments. That's a lot of like the kind of scaffolding we built is like mapping out all these relationships that are very specific to kind of B2B go to market. So now the workspace is ready, we'll poke around here a little bit so you can see basically what's happening is we have kind of our company definition. We can dive in there further. You can see our Personas have been created, use cases and then we have the ability to add lots more kind of nodes to your brain. So the things that matter, like who are reference customers, who do we talk about that we've made successful? What are different segments we go after? Cool thing here is you can think of this in basic terms of, hey, we have a SMB mid market enterprise. We talk to them a little differently. But in Octave you can define this in natural language. Your segment could be, hey, we target E commerce companies differently than we talk to fintech companies or whatever you want. Right. The system is flexible to your definitions. And then things like competitors and proof points. I won't go into all these. This is where you kind of map stuff out where it starts to get fun is again, we all know things are more competitive, moving faster than ever. We want Octave to be a place again, not a, not a dumping ground for static decks and docs, but a living brain. Right? So here basically you're seeing, you know, looks like a nice, you know, notion page, what have you. This is the model reflecting its current definition of like when it says zoom. This is what I think the cool part is we want to make it really easy for you to kind of fine tune this brain. So this notion of refine is accessible anywhere in Octave. And it makes it simple for you to just chat with your model and make your brain smarter. So you could do something like, you know, bad example, but make this more about how we help with GDPR compliance. Right? Totally crazy. I know that. I just kind of want to show you guys it's as simple as this to kind of change your messaging and positioning. And you see it's going to go through and go, okay, if that's how we want to update our story, it's going to go through. It'll show you the diff view all the things we're going to change. And then if you wanted to update that, all you'd have to do is go confirm changes and then that flows to everything downstream, right? So now your whole brain got smarter. So I'm not going to do that because that doesn't make sense in this case. But you get the idea. That's kind of the library. I'll take a quick breath and pause. Any questions about the product or kind of about, you know, defining these, like, these primitives in general. Curious if anyone has thoughts or takes or see anything we haven't covered.

Or we'll keep. I have a question.

Oh yeah.

On this particular example. So say it's Zoom. Say it's, you know, HubSpot. Any of these larger companies who have multiple product sets that sell to multiple Personas, is there a way to have it scrape that or is that a best practice to kind of add those in individually as separate products sets?

