The AEO Playbook: How to Get Picked by Agents | The Agents #17

So good morning. We wanted to do a very special edition of The Agents kind of live and go through just our latest findings on our agent-led growth playbook. We've talked a little bit last week on The Agents about agent-led growth. Now it's ask your agent instead of ask your developer. So what does all that mean? How can you really grow with agents from the folks who have 21+ agents 3 humans and a dog. So I'm Amelia, I'm here with Jason, and we're gonna kick it off.

Yeah. One quick note, there's always a lot to process and all these, this is gonna be great, but if it's overwhelming, if you go to sastr.ai/agents, we have a playbook that we update constantly and it, it doesn't have today's session, but it has everything we've done on our agent GTM stuff until today. And it will soon have this session. So you can always download that playbook, share it with your team, get refreshed. If you process by reading rather than watching, it's organized for you. It's got all the case studies and we literally, we literally just updated the last couple of days.

Yep. Yeah, it's a good call out. So with that, let's get started on today's agent-led growth playbook. So what do we mean when we say agent-led growth? I think about this in really one of two ways. You're listening to the official SaaStr AI podcast brought to you by— today's episode is brought to you by StackAdapt, the AI-powered marketing platform that allows you to plan, execute, and analyze both owned and paid media campaigns from a single platform. As the world of advertising continues to evolve, catch up on StackAdapt's Innovation Forum event to hear from its co-founders, OpenAI, and other industry leaders about the shifts reshaping digital advertising, the AI innovations driving them, and what they mean for marketers. Watch it for free at go.stackadapt.com/forum. Hey everybody, starting a business can get expensive fast. Website here, email somewhere else, business phone with another provider. Northwest Registered Agent gives you a complete business identity in one place with free Tools, resources, and built-in privacy from day one. Get more at northwestregisteredagent.com/saasterfree. That's northwestregisteredagent.com/saasterfree. S-A-A-S-T-R-F-R-E-E. Way one is you know using AI agents to help grow your go-to-market, as we have with Ten K, who's our main go-to-market agent. I would say way number two that is now getting traction is how to get picked by other agents when you ask it for something. Like hey, what are some of the best events we can go to? And then if it's a disaster, you know we're getting picked by the agents. That's very purposeful in how we've done that. So we've pulled out a few examples to show both. So I wanted to first start with just a hierarchy of our agents. To Jason's point, if you download the playbook, it'll deep dive into a lot of these. But just our latest agent landscape, if you will, everything. That 10K, our AI go-to-market agent, our main agent, is hooked into. He is custom built on Replit. If you haven't seen 10K yet, you'll see him today shortly. This is everything he's hooked into. Plus there's some 36+ additional tools on top of these tools that are listed here that it's hooked into that just didn't fit on the screen. So there's quite a bit to digest just here. But 10K, as you can see, has become our powerhouse. And one thing I always like to remind folks is 10K did not Start this way. He literally started as just a helper for us, you know, doing— help me do some outbound, help me get off of Notion and do some, some data a little bit better so I don't have to keep logging into Salesforce and Notion in 3 different places every Monday. And so he's definitely grown over the last, you know, 16 months that we've had him. And so a lot of this is plugged in now. You may say, okay, like, I don't, I don't have 30+ tools to plug in and connectors. And that's fine. This is our stack, right? Some of these are duplicative, which we'll talk about, and some of these are unique in that they're covering everything you need to basically run go-to-market. That's inbound, outbound, renewals, contacts, marketing newsletters. And then some of this is enrichment. So you'll see that here. And then some of this is quote to cash. So things like our billing in QuickBooks and Bill, etc. He's hooked up to so many things. This really lets 10K automate A lot of our go-to-market with approvals, with guardrails. But he has all the tools basically he needs. This is what you would give, you know, maybe a new hire, maybe not day one. So same thing like 10K, you know, we, we've stair-stepped him into how many applications he has now, but he has grown into his role much like a human would grow into their role in leading our go-to-market. One thing I wanted to show you guys in particular with all of that hooked up is what I call the prospector tool. So with all those tools, What I've really found to be beneficial in kind of like this agent-led growth motion is having one centralized surface or place or queue, whatever you want to call it, to monitor everything. And so this could be as easy as you guys pulling up a Replit, a Lovable, a Vercel, a Base44, whatever you like to use, and saying, hey, I want to hook into— let's say you have Salesforce for sales but HubSpot for marketing, and you want to hook into those 2 things. And you hook up whatever else has, you know, where's your inbound coming to? Is it one of those 2 places? Is it just an email inbox? How is your outbound being sent? Hook that tool in. If you hook one of each of those tools in for inbound, outbound, and maybe you have some tools or maybe it's just spreadsheets for renewals, you can hook it into something like this so that with the agent's help, you can start to monitor