Matt Langie on How AI Memory & Personalization is Transforming Partner Marketing

Partner marketing is entering a new era, and AI is changing much more than workflow efficiency. In this episode, Matt Langie, co-founder and CMO of Personize, explains how AI memory, governance, and personalization are helping partner marketers build always-on programs that learn and improve over time.

Matt shares why traditional nurture campaigns treat people like segments instead of individuals, how persistent AI memory creates compounding improvements across campaigns, and why governance is essential for protecting brand standards while scaling personalization. The conversation explores practical applications for partner marketers, including CRM intelligence, personalized email nurtures, dynamic landing pages, and AI-powered lead qualification that adapts to every buyer.

The result is a look at how AI can move partner marketing beyond automation and toward truly intelligent, personalized go-to-market programs.

Transcript

SPEAKER_00 0:00

Hey, I'm Rick Courier, and this is Never Go to Market Alone. More than a show, it's a community where tech, marketing, and the human connection come together. You're not just a listener, you're a GTM friend. And friends don't let friends go to market alone. Let's go. Before I dive into today's episode, I just want to say I'm so excited to see some of you in person this week. We're hosting an exclusive event for tech partner marketers in the Bay Area where we are going to be having a fireside chat with Maisa Fernandez of Palo Alto Networks, and we are going to be talking about partner marketing transformation. We're going to have a private QA with her and then some fun networking just with tech partner marketers in the area. I already have calls from her friends in Austin, Texas, Raleigh, North Carolina, and other areas about hosting similar events in their cities. So if you're interested in joining us in person, head on over to partnervista.co slash newsletter and make sure to join our newsletter to stay up to date on our latest events. Now for today's episode, my guest today is Matt Longe, CMO and co-founder of Personize. Matt and I have actually been working together for a while now, building out the AI layer behind some of the partner marketing programs we run here at Partner Vista. So when I wanted to dig into where AI is actually moving the needle in partner marketing, it was an obvious call to have Matt on the show. Most partner marketing programs start from scratch every quarter. New campaigns, new leads, new content. Every time it feels like we're just reinventing the wheel, picking up where we left off without actually knowing where we left off. The learnings don't compound, the personalization doesn't scale, and the AI tools that are supposed to help, well, they forget everything the moment you actually close the session. In this episode, Matt and I dig into what's actually driving the problem, why memory and governance are the two things most AI implementations get wrong, and what it looks like when you're building a program that generally understands and gets smarter every time you run it. Thanks for listening to today's episode. I hope you enjoy it. Cheers. Hey Matt, how's it going? Rick, good to see you. It's funny. We were just putting we were putting everything on do not disturb and quiet, but I I actually didn't mention to you before we hit record. I'm home alone. Um, I have a sick wife. She's actually at the doctor's, three young kids and a puppy. So, you know, it's like I can't exactly hit the do not disturb on all those things. So we'll just we'll see what happens on the podcast. Yeah. Might have a five-year-old running in here with a puppy peeing all over me. So we'll just see how it goes.

SPEAKER_01 2:32

Okay, well, we'll we'll we'll see how it goes.

SPEAKER_00 2:35

Yeah. But uh it's great, it's great to have you. Why don't you just do a quick introduction of yourself? I I've known you talk to you every week practically, but the audience might not.

SPEAKER_01 2:43

So for a while now. Yeah, sure. No, it's great to be here, uh Rick and appreciate the invite to join. So I'm I'm Matthew Longi, go by Matt. Um, I've uh been in the tech uh space for quite some time. Uh interestingly enough, I came out of grad school, worked for Intel for a few years up in Portland, Oregon. Um so I got a taste of like really large enterprises. And this was under Andy Grove, you know, big, big company growing fast. Uh it was on the you know, cover of Time magazine, that kind of thing. Um, but I was a I kind of at hard as always a software guy for some reason. So I actually worked in a software lab at Intel that was responsible for building and developing 3D algorithms and audio algorithms, a lot of stuff that's probably used in in podcasts uh today. Um and then I was approached uh by a CEO of a video game uh developer that had partnered with Michael Crichton to serve as his uh his VP of marketing. So that was kind of my first taste into uh as we'll get into AI, where we're uh crafting video games based on Michael Crichton's books and movies, uh, one of which was called Timeline. Uh it was wasn't a wasn't one of his bigger movies. Uh it was right after Jurassic Park. So he was kind of uh operating the halo or the glow of that. Um, but one of the things about Crichton was that he was a scientist. He was a he was a doctor by trade at Harvard MD, and he was very, very specific about wanting to know the numbers of marketing. So he would, you know, you know, basically I had to do marketing reporting without the marketing tools we take for granted today. So I was ripping through log file and doing log file analysis and stuff, which then led me to my career where I ultimately ultimately landed at a company called Web Trends, which is one of the founding companies of web analytics. I got uh stolen away, if you will, by Omniture, one of their top competitors, ended up at a uh being with Adobe through that acquisition, and then uh been in you know kind of the the SAS and marketing tech space for that that whole duration. So it's been a it's been a fun ride. Um and then I came into the this now AI space with Persenize uh with my co-founder uh because the things we're doing that we can get into. But um yeah, it the world's changing yet again. And so, you know, the only the only constant is change, that's for sure.