Great question. So you can have multiple products, right? So you can add, add a new product, add a new service. So you can definitely. I would say the thing to think about for companies best practice would be create new products when they are truly. Hey, I would go out and like, I have a different story to tell about this product versus something else. You know, I, I will sell. You know, DocuSign regular is one thing. And yeah, like Docusign for real estate companies, like, that's a different product. Using the example from my past. But like that would be something. Yeah, like we have a different go to market because real estate's such a unique industry. So the best practice would be like when they're like truly materially distinct offers that you would speak to your market about separately. Create that as a different definition. Oftentimes we do find sometimes it's more about the use case. You know, it might be like the use case is where that differentiation really lies. It's not at the core product. So just something to think about there for sure. Cool. All right, let's build a playbook real quick. So library is kind of the foundation. We consider these like the core kind of building blocks. Playbooks. These are where we want to help you kind of create that story that's a bit more precise for different audiences or kind of niche clusters. So you can go like, hey, I want to sell this product. And then we want to help you think through like how you position, like do you want to position A sector based playbook would be like, I want to develop messaging that's really about the type of company you are. Again, maybe the, the FinTech versus E commerce solution may be more oriented around a business problem. Hey, we help you reduce credit card fraud. Blah, blah, blah. Milestone is maybe some compelling event or you can have, you know, competitive playbooks. Hey, you know, HubSpot is better than Adio because blah blah, blah, blah. Right? Or account based messaging. Like we want to develop a campaign just for, hey, McDonald's. Here's how we can help your IT team. Whatever. Let's do a sector one together. Just so you see the idea. And again the, the, the hope behind, you know, our app and this product is we're, we're giving, you know, we want the human to be at the center of this but giving you good struct kind of theory to build and model all this out so you can see it's already starting to learn and like consider different ways we could break down different sectors. So let's say yeah, creative agencies, like that sounds great. And then you know, the key insight we need for lots of, you know, high velocity. Oh, I can't spell this morning. Async collab. Right, Something like that. Great. And then you can determine like who are the Personas that like matter in the segment. So yeah, we're going to pick the head of IT as well. And then what are the best use cases? So yeah, we think Unified team collaboration Hub is like that's the core for this audience. Again, we haven't added these Other elements yet. So we'll create a playbook. So playbooks, like think of these as like where we can define all those kind of clusters that we want to go after and like test different messages with to see if we can find, you know, message market fit. And the idea being we want to help you go more narrow, to drive more engagement, right? So it becomes really hard to get engagement with your market when you go, hey, we help financial services companies be more secure. You know, we want to help you go, hey, we help, you know, mid sized credit unions, you know, detect fraud in their signup process earlier, blah, blah, blah, whatever, right? So you'll see the playbook that's been created, it starts to kind of give you this pov. You know, how would we talk to these creative agencies? It will generate what we call value prop hypotheses. So now kind of helping you break down, okay, for each of these Personas in this kind of cluster, what are different things we can test in our messaging? Right? This isn't meant to be the copy you would use yet, by the way. These are meant to be more kind of conceptual. But this is a really cool place where we kind of make that transition from like, we want to help you take the theory and the context and turn it into action. So you can see things like obviously these toggles are to make these things available for the agents to use or not. So maybe say like, hey, you know, this isn't something we want the agent to talk about. You know, those two. We're going to turn off the other cool thing I said already. But you can refine Playbooks as well. So you can imagine these Playbooks can power real time campaigns. You could have a campaign that's targeting people in the freight and logistics industry. And then something like tariffs comes up and you go like, oh my God, we have to update all our messaging. You could come in here and be like, make, you could go make this more about how we help with tariffs, blah, blah, blah. And then boom, you could update everything downstream immediately. Right? So we want to bring us out of the world of static decks and docs and long cycles to change messaging. That's Playbooks. I'll take another quick, quick breath and kind of give you the, the last piece here, but I want to see if there's any questions or, or thoughts. I'll keep rolling. All right, last piece here. So then you can build agents. Agents are kind of how you activate all this context. So here, this is our sequence agent. We have a bunch of different types. So you can do enrichments, you can do qualifications. And to, to kind of give you guys the theory here, kind of what we found is that if you start with this baseline of getting really rich messaging and positioning, like encoded in that is actually all the information about your ICP and allows you to know how to research them better, what to look for, how to qualify them, how to classify them into different buckets. So that's kind of the theory behind these agents is we're like grounding them in. You work for Zoom, you know the Personas you care about, you know the different segments you target, right? Like that's kind of what we're building in the background. And then you can, in our sequence agent, which is where most people start, you can do things like determine what type of sequence, number of steps, you can ground it in different contexts. So you could say, for example, let's say you have many playbooks, which most of our customers do, maybe you have some agents that are in best match mode. Like, hey, you allowed it at runtime to go determine depending on who you send me, you're going to allow the agent to pick the best message for. So again, you're getting that kind of dynamic on the fly ability to build these things out. You can see here we go super deep. I'm not going to do it now. We will do it. We will go super hands on in, in the school. But you can train these agents around your styles, your vocabulary, you can give it example emails, right? So you can make these things sing whatever tune you want. And then basically here, this is meant to be a playground where you can kind of test your agent, train it further. You can do things like this. We have kind of a cool playbook powered search. Again, that same idea of like encoded in your messaging is kind of like who you're looking for. So we have a model that can even like help you go look for individuals. And so we could say, yeah, this guy Armando sounds great. We want to test this agent on him. It'll find this individual and then we can run this agent here. And so basically this is just meant to be a playground. Nothing gets sent from here. We don't do that. We just want to help you build this brain and, and build these arms that then connect into your existing infrastructure. So this agent, this flow takes anywhere 30 seconds to 2 minutes usually what's kind of happening in the background just to share with you guys. So basically we let the agent go out, we send it to go grab that person's profile and again basically go, hey, you're working for Zoom. Go research this person. Build yourself a research report. All right, Go to their company, same idea. Build yourself a research report. Now go look at this library. Pick the best playbook, pick the right Persona, and then kind of construct this whole message for them, right? So that's kind of what's happening in the background and kind of a simplified sense. And again, this is pure out of the box. You can train this thing however you want, but you can start to see, you know, how the agent thinks, its confidence, its rationale, why it decided to personalize things in certain ways. Again, lots of stuff you can do here. You can train these easily. You can go thumbs up, and then you could edit this by hand to improve your own examples and kind of recursively train it. But super cool. You save this puppy, we give it a fun name, and then it becomes available basically, as an endpoint. You can hook up anywhere you want. So this guy will save here in a second. And then you see now it becomes instantly available. You can use it anywhere you can use it. Clay N8N cargo raw API. Most of our customers end up using us for Clay. You can generate an API key and then you can plug it into Clay. I'll show you real quick. And then I'm going to truly pause and see if there's questions. But this is just a table. As an example, I pulled a few leads. These are like real people hitting our website the last day. And then what you can see here is I'm using a couple different. I'm using a. Got a little fancy here. Just to show you guys kind of some things you can do is we're using a qualified company agent and a qualified person agent. And you see, these are giving us scoring, right? And you can see in the scoring, it'll also. Actually, I can do this here. It'll give us kind of a rationale of why it thought, you know, this is an 8 out of 10. And then here I'm getting a little fancy and wanting to combine it with basically a score of the person. So I'm kind of going like, all right, how good of a fit is this company and how good of a fit is this person? And then in this case, just to kind of show you some of the possibilities, I created basically a score threshold where I'm going like, hey, I want the combined score to be over 12 to consider them qualified. And then if they're qualified, I hit the run sequence agent, and then it's going to build me bespoke messaging for all these people and then those could flow straight into your sequencer. So very quickly you can imagine you can build up these very high fidelity, really precise flows that kind of turn into evergreen pipelines and generate again. I think of it less about personalization and more about being context aware. How do we speak to people about the problems that a small group like them we know face and so we can talk to them in a really resonant way, you know, and relevant way. And so I'll pause there. Lots more stuff you can do. Tons of possibilities. But take a breath and see if we got some questions. Just minds are blown. Let's see.