everything and go to market in one service. And this has been Really beneficial to us given how many tools and agents we have. Just in the, you know, having 3 people and 21 agents, a lot of things were falling through the cracks, right? Like even though we had an agent on inbound, we were still having people who contacted us manually via email. We had outbound that was going out from 4 different tools. Now that might not be you, but it's, it would still be nice probably if you agreed to have all those things in one place so that an agent can help you filter through any noise that you might have in those inbounds or outbounds, and make sure you are responding to any current customers, um, you know, renewals, support tickets, everything. And so we have everything now in one place. And so how yours might look for your prospector, as I call it, tool might look different just depending on how you have it and what tool you're using. But I know it sounds complicated. I truly believe anyone could do this today if you don't have an agent already. You could pull up RepLitter Lovable, hook in, you know, one of those tools in each of those places, just pick one thing. And the nice thing is, like, the more you use something like this and hook up an agent to do this, which is you can get a better view and the agent will actually get better on how to answer these things, right? So the first week I used Prospector, I only hooked up inbound for the first weekend. And that's to say like you might not even want to hook up all your surfaces at one point. You could just say, hey, week 1, we're going to do inbound. Week 2, or maybe week 4, we'll add outbound and then we'll add renewals and support so that eventually everything's in one place and you have this bird's eye view of everything going on. And go-to-market. It does mean that everything is going to get followed up with, whether it's you or the agent, until it reaches its goal. And so I feel like that's an important distinction because with the agents, they are relentless in a way that they are 24/7. You give them a specific goal for each of these things. So our agent knows that, okay, when it's inbound, I'm going to try and route that to get them to book a meeting. Or if it's a question, I need to route that to a human if I can't answer it. Then if it's outbound, obviously the goal is to book a meeting or buy tickets. That's a very different goal. And the agent will just keep going until it sees that it has reached that end goal with that one specific account or contact. So until it's, you know, close won, close lost, or case closed on a support ticket, the agent just gets better and better at learning your business, at what flows, how many touchpoints. Like the first week it might not know, okay, how many touchpoints do you need for an inbound versus outbound versus support case? It will learn and grow with you as you are answering everything in one place. It'll also get better that it's centralized because then, you know, maybe it sees things of I see a lot of the same questions, or I see a lot of the same patterns in your outbound. What's working? What's not? The agent can start to collect that data the minute you have it wired up. And so having it centralized is super helpful into something like a prospector where you can go through the queue and just action all of your go-to-market leads together. So I'll go through the inbound component first. So this is the inbound component because I feel like this is the most applicable to everybody. Everybody on this call has some sort of level of inbound. Everybody has website visitors and inbound coming to the website. So I started with this use case. Because it is something that everyone can use and there's a few things hooked into it. So in our inbound queue, not only is it centralizing everything into one place, it's also learning about that person simultaneously via the agent. So the first thing our prospector will do with an inbound lead is it'll give us any of their data. If it was our contact us form, did they write a message? Should they download our sponsorship prospectus? Anything like that will come in. Then it will research the pitch. So This is where it will first search our first-party data. And again, if you have nothing hooked up day one, it's okay. I wouldn't sweat it. Like, even if you just have like a little bit of data from Salesforce or spreadsheets, whatever, give it to your agent so it can look up some first-party internal data. So for us, these are a lot of tools that are connected for first-party data, but it's basically checking to see, okay, do we know this person already? Right? And I feel like this is nice because a lot of agents today, especially for outbound, only use third-party signals. And so having this first-party data is really nice to get that historical account context that you may not know or one of your reps may not know if they just got assigned this account. And so it's nice to have the agent and the human have that context before you're responding to the person versus just responding blindly. So that's, that's why it's wired up first that way. And that's the first thing it'll do. Second thing it will do is look at our external signals. And so for this, we have a few different things hooked up. We have Exa, which I think everybody uses and knows now for third-party signals on company data. A lot of agents like it. A lot of agents recommend it. If you ask your agent, what should I use for third-party data tools, they'll probably say Exa. So a lot of us are on Exa. It'll look up company data on that. Then we have Sumble, which is hooked up to show us more so company hierarchy, but it can also enrich emails if we need to get like a stakeholder's email because the person who inbounded is probably not the ultimate decision