SPEAKER_00 4:52

So a lot of a lot of software background there. What you know, but now you're the CMO and co-founder of Personize. So what was the like transition into the marketing world and and what is what really stuck for you on the marketing side?

SPEAKER_01 5:04

Sure, sure. Well, I uh I have an undergrad uh in marketing uh business uh uh BBA from Notre Dame. I've got my got my MBA focused on marketing in tech uh from uh UT Austin. Um I've just been in I've been kind of all always around software. I you know I was one of these geek kids that had a computer in my basement and I was you know programming basic and Fortran and stuff and making video games and music sound uh programs, things like that. Um, but I always I was never like the engineering nerd, so to speak. I was always the more the marketing nerd or the business nerd or the entrepreneur nerd in the sense that I was like, hey, how do we how do we find a way to sell this? So I was always trying to find ways of like how do we take this stuff that we're building with technology and find ways of of marketing and selling. And so I just kind of naturally fell into uh the marketing space. I I love working with marketers. I was proud to say when I was working uh at Omniture and then Adobe, uh I was a marketer who was marketing marketing software to marketers. So it was about as a pure play uh job as I could have. Um and it was fun. You know, uh Omniture was growing fast. Uh, we went from $120 million in revenue when I joined the company. I left Adobe seven and a half, almost eight years later at 1.3 billion. Um worked with some of the most brilliant marketers uh in in SaaS and in tech. I mean, just everywhere you turned it at Omniture and Adobe. We just had great people. Everyone is really smart, worked really hard. Uh, Omnisure was known as a kind of work hard, play hard culture uh in Utah. Great experience uh with that that organization and the and the team that we had there. And and really it was just a a way of getting uh our hands dirty with um really understanding what the where the market was going, what the customers needed, how marketing technology was changing. You know, when we started, when I started at Web Trends and then at Omnature, um, you know, those charts that show all the logos on the on the screen. It was there's like 12 companies in web analytics and Mark Martech. You know, Martech wasn't even a word at the time. And all of a sudden, you know, Marquetto pops up and and all these companies start popping up. Next thing you know, there's like a hundred thousand logos on on the uh on the graphic. Um so it was fun being uh part of the kind of the journey early days. Um, but you know, you learn a lot of things that I think you know are true now. And you know, it's kind of like it's history repeats itself, you know, if it doesn't repeat itself, it's like a what is it? It's a history rhymes. Um so it's me, it's not the same play, but a lot of stuff that we're seeing with AI, and you know, I I'm on LinkedIn uh a lot more now. Um a lot of the same things that people are talking about today. We were talking about, you know, 15, 20 years ago uh in the early Martec days. So um I'd say the problems are the same, but they're they're different in in many ways. Um, but it's uh it's I think the question for us as marketers is okay, how do I leverage or use this technology to solve the problems I have from my business so I can reach my customer, better serve them, create better experiences. And that's where I think AI is really, really exciting.

SPEAKER_00 7:58

What do you from your perspective, what are you seeing that's kind of the same from then? And then you know, what's different this time around?