Just to kind of break the silence. Let's see. To kind of break the silence here, Zach. I'll seed it with a question. So there's a lot here, there's a lot of different sequence agents. I mean what you're showing is mind blowing, but it's also a lot. So like if I'm, you know, if, if we're doing this in the module, do, do you give me a fake company to use or can I bring my own company, my own projects? Do you, you know, do you have, do you or do you have people in the module helping me to refine them, give me feedback, tell me which of the features to use when, how does that all work?

We will help. We're very hands on. We'll be hands on in the school. We're hands on with our customers and users. I'll be there, my co founder will be there, our Go to Market engineering team will be there. So yeah, totally understand transparently us as a business, we've invented this thing that doesn't exist before, this dynamic messaging context engine. So yeah, there's a learning curve. We're there to help. That's part of why we're excited to be part of the Go to Market Engineering school. If you leave this and don't become an octave customer, but you get better at working with APIs and these automations, like we're happy. Like I think this is the skill set of the future, you know, tangent. But like I think Go to Market engineering is going to become a incredibly important skill set. You know, as like AI proliferates, there's going to be kind of the do you build your own bespoke growth engine and kind of stitch tools together yourself or do you go for an older all in one off the shelf that promises an easy button? My personal belief is like if the thing you can pull it off the shelf and all you need to do is feed it money so it works like guess what, like that's the water table, that's where everybody, that's, that's the playing field. So to get above it you're going to need to do more and I think go to market engineering will be a really important, you know, skill set to do that. So we, we want to be a part of the community and help people build. Is my, that's my super long answer to your question. Oh, you're muted I think.

Let me read some questions from the.

Yeah, please.

From the chat here, Jordan asks, can playbooks be created for channels other than email? How do you think about Octave for the multi channel world?