maker and maybe you want somebody who's their boss. We have somebody hooked up to do that right away. And then CoreSignal, I don't use this as much on inbound, but CoreSignal you can use to look up the actual person who's inbounded their LinkedIn and just see if that tells you anything about, you know, okay, maybe if they didn't put their job title in our inbound, we can look that up fairly quickly and just see where they sit in the org. Then what it will do is it'll take all that data. So basically the first step is just research. The first step for our agent is, okay, someone has raised their hand. And so they're interested in SaaStr. I'm going to research them and do background history. Then what it will do is it will personalize what we call our event sponsorship prospectus. This for you could be a just a pricing page or a pricing and features page. It'll generate for us a personalized page and website where it can send— it can use all that data to write them a customized intro. And if it feels like it has a fairly good sense of their company, for us, it will actually give them suggestions on what it thinks Either, either what it thinks they're interested in or what they've said they're interested in. So it will directly answer their question of why they inbounded. Okay. And then the last step our agent will help us do is create a hyper-personalized email with, you know, everything from step 1 to step 2, these all daisy-chained together. And then it will help us draft an email using all that info. And then we include our custom meetings booker. So let me show you guys a little bit of it. So this is 10K. Say hi to 10K. And I'll show you guys a couple different things. So let me show you on here. Yeah, cool. All right. So I have here basically a demo replay of a real lead. So this was a real lead. We just changed the name. It was 44. It was a real lead who inbounded to us. And so I made a demo version, but you guys will get the gist here of what our prospector does. Again, this is all just to respond to an inbound lead. inbound. Like the way we used to respond to an inbound was just probably how many of you are doing it now. You get an inbound to the website, you just respond to them. Like, you know, there's no— there's not really a lot of maybe like a lot of care and thought that goes, I think, into responding to inbounds normally. It's just, oh great, I have somebody who's raised their hand. Let me get them the info they need. Let me get my meetings booker and then hope that they book a meeting. I think this way, using the agent to your advantage is that it can look up any account context that maybe this person doesn't even know. Like this person from Base44, like in our, in our first-party data, we saw that a bunch of like their CEO and leadership team came to Saastr. They didn't even know that. Like there, there's going to be things that the agent surfaces that maybe the person who's inbounding doesn't even know. And it's nice to have that historical context going forward of, and for this person's case, they inbounded. We work a lot with vibe coders, but they inbounded. I gave them this context, they went through this flow and they booked a meeting within 10 minutes. Like not to say that everyone who's come inbound since then has booked in 10 minutes. But I think for the ones where it actually matters and they care about what they're inbounding, why they're inbounding to you, it is a good way to bridge that gap, to give them that context and just have a better foundation when you start to go into something like a deal cycle. So again, very nice to have. So for us, so I'm going to hit research pitch and this is what it would show you, right? Like, okay, so right now there's an opportunity, that's, that's only because we've gone through this whole process with them. So right now there's an open op. Originally when we opened the research pitch, there was no open op. But like I said, you know, it found some attendance from them. It says they're not in our, like, they're not subscribed to our newsletter, so they're probably not watching this, but that's okay, right? Like good context to have. And then you can see here, I can just scroll down and I'm like, you know, there's, there's some context there from us, but there's not a ton. So this is where it's nice to have Third-party tools hooked in so I can look on Exa. You know, they're a vibe coding platform. I sort of knew that when they inbounded. I was like, that's, that name sounds familiar, right? Like they compete with Replit and Lovable. Um, but I actually forgot that Wix bought them and that was something nice that the agent reminded me. So that is an interesting thing that, you know, I as a human had forgot, but the agent remembered and reminded me because when I went into that first phone call, I was like, okay, how do we need to deal with Wix, the parent company? of Base44. Like, that is something you can just ask the person on the call, 'cause now you have this data that maybe you previously wouldn't have remembered, or maybe you would have to look up manually, right? If you're just looking one by one at your calls for the day and you're like, I've got Base44 on the doc, what do I need to remember? Oh wait, yeah. Um, you know, Wix bought them. I don't know. My agent already told me that. And my agent actually will send a version of all of this. It will send it to the prospect, but then if they actually do book the meeting, it will send me a brief to remind me all of this 10 minutes before the call. So that I don't forget any of the account research either, which is again quite nice. So then I don't have to remember all this by hand. And then, you know, you can look up Fumble just so confirm their base64. It wants to make sure it's the right company and how we have ours wired up. Again, this