SPEAKER_01 8:06

Yeah, I'd say um it's a lot of the same, you know, same principles of business. You know, who's my customer? Um, how do I find them? How do I reach them? How do I know they're they're actively buying or not buying? Um, I'd say today the data's a lot better. You know, we have, you know, back in the day in 2008, you know, intent signals or intent signals that wasn't a thing quite yet. Um, so a lot of it was, you know, cold email. Uh, but I'd say a lot of the the channels are still the same. We still communicate via email. And you and I were just emailing minutes ago to get set up for this this podcast. Um, text. So I think that the channels may change slightly, um, whether it's a direct message or an email or or an advertisement. I think some of the uh so the principles I think are uh ultimately uh more or less universal. What's changing the though is the capability of how we can uh reach out to customers and in what way. And that led to uh my working with my co-founder years ago when he first started um working on personalization technology. So that's in the in the name of our business, personize. And this is back in 2020 when we first started working together six years ago. Uh he was the first guy to, his name's Hamed Tahiri. He was the first guy to introduce me to ChatGPT. He was the first guy to say the word. I was like, what is ChatGPT? And he was getting at all the technology about AI, and this is like version two, I think, of ChatGPT. So it was very, very early. Um, and I was kind of like, yeah, whatever, you know, new technology. Um, and then uh I was running my uh marketing agency at the time, uh working with some clients, and then we brought uh a very early version of Personize into some of my clients, and then what we saw in the way you can do personalization was dramatic. As in, we could learn all about the customer, and we can talk about this, Rick, with what we're doing with uh with partner Vista and your customers. But this idea of taking a whole lot of data and bringing it all that together and synthesizing that, basically getting the right context. And we'll we'll talk about that a lot here, I'm sure, on as we get into AI. Um, knowing it's John Smith at XYZ Corp, who is the decision maker, and he works with Mary Jones, also at XYZ Corp, and she's in finance and she's the champion, and he may be the blocker. All those things can now really be learned and discerned and acted upon in in a much more uh cost-effective way, uh much more efficient way than we could, you know, five years ago, 10 years ago, certainly. So I think AI has given us the ability to accelerate things very fast. Um, one of the funny things I read the uh a few months ago, I guess, is that um AI made good things better, it made bad things worse, and it made mediocre things faster. So this idea of, you know, use AI where it makes sense. Um and I, you know, I'm sure a lot of your audience would say, yeah, I love AI for this, but I also hate it for that. And I'm in the we're in the same boat at personize. We're an AI for company. We do a lot of things with AI. There's a lot of things I hate about AI as well. Um, I can spot, you know, clawed code uh websites a mile away. I can spot uh, you know, if it's not this, it's that. You know, that that that phrasing that you see everywhere. Of course, I've programmed personize our memory and my claw agents to never talk like AI, at least try not to. Um but yeah, AI is great. You know, we can do a lot with it as marketers, but um, it's a tool. And not everything, you know, if you've got the hammer, not everything's a nail. So use the tool in the right way if you're doing a job.

SPEAKER_00 11:30

Now let's let's go a little bit deeper in that because I know a lot of the, especially a lot of the partner marketers I'm talking to, you know, a lot of them are heavy AI users and kind of uh what I would call um uh you know, workflow proficiencies. So helping them just do their job faster, but not as much in terms of actual program setup and execution for how they're going to market with their partners and and how AI is actually helping them from a targeting perspective, a personalization perspective, a program delivery perspective. So, you know, what are you seeing work well in terms of integrating AI to help actually marketing outcomes as opposed to just helping me be a faster, better marketer?

SPEAKER_01 12:09

Yeah. Yeah, I'd say, you know, so AI is great for how do I do these steps, this workflow much faster. So uh one of the things that we learned is that it would uh so we uh at personalized, we integrate very heavily uh and directly into HubSpot and Salesforce and all the tools. Um, because what you really, what you're really looking for as a marketer is, and you'll hear this word a lot in AI, is context. So, what is the context related to um, and I know partner marketing, we talk a lot about leads. It's like lead delivery and and lead management, and and I've got this bucket of leads I need to get to the partner and have the uh executed on behalf of the partner. I would dare say that partner marketing is is going to change dramatically with AI because now those leads are all they're all humans, they're all they're all people, they're all contacts at a at a company. And the ability for AI to learn everything it can about those leads, those contacts, and then deliver a personalized experience so it's not a one size fits all. And that's you know, that's how Rick, how you you know that we're working with with Partner Vista, is that uh we can do uh uh lead intelligence or contact intelligence. So leveraging AI agents as we have with with personize, going out and finding everything we want to know about Mary Jones, who's that CFO champion uh at you know at the company, um, or anyone else on the team for that matter. Every, you know, we all have a very public footprint for the most part. There's a lot that the AI agents and and technology can learn about all of us as individuals. And the whole idea is how can we deliver a much better experience? So it's not a one-size-fits-all partner marketing program that we're just trying to check a box for, yep, we delivered these programs for these leads, and this is what happened. Now there's a whole lot uh more we can do in delivering uh a much better experience. For example, personalized emails. Now I know there's a lot of people that have received AI emails, and a lot of times we can spot that because it's just it's kind of cold email spam at a much higher volume. Uh, I've received those. I know you've received those as well. That's not, that's not what I'm talking about. What I'm talking about is a very um, I would almost say it's it's uh handcrafted or it's um composed in a way that it's meaningful and it's it's highly personalized based on everything we know about that particular contact. Then take it a step further. It's like, okay, they receive that landing, they receive that email. Where do they go? Well, they can go to a landing page. I would contend that the web is changing in a very, you know, and websites are going to change in a very dramatic way in the sense that think about a website as just a blank canvas that is then reactive or responsive or personalized to the individual. So no longer does a website need to be one size fits all. It can actually be come here to this website uh from this campaign that I got from this personalized email. And now for Mary Jones, it can speak directly to her, what her issues are, what we know about. She may have spoken publicly uh or posted something or blogged about something or tweeted about something that is meaningful to that experience. Um, and that can be reflected back to her through what is the content that's that's placed on uh on the on the landing page. So I just I look at it as uh as marketers, you know, we can do a lot better. Yes, there's work and there's technology and there's AI and there's a lot of things that we got to stitch together to do that. It's not that hard uh at the end of the day when you get it right. Uh, and it can be very meaningful. And the end result is much better customer experience, much better experience in in these campaigns and much higher conversion rates, and everybody wins.