Yeah, totally. So Playbooks, you shouldn't think of them as like email specific in any way. Those are really meant to be like how do we think about a certain defined group of individuals in our market? So that's really the purpose for a playbook. And then yeah, downstream, like we just saw the sequence agent generating emails again. If you want that style to be slightly different for LinkedIn, that's just, in our world that's just a style. Many of our customers use that for LinkedIn campaigns or many other places. So yeah, totally doable.

Do you have anybody using it for call scripts if they're doing upon call?

Yeah, lots of. Yes, you can imagine there are when you start to get really fancy and have really cool clay tables. You can imagine. Yeah, somebody comes into the pipeline, we're qualifying them, we're assigning them to the correct rep, we're creating call script, we're creating the LinkedIn and email messages that are going to be queued up. All of that can be done in one flow. So that's where it gets real fun.

And then Sarah is basically asking show me the money on average, what kind of lift in reply rates are customers seeing from this hyper personalization?

It, it truly depends. I wish I could sit here and say 10x, you know, it truly depends. I think for some companies this is, it can be that dramatic, it can be doubling, tripling. For other companies that are in highly competitive markets like I, I want to be honest with you guys like this, you're, you're going to need to do something whether it's with me or other tools just to compete, you know, like the, the playing field is getting more competitive, it's moving faster, there's more noise out there. Every company in the world because of AI like you're going to have a thousand more competitors in your field in two years because it's so much easier to build. So you know, I want to be honest with you here, like, if anyone's promising you 5x this, 10x that, like, they're lying, run away, you know, it's just, you need to get more precise and more dangerous and it's going to take a different, a different toolset.

And I'll also just add one thing onto that. Sarah. We have this podcast where we're interviewing outbound agencies and quite a number of them actually on their own, kind of brought up this question of like, how has Octave changed the game for them and what kind of lifts have they seen? So poke around and see if you could listen to some of those podcasts on your, on your jog. And I think you'll get some different perspectives on why people are shifting to.

This direction, I would say. And one other thing, not to sell too much here, I'd say a lot of our customers, it's not strictly response rate. It's also how fast can we deploy new ideas as our product changes? At a high velocity too. How do we go from, oh, we can release something on Monday and have campaigns out on Wednesday that are reflective of some new capability, some new feature, etc. Like, it's a, it's a compression of those cycles as well that people really value. Cool.

Let's see some more questions here.

Current customer here, live question real quick if that's okay. Yeah, has anyone, what are some like, more niche use cases for Octave? So say could you do, build like a custom agent? Say I, you know, close a deal on a, you know, super high profile account and I want to use some of the contextual information from a lot of the call transcripts to write a case study. Is that something that could be done.

In theory, totally doable. So yeah, like we have custom agents you can build, you can think in that agent builder I showed you, there's a bunch of like, yeah, I want sequence, I want qualification. You can also build custom agents that are like, they're kind of like stem cells of like they're tied to your Octave brain and have all that knowledge. And I want them to write a white paper or a case study or whatever you want. So, yes, two parts of that question. One, yes, totally possible. The second, I'm glad you brought it up is what I'd say, arguably we are the most differentiated in our capabilities is feeding in all that additional information. So again, whether it's from CRM data, call recordings, doing other enrichments, other signals like, hey, people are hiring. You can feed all that into Octave too and have those agents that are then like, oh yeah, I'm reaching out to DevOps person about blah, blah, blah, and they're hiring for a, you know, senior DevOps, you know, engineer. Like, okay, great. Like I know how to sandwich that signal and make that a part of the story very well. So totally doable. Any others? I'm pulling up the chat.

Any other questions about Octave, about messaging in general sales, the go to market engineer school schedule, anything ask live or chatted in here? Any questions about where you can get a wonderful hat like this, just let me know. The answer is cvs.

Thank. Thanks. I'm looking at the chat. Michael David, thanks. Thanks for chiming in. Pumped to have you guys customers. Hope all of you can at least for free, take it for a spin. Let me know your feedback. Would love to see if it helps you where we can improve. But we're here, we're accessible. Email me, find me on LinkedIn. We love to build. So we are here.