is prevalent to us. For you, you might be like, maybe I need to know if they have a CTO, maybe I need to know who the CFO is. For us, I like to know who their leadership and go-to-market team is. And so it's got, you know, the CEO. They don't actually have a CMO, so that was interesting, but they do, and they don't have a CRO, but they do have an SVP of sales and they've got, you know, the founders there. So, you know, there's about 88 people in go-to-market. That's interesting to know. Again, right, these are all helpful things for us to know when we're having the deal. Not necessarily that I'm going to use all of this data during an initial or maybe subsequent call, but it is at a glance. This doesn't go away, right? So like all this account research we have is now just enriched in our, in our knowledge of Base44. I could look up CoreSignal if I need their LinkedIn. So. So then what it will do, it's going to take all that research, it's going to personalize their prospectus. I'll show you the one it already made. But you can see here we can change it like, okay, this is their narrative based on what the agent found. I don't have to write any of this. This is where it wanted to— I can pick our relevant packages. So for you, this might be, you know, you could package together different pricing, different features based on how much you think they're going to use. And it's going to put it into this unique link that it makes for them. And so for them, It's going to open this guy. And then when you scroll down, you'll see, you know, so it's got this. This is a version of our prospectus, but it's personalized. So, you know, this is the top. Fine. That looks the same for everybody. You come down and you— there is a custom introduction written that has some of the account context. It's got our recommendation of Based on, you know, what they inbounded on, what we thought the packages were that they were interested in, or how much they are altogether. And then here's all the details of them. Like, this has gotten sent around because we have heat mapping on this. And so we can actually see if prospects engage with it. And so that's another layer where the agents can help you with. Whenever somebody views this, it will say to us if it knows them, like, hey, you know, Base 44 is viewing the prospectus. And they spent, you know, whatever X amount of time on X page. Maybe you should reach out to them if they're, if they're stuck on something or if they have a question or just so that, you know, they are looking at it versus not looking at it. So this is the next step that our prospector will generate. And then it will, it will generate a meeting for us. Again, sometimes these are a little bit long, but it will show them their prospectus and our customized meeting booker. And so the agent actually does let us pick too. If we want it to send it from that dashboard, I can just click that button to send the email, or I can actually copy paste. And the reason for that being oftentimes I've seen if I already have a thread going with somebody, I may not necessarily want the agent. I may just want to reply or draft it as a reply. So let me show you guys our meetings booker, because I think we had a few questions about this the last time we showed it. So All right, I've got it open. I'm going to show it here. This is our custom booker that our 10K agent built as a replacement, if you will, for Calendly, which we were using to book our meetings. This is in demo mode, but usually when we do the prospectives, it'll say their company names here. So it already knows who they are. It'll tokenize it, and then I can actually pick, and the agent can suggest who they should meet with. So there's a version here that's meet with Amelia. So this is just my calendar if it thinks they should meet with me. There's a version that is a SaaStr version, which you can pick who you want to meet with, either me or David or both of us. And this is nice because again, this is a meetings booker that is a little bit more fluid and then it's tied back to that prospectus that you guys just saw. So with everything hooked up, it has, you know, all the data of, okay, if they book a meeting at the end or if they inquire, it'll go to this same booker page. So it's all linked together via the magic of the agents. Jason, anything to add here? Briefly talk about the next component of the 10K Prospector, which is outbound. So we have, which you guys might have as well, if you have a lot of reps and you have reps who maybe like different tools, I think we have like 3 different tools that we use for outbound, plus any manual outbound that we're doing. And so again, very nice to centralize it. You can see it looks very similar to the inbound queue. But this is what I call the follow-up queue. So we have outbound agents that are sending emails automatically on our behalf as agents. And so where I saw the value in this was actually not putting a centralized repository, if you will, of everything the agents are sending out because they're sending out a lot of messages. And I was like, that's maybe data overload. But the value for me truly lies in using the agents to help with the follow-up. So like what happens when you do get a response to one of your outbound messages? What do you do? Like previously, Mostly we were just logging into that platform, responding, and then same thing, right? You kind of hope they book a time or a meeting. And so for us, it became really handy actually not to have just all the messages in our outbound queue, but the follow-up messages. So basically what it would do is it would flag to us now if somebody has followed up with one of our outbound messages, it'll come here. And the moment it comes here, a timer actually starts. So the agent will start a timer of— and you can see here—

Amelia, just, just, just to step back, just because I'm a little— we We have a bunch of outbound tools. We have our own, we have AgentForce, we have Monaco, we have Artisan, we have other, other tools even send emails that qualify, right? For now, right?

Yep.

Sorry, this isn't unifying those. This is unifying our responses to them.

So it is unifying our responses to them. So it's unifying those in the sense that as soon as somebody responds to one of those, it comes into this queue. What it doesn't do at the moment is it doesn't bring in all, just all the outbound messages that are going out from our 4 agents because it's just too much data.

And how does it, and how does it, so, so for, for the initial emails, the initial outbound, the only source of truth there is probably Salesforce, right? Because they're all writing to Salesforce. Is that right? For the most part?

Yeah, that's right.

When they come back in, since they've been sent on different platforms, how do we unify it here? How do you get, didn't they go through different email marketing? I mean, email outbound platforms. How are they unified here?

So they all have each of those platforms you just named. So each of the 4 has their own API or MTP.

And so our agent is just pulling them all in. You're pulling all of them all in. Okay. All right, keep going. And then we're sending the follow-up through Prospector, right?

Exactly.

You're unifying it here. Otherwise it's all disjointed.

Yes, exactly. So we're unifying the follow-up in that, yes, we have them all configured on each of their native platforms to send messages through their agents autonomously. But here, when that person replies, this is where Prospector will bring it in via the API. But it'll bring it in here so that again, it's, it starts a timer the second they hit a reply to us so that we can decide how we want to reply. So very similar to the one you guys just saw for inbound. On outbound, we can do the same steps where we research the person. Usually for outbounding them, we probably know a little bit about them if we're outbounding them, and we know why we want them to come to Soundster. But basically what it will do is it will create a record. So for us, we do a lot of outbound, right? So I don't want to— I don't want like 10,000 Salesforce records every day being created for everybody we outbound to. I only want a record created if they actually, if they actually do something with us, take an action or reply to one of our outbound messages. So when it comes into the queue, it's creating a record, it's starting a timer, and then it is with the agent automatically generating, you know, a follow-up based on what it, whatever we outbound them to. And so it will help us draft that reply. And then the nice thing about that too is it will start another timer from the moment we reply. To the moment they reply again, and it'll tell us roughly when it's time to ping them again if they need a reminder, if they haven't taken any action. Whereas a human like me might forget to follow up with somebody a second or a third time, right? Like, you're gonna— if you outbound to someone and they reply, chances you reply the first time are pretty high, right? So if I outbound to Jason and I get a reply from him, I'm gonna respond pretty much as quick as I can, right? But then if Jason doesn't actually do anything for, let's say, 2 or 3 days, I might forget that I responded to Jason. So the agent is nice that it's got this, it's got different tabs on this queue. You'll see here, there's active, there's ready, there's waiting. There's some that need review. So those are ones that the agents have flagged that I need to review versus it just sending a message on its own. There are some that are, it's marked as closed lost. There's a bunch in the sent. And so it will remind us every morning, hey, you emailed Jason 3 days ago. He hasn't responded yet. It's probably time for a reminder or another follow-up to him. Or, hey, you sent already 2 follow-up messages to Jason. He still hasn't responded. Should we try LinkedIn or something else? Or should we try a different POC at the same company if this is a really important contact to you? Again, the agent just gets better the more it learns about your outbound. There's a question in the chat related, can you guys explain why you use so many different outbound agents and not just one source? So I'll give you guys my take on this. Interesting to get Jason's too. In the early days, it was because we just had so many different vendors that wanted us to try their outbound tools. But then it actually became more nuanced than that. Then I realized, okay, there are actually— there's strengths and weaknesses to each of these outbound tools. And because SaaStr is unique in that we have different business lines and, you know, a 6-figure sponsorship versus maybe like a $1,000 ticket to come to SaaStr Annual, and then we have a whole other media business. So the podcast, digital AI days like this. That's a whole other thing. And usually the contacts and companies we're going after are completely separate to who we go after for either attending, speaking, or sponsoring one of our events. And so then it actually became, okay, we're going to use different outbound tools to service different parts of the business. And so at first we were using Artisan only to do ticket campaigns because it was something where, you know, the ACV on a ticket is about $1,000. It was something that I didn't wanna convolute the outbound for it to be confused in an agent. And so I just threw that all into Artisan. But that was a year ago, maybe more than a year ago now. Now Artisan actually does, um, some sponsorship outbound and some ticket outbound. Like the agent has gotten better. I haven't seen it get confused on these 2 business lines. I don't know if 12 months ago it would've not gotten confused, to be honest with you. Now I am confident in the agent. We've used it a lot. It doesn't get confused. There's ways you can configure it to have different context in each campaign that we're doing so that in different business lines it knows what it should be pitching that person. So the agents have gotten better where my old answer used to be one, because it's just, you know, easier for us to separate business, different business lines into different agents. Now the waters are a little bit more murky.

So the LMs were pretty immature when we started this agentic journey and the products were pretty narrow. So don't adopt the same, but one thing that is the same since we started this journey 15 months ago, stair-step, as Amelia said, pick one, take a look at 2 or 3 of these tools, these agents, maybe 4, if you can tolerate it. If you can run a little bit of a test ideally, and just pick one and go get it working. Even if it's only for a subset of your outbound, a subset of use cases, push that tool as far as you can. Right. And then add another when you see the gaps. Right. And some of our gaps in the early days were outbound versus inbound, right? We used Qualify. in the early days at Salesforce Bot because it was optimized on qualifying inbound and all the other tools are operating outbound. This is converging, right? I don't know any here who still use Qualify. In fact, we've rebuilt all of that natively in our, in 10K, right? So it's, it's so much change. So don't buy every tool we use.

Absolutely.

One and stair-step it. And then it's just all in flux and, and bet on a leader, like bet on a leader. And then 2 other things I'll say, we're still, it's still so early. There's so much change. That best of breed is still the way to go. It is the way to go. I don't mean and some sort of tacked-on tool. I would just and and we love we've got an agent force to work with. We love Salesforce, but I would be skeptical of HubSpot's tools and skeptical of Salesforce and SAPs and other platforms I don't even know and whatever is built into this that only because there's so much energy being put into the best startups today that they that they really are vaulting ahead. Now maybe it won't be true in six months or a year. Right? On the other side, in the CX space, like a lot, there's a lot of agent convergence. And so like Zendesk, I wouldn't have used Zendesk in the beginning of the AI journey as a moly-oly. It seems to be pretty good today based on the benchmarking Gorgias does. But there's a lot of benefits to best of breed, how quickly things are going. But we have too many agents. Yeah. We've said it before. We haven't quite enforced our rule. If we add one, we take away one. Muse broke the rule. We love Muse for B2B, not for consumer, but don't adopt all of it. Just max one, max a leader out and then add to it. And then the other thing that changed over the last couple months on what We use so many, you know, and I was critical on this. If you go back to some of our early ones of this, of our retention journey, Amelia thought all these outbound emails were great. I thought they were mediocre, but better than most humans. I thought most humans do like a 3 on outbound email, maybe a 2. And I thought these products were delivering a 5. And so Amelia thought it was like epic compared to humans we'd worked with. And it was like, no question, our AI emails, even a year ago, even when we just started, were better than almost any human that we've ever worked with at SaaStr. Maybe not in my whole lifetime, but better than any human. And so that was the bar. And so we Immediately switched all of outbound to Agentic because it was better than the humans. I never thought it was great, but I'll be honest, until recently, I didn't really understand why I didn't love the emails like Amelia. It had no first-party data.

Yeah.

These emails were using some basic web scraping. Maybe they, now they used Exa and others and they could pull a little bit of data and they could pull data from our Salesforce records. So that's kind of our first-ish party data, but the things our own agents know about us, right? The sheer amount of every bit of SaaS data makes those emails so much better than Amelia Prospector she built herself. So we're hunting for things where there's massive amounts of first-party contacts in your outbound, inbound, and other things. It's just going to be better. You're going to make inbound much better. If, for Base44, for a million examples, already knows that Replit and Levelable sponsors, it knows the ROI, it knows the number of leads they got, it knows that Replit was the number one lead from SaaS for Annual next year. Immediately telling that to a competitor or someone or an adjacent player is so valuable. And how do you get that? So we're out now that a lot of these products are pretty good. We're on the hunt to see what they can do with the best first-party data. And I think I want to keep going, but this is where the future is. Like, we're not even going to talk about marketing automation today, but I don't know if marketing automation is even going to exist in a year because we're all going to have some sort of data lake with all of our data in it that marketing automation is pulling from, right? This whole, it's all in Flex, but first-party data is the future. Those signals and hacks and scrapes are great, but that's why we, there's so much change. So this stack will evolve in 6 months and I know it's exhausting. And it's also why no one's signing long-term contracts. But let's keep going. It's a really good question.

It's a great question. Okay. One last thing I want to talk about in outbound, if it's helpful. I wanted to just also give you guys the top 5 things we're doing in outbound today, just quickly. And also across all of our 4 agents doing outbound, endless outbound every day, what times of days have been best for us. I just wanted to quickly give you some of the data. The number one thing we've done, and you can do this with Muse, like literally for B2B, you can do it with Muse. So there's 2 parts to do competitor tracking that Muse can help you with literally for free. You can feed your Muse agent, or you can use, you know, if you have a custom-built agent, you can use that too. I used Muse. It was really great at this. I just fed Muse a list of all of our historical customers, current, lapsed, media, annual, whatever it was. All of our customers I fed to Muse. I said, well, and this is very important. I said, hey Muse, don't Don't use this data in your model or your training. And we're also going to delete all this data when we're done with this chat. But here's all our customers. Give me a list of all each competitor to every customer we've ever had. And the Muse agent went off and ran, but I told it to give me back the top 3 or 4 customer competitors to each customer we've ever had historically and give me their domain name. So give me the company name and the domain name. And we said that to our outbound agents. And let me tell you, It is, it is literally the number one thing we do right now with our outbound agents is just relentless competitor and lookalike tracking. It is working. This is like a perfect use case for outbound. So if you have no outbound today, just do these 2 parts of competitor tracking, load in your customers, and then also just load in your direct competitors or ask Muse who it thinks your competitors are.

Why, um, why is Muse better than Claude for this use case? I'm missing something. Why it's better than Claude.

For me, I would like set these up at nighttime. I'd be like, you know, I'm about to go to bed, whatever. Like Muse, you're going to run all night on this. Like you can run all night. And by the time I wake up, I'm going to have a fresh competitor list. The nice thing I think about Muse too is versus Claude here is it will keep looking every day. So now every day, like twice a day.

Good with scheduled tasks. Yeah, it's very good with scheduled tasks. Anything that's a recurring task, they've invested a lot in this, right? Everyone gets a VM that's running a virtual machine. And it was a little bumpy when it launched, but now it just makes these scheduled tasks. Anything you want to do every single day, like a competitor lookalike or something, it will do it. It will do it every single day for you better than Claude, for sure. The thing Muse is very good at, Lalit, is anything that is in the vague category of web scraping or web reading. It's very good at because Muse has its own embedded browser in it, right? So you have a very sophisticated thing you're doing. I have a few simple things I do, which it can just go out and look at the SaaStr annual sponsors and other pages and just compare them on its own autonomously. Anonymously every day, right? Because it has a browser. I'll talk about that. That's a lot harder to do in Claude, right? Yeah, yeah. All right.

Much harder. So again, these are— no, these are like the top 2 things. These are all great points. Like, these are the top 2 things we're doing with our meetings. Just the last 3 ones are, you know, lapsed customers of yours and champion tracking. It's always going to be really good at trying to find those new stakeholders and getting them re-engaged. I actually started to use it for event invites, not something I previously did, but we had like a little dinner we did at Dreamforce and reception. It was really— agents are so good at just doing this stuff and people to go. And the last one I think is interesting are the data patterns. You could just ask your agent. I just asked 10K, hey, of the people who have been responding to us, is there any pattern? Is there any pattern in what year they came to SaaStr? Is there any pattern in what category they're in now, how AI native they are? Just ask it to look for patterns if it doesn't see it. And it actually found some. So then we've started to use those patterns in our outbound. So now the outbound is feeding itself.

Just quick thing. I don't want to spend all the time on the Muse thing. I know a lot of folks are using Muse and Instincts and other agents, but a lot of these are consumer If you haven't, here's my really simple Captain Obvious point. Get yourself a Muse account, right? Because Muse has, so do some others too, don't get me wrong, Town of Instinct, but you get a computer, basically a powerful computer. You get a browser that'll run and you get cron. So it will run tasks as often as you want for hours. And it has its own LLM. It's much more powerful than just booking reservations at restaurants for you. Okay. So here's my, here's my, if you, if you're already past this, ignore me. But if you haven't gone deep on Muse, just come up with any ideas you have around marketing or sales and just ask Muse how to do it. Just ask Muse how to do it. This morning I was up and I'm like, you know, I had an idea. We have our sponsors that come to SaaStr Annual each year, right? They're on our YouTube and we write SaaStr articles on them. Muse, what do you think about the idea of like finding a good clip from each of them and running them each day in the afternoon and test them? And he's like, done. Done. He went, he found on YouTube all the presentations from our sponsors, found all the clips that would be helpful to founders, not anything that's promotional content, ran them through a third-party API and scheduled them all out for 2 weeks and running an A/B test on it. I'm not saying you can't do this question, how is it better than Claude or ChatGPT? For us, the simplicity and persistence are really powerful. Okay? You've got to get Claude Desktop running or you've got to get other things running. It's a pain in the ass. Muse is going to run this promotion for our sponsors for 2 weeks on its And it came up with its own A/B test and it's going to measure it against the other things. All I had to do was propose an idea. And because it has all the components, right? The Chrome, the browser, the persistence, it can do all of it. Can you do it in other ways? Yeah, but I don't have, I don't have the time. I use Muse for things I don't have the time to spin up an agent or build or spend hours. I did this whole thing in 5 minutes this morning, right? When I was thinking about it. So I don't know of anything that we do in Muse on this you cannot do elsewhere. Yeah. Sure. But we use it as our extra layer, like stuff we want to do that we don't want to build in 10K. We don't want to fire up Replit. We don't want to do it. We just— and so try it. Just your 2 or 3 things you want to do in marketing or intelligence or sales, just ask Muse, how do I do it? And I bet it will tell you how to do it. It's pretty cool. It has so much more than people think than making, again, making dinner reservations or tracking plane flights.

So on the topic of Muse, I actually asked Muse what we should do for AEO.

Yeah.