SPEAKER_00 15:36

Yeah, I know we've leaned into it very heavily just working with you all because nurture's been like a big kind of need and challenge, especially in the partnership go-to-market motion, in terms of like, okay, we're generating leads, but we need to, we need to nurture these leads before they get to sales. You know, and from my point of view, you know, 15 years at IDG, five years at Tech Target, and just working across the industry, nurture's been a very robotic experience. Like, okay, we're gonna create a five email nurture, and every email is gonna say, you know, every email one says the same thing, every email two says the same thing. And then when we talk about personalization, you know, essentially all we're doing is like insert company name, insert industry, right? Oh, yeah, we're personalizing these emails, but all we're doing is just replacing finance with manufacturing versus government. You know, and and so I I ran a I did a webinar with ServiceNow for their partners, kind of just talking about some of these challenges. And the example I gave was, you know, in terms of, you know, the challenges, like we're treating leads as segments. And we're and and the reality, I think you pointed this, is that leads are individuals. Like these are individuals on buying teams with unique challenges, you know, unique priorities. And the example I gave is like if we send an email, email one, right, it goes out to a thousand different people, um, yeah, it might all have the same call to action, but you know, we know that this email is going to John Smith, who works at Children's Hospital. We know Children's Hospital has a brand new CIO. We know the CIO is making public announcements about um, you know, patient experience and how they're investing in digital transformation to drive patient experience. And we know that they're hiring for XYZ jobs, you know, maybe related to AI workflow automation as part of that digital transformation. You know, we know what they're posting about on LinkedIn. We're gonna use all this information to personalize that email to John Smith to say, hey, John, we know how important patient experience is for you and how AI workflow automation can help drive that forward.

unknown 17:27

Right.

SPEAKER_00 17:27

And that might be totally different than email number two, you know, that goes out to Jane Smith, who's at a manufacturing company that's, you know, investing in something different. So it's, I think just that the big takeaway here is like, why aren't we treating individuals as individuals and not as segments? And I think, you know, there's a lot of tools out there like yours that that can help us do that in real time, bringing AI into these programs, you know, without having to nest, you know, from our point of view, without having to, you know, invest in a platform. So I think that's always kind of like the the big thing for a lot of marketers out there is like, well, look, it's just, you know, do I have to invest in another platform to do this? You know, and for us, it's like, well, we just baked it into our workflow on a cost per lead basis. So I think just trying to keep it simple and easy is is kind of the key.