All right, cool. If there's no more questions, we can wrap this up. Thank you all for your great comments and questions and hope to see you in our next webinar, which is. I think we have one on Monday.

And yeah, I did just ask a question. Sorry to be late.

Yeah, go ahead, go ahead.

That was my comment above. But to kind of follow up on Sean's question about importing call scripts as contextual info. Is that something you demo real quick?

Yeah, let me give you just so we don't hold everybody too long. If people are eager to get out of here. Let me show you real quick, just to give you the idea. Where's my share button?

Yeah, it's a great question. This is cool.

All right. This is where the fun of clay we can start. Really having a good time. So just as an example in the sequence agent, so you would go into edit the column. Let me move my zoom screen here. So you're mapping in right now it's just taking in like the LinkedIn profile name, title, domain company name, bunch of other things you can do. You know, again, it starts to get fun. Different languages. This is what we call runtime context. And so here's where we have a very high degree of granularity. I hope this isn't too intimidating, but it's really cool where you can, for example, if you have a call recording and you want that whole thing to be a part of the agent's brain for your entire sequence, you can go all steps and you can just. Whatever column that's in, you can just put that in right and you would ideally give it, like, a little bit. The more if you give the agent, like, this is a, you know, this is a transcript from our God. I can't really type it. Last call, right? Something like that. You don't need to do a lot of prompting here. It's kind of the cool part about these agents. You can just stitch this in. You can also do this at the granularity of each step in the sequence. So just to give you an idea of, like, how this gets used, where people, you know, drive campaigns that do get much higher responses, is they'll do something like using a hiring signal. And maybe in step one, I'm pulling in the title of that job that I've scraped that they're hiring for, right? So I just want in step one, I'm going, hey, I saw you're hiring for a. Ahead of learning and development. Then maybe in step two, you want to weave in, like, hey, I see this job has been open for two months. You know, like, it seems like you've been looking for this person for a while. Like, step three, hey, I noticed you're actually hiring for half a dozen people in this department. You know, like, that is a way, like, you can take one signal and kind of break it down into these chunks. So then you end up with, you know, the agent is, like, sensitive to this whole story. It'll piece it out for you, and you end up with. It's like, can't fake it. Personalization, right? Like, it doesn't matter at the end of the day if AI wrote it or not. No one cares. The person is just going, like, all right, like, this clearly meant for me, this company, this person did their homework. I'm interested or not, you know, and, like, that's honestly the benchmark you should be looking for. So that's where there's a ton of fun. And like, those will be the kind of things, like, again, we can go hands on, super deep in the school where you can turn signals into kind of magic in your campaigns.

Can I respond to that answer? I think that to me, if I'm incorporating that level of personalization into a sequence, I might as well just write it by hand. That's kind of my response to that. I'm more thinking of. I have, let's say, two or 300 call transcripts. Want to sort of like, summarize the intelligence of that data into the, like, high level in Octave that is feeding the way that those conversations happen with everybody. Not on an individual level, but, like, these are. These are Patterns of things that we say in calls that lead to close one deals or lead to good outcomes, scheduling the next meeting, whatever it may be. That's the kind of thing I want to ingest into Octave and have Octave do some magic and help me position my. My emails from that.

Totally. So those are two different things. So one is, I argue, if you wanted to do what I just described across 10,000 emails by hand, like, that would take you a lifetime. So, like, what I'm describing here is programmatic. You would want to do that with some type of tool. Right. What you're describing is something different. Like, hey, you want, you want to feed in additional context into Octave itself? Yeah, totally possible. Variety of ways to do that. You can add additional concepts, you can add additional context. Like when you're building, hey, I have a call that's about a certain Persona and I want to add in a file about super easy. You can do it at that level of granularity as well and feed it into the overall brain. So maybe those are two different things, but both very possible.

Thank you.

Yeah, of course.

All right, thank you, everyone. Hope to see you again in another webinar or go to market school or just hit one of us up on LinkedIn. Take care. Thanks for your participation and thank you so much, Zach. This is fantastic, as always.

Thanks, everyone. We're here. Hit me up if you have questions.

All right, bye. Bye.

Bye.