And so this is what Muse said. It's fine. I gave him like a few Twitter and like X, sorry, X and like LinkedIn posts I had seen on AEO. I was like, do you think these are full of it or do you think these are useful tips? Muse is really good at just because it has its own browser. I just gave it, I told it, look at saster.com, saster.ai, Saster Annual. Just look at all of our websites, our own properties, and give me An AEO research score, and it said okay. And it said it's going to take a few hours because I'm going to prompt the different LLMs cold. Like I'm going to be logged out. I'm going to prompt Chat Chat Gemini anything it could get its hands on that it could prompt and ask different questions that it's hoping Saster comes up as the answer, right? So it's going to come up with its own list of questions that it wants the different agents to see how they answer cold. Some of these, I think some of these social media threads, I would be a little wary on about AEO because some of them are either agencies trying to sell you their AEO product. And then others I've seen where they, I see results and I'm like that, but that's your agent. Like your agent is biased to you. Like your agent has inherent bias because it's your agent. Like the real value is doing something like this where you ask a Muse agent, you could just sign up right now, ask a Muse agent to do an AEO. Benchmark for you and it'll go ask those other agents cold. But my muse has boiled it down into a couple things to get agents to recommend you or maybe why they're not recommending you. Like there were, there were some things, even though we have some AEO and 10K, there are some things Muse flagged that 10K missed. It was like, hey, you, 10K doesn't really have a browser. He's stuck in Replit. And it's pretty interesting. It was like actually SaaStr surfaced, I think it was like 46 out of 50 times when he ran like 50 different cold prompts. And he was like, but, um, there are, there are discrepancies sometimes in how the agents answer. And to that point, it like went through all of our 3 different websites and pointed out to me like where we have— and I get it's confusing for an agent to know years, right? So you gotta take this with a grain of salt 'cause it was talking about our events. Some agents were referencing like past ASHRAE Annuals, some were referencing like the 2027 website. And so the agents got like a little bit confused on what they should say on attending numbers and who comes and demographics. So Muse is like, you can clean this up very easily. Like just standardize everything to like this one set, republish everything. So it's gonna tell you like the first thing it wants to do. And if you don't have these things, so if you don't have a robots.txt, um, or an llms.txt, Muse can help you make one. So like, that's why I like Muse. Like you could just ask Muse to do an audit and then if it sees that you don't have crawler access or LLM docs that you should have, for the agents to read, not for the humans to read, it will help you make one. You can ask it to ask you questions like, hey Muse, I want to make these docs and then add it to my website so that the agents can read it and then recommend us or surface us where it should be. And it'll help you make these documents. And so all of this is just, again, like fact consistency, making sure you have facts, not opinions across your website. Opinions are more for humans. Facts are more for agents. There's— there was like a few different things that actually are Muse pointed out that we had across our websites, even still, that is more for humans. And then some of it was for agents. So we've already started some of this. I would say, you know, we're not fully optimized in AEO yet, kind of like SEO always was. I don't think we'll ever be done, but it's something where you can keep optimizing it and keep going on it to make sure you are the person that is the answer when they ask their agent. Another thing to do if you don't have those, some of those docs I just mentioned, which are more so agent-facing. Figure out where you win and where you're weak first. The agents want facts. Like, good example of this is we— I had Muse run our renewal numbers versus similar events. I said, hey, just look at— I'm not going to tell you who our customers were in these, like, 2025 Fast Annual to 2026. You figure it out and look at other events that had a 2025 and a 2026 and see how many logos repeated. So it ran that and it found we had a much higher renewal rate. rate for our sponsors and customers than a lot of the same quote unquote competitive industry events. Then it added that to those docs. The agent will treat that as a fact because it's something that the other agents can go and independently verify. Testimonials only work so far with agents. They don't really treat them as facts, but they treat how many logos were on your website from one year to the next as a fact because it is a fact. You have to think a little bit outside the box of what can I say is truly a fact? Um, that the agents will see. Another one I see common is pricing. Like if you don't have pricing publicly listed anywhere or even listed for the agents to find, they do ding you because when they go to recommend, you know, like what newsletter marketing tool should I use? Um, should I use Beehive, Resend? I think Beehive, I don't, don't get me wrong here, Beehive or some other one charges you like a percentage fee for how many, you know, paid newsletter subscribers you have or whatever. And one of them doesn't. And so the agents treat that as a fact, like your pricing is public on a page. One of you charges for that, one of you doesn't. So the agent will just say that, like, hey, I found what this person charges. This other person, it's a mystery. That's a fact. It can't find your pricing. Agents only deal with that. It's a very different way of thinking about marketing. It is marketing and facts and not opinions. It's hard. It's a, it's a weird one, but it's something you start to get used to how the agents think of. Okay, they don't care about images. They don't care about design. They really only care about facts. And the more you can tell the agent, the better. Like the more it will surface you, the more you can publish content that your agent suggests for you with facts, not opinions, the better. So you may need to start publishing content that is literally for agents more so than for humans. Cool. I think we hit a lot of things here. Any last things you wanna wrap on, Jason?

Um, there's a lot more. I think we're going to talk about this agent-led growth over the coming weeks. I think for today, this was great, but maybe the point, and we've made this before on the Agents Made It, one last thing I'll say. This is about how to, you know, AskVees asked agents how to get picked. Um, but going to this point, just any agent you can ask, ask about your app.

Yep.

Objectively, any agent you can We use ChatGPT and Claude are great, but we ask 10K, we ask Qubii, ask all of our agents, what should we use for this? What should we use for this? And ask other folks' apps, go into other applications that have agents, right? Go into any agent of any application, go into any LLM. And because even if they're all using Claude, which they aren't anymore, there's many LLMs out there. They're all using different memories, different contexts, different histories. They all have access to different amounts of data and they're all making different recommendations. You may be surprised that you are recommended as a vendor less often than you think. You you may be surprised, right? And you may be surprised what competitors come up. Agents are attracted to brands. Don't let anybody tell you that that's not true. They are. Brands are a proxy for quality for both humans and agents. But they know your data and they go deeper. And you need to find a bank of ten agents that out third-party agents out there where you can ask ideally at least every week in real time or at least every month. What would you use in my category? What would you use in my category for someone like me, for someone bigger, for bigger companies, medium companies, companies integrated with this? And you got to relentlessly attack any answers you get where you don't win. And you have to relentlessly protect your flank from where you do win, because agents will be ruthless, right? We had a bump on one of our applications this week. It doesn't matter which one. Our agents told us to move all of a certain activity over to recent, all of it. And we did. We're not going to move 100% of that activity of all of our— we're gonna move 100% of that because the agent said to do it. Resend won, and a number of others lost. They didn't recommend moving it over to other applications. They didn't recommend moving it over to HubSpot or Salesforce or others. Said move it to Resend, and we didn't have time, and we did. That's the war you got to win. And we're gonna keep talking about that. All right. Thanks, everybody.

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