SPEAKER_01 18:09

Yeah. Well, and and and Rick, what you're speaking to is this goes back, we were talking about this back in the, I think it was even in grad school. There's uh uh some notable authors, uh, Peppers and Rogers, you know, one-to-one personalization, one-to-one marketing, some of those ideas where, you know, get a 360-degree view of the customer, understanding of the customer, and then you can do true one-to-one personalization. Um, that promise has been one of those kind of, you know, North Star guiding principles that that I've always looked at as a marketer, but it's it's never been achievable. I think we're a lot closer now. Uh, because we can, instead of email one being just a um, you know, cut and paste of a bunch of words that goes to everybody in the same way. Now it's like, well, uh Mary Smith has slightly different uh as the COV of this organization has slightly different uh expectations than um John James over here at ABC Corp. Um they may be in the same industry, you know, they may both both be healthcare uh CFOs, but what they talk about, what's important, what's priority for them, is is different. So I think a lot of it is, and this goes back to this idea of context. The context for what we understand, what AI can understand about Mary is going to be different than what it understands about John. Why wouldn't you then necessarily uh why would you refrain or not use that that new context uh to deliver a better experience for each of them individually at an individual level? You can do that now. And so um, and we we don't call plat uh personalized a tool. We are a a platform in a way that we're kind of the infrastructure. Um one of the things I would I would add though, Rick, is that something that's really difficult for marketers today with AI, and that is AI and AI agents are stateless machines. So it's on or it's off. So the whole idea here is that um the analogy I've been using lately is think of the world's smartest consultant with perfect amnesia, which means every day they show up at your office as that consultant and they've forgotten everything from yesterday and the day before and the last week that they've worked with you. Everything is is it's complete blank. But they have a binder and they're really smart. They're the world's smartest consultant. They can open that binder and go back and refer to things like, oh, yeah, yeah, yeah, we did this thing on on Friday last week. It's now Monday. Uh, let's go do email number two in the nurture or whatever that might be. Uh, as soon as they close that binder and it's the end of the day and they come back on Tuesday, they've forgotten everything again. So, what AI needs to have is a persistent memory. It's something we call unified customer memory. This idea that you need to have memory that that is retained over time. So it's not stateless. It's not your AI agent that understands what it's doing right now, and then as soon as you stop, it forgets everything. So that's and that's important for this personalization. Because if you remember everything about Mary and then there's something new, maybe she just posts a new, makes a new tweet uh or posts on X, or uh maybe there's a new uh 10Q that came out from the company that's very relevant to the finances of the organization. Maybe there's a new round of funding. Something's happened. Some there's some different state for that company. Um, when you have that memory already embedded in your AI operations and that new thing comes in, that's that's new context, it's retained. Uh and the whole idea is you you're no longer dealing with perfect amnesia, you're you're dealing with perfect memory in many ways, where you know and they can infer things like, okay, now is the time to send out the nurture to Mary because they just got a new round of funding. Uh they're fresh or flush with cash. This would be a great time to engage them with this, this offer or whatever the whatever the campaign or the the uh the outreach might be. So I think this idea of um it's some of the challenges with AI has been that that lack of memory. So that's one of the things that that we were dealing with a year ago as we were building apps for AI and found that really you have to you have to solve the plumbing issue first. So if you want to have the the the nice bathrooms and the pretty spigots and everything in your house, you got to have good plumbing. Um So we went back to the drawing board. We we essentially pivoted as a company in what we were building. And uh my co-founder, Hamed and his team uh of engineers, we we went off and kind of threw out the the old playbook and wrote a new one and and found that uh, you know, memory, persistent memory is key. The other part of this is what we call governance, uh, and that is we have to be able to tell the AI what to do and when and and why in many ways, uh, particularly as marketers. So think about brand. Uh, you know, uh brand is uh synchrosanct at uh companies like Adobe and Intel and others that have built very large, successful brands. Uh sacrosanct, I think that's the the the right way to say it. Um the whole idea is that brand is is it's like a fireable offense. If you mess up the brand as a marketer at these companies, you know, say say goodbye. Um so one example I always use is it was and I learned this early on. This is the the late 90s of Intel, it was that the Pentium processor was rolling out. The brand mandate from Intel was you never make this a possessive. It's never Intel's possessive S Pentium processor. It is always the Intel Pentium processor. And if you broke that rule, you got fired. Today, an AI agent could break that rule because it doesn't have governance saying, this is our brand guideline, this is how you speak about our brand to our customers. Um, do not ever violate this. AI agents don't know the difference. Again, it's that, it's that consultant with perfect amnesia. They can't remember not to do those kinds of things. So we've also built that capability into personize. And that's that's I know that's helped with uh the programs that we do together, which is if you're working with large organizations like ServiceNow or Google or um Nvidia or any large brand that's very successful because they've they've they've been consistent and persistent in delivering their brand in the right way into the market. Um, you've got to make sure your AI agents are cognizant of that and are aware of that and behave in the right way. And that's that's the other aspect of AI that that I think we've solved for quite quite well.

SPEAKER_00 23:57

Yeah, I think that's a good takeaway for a lot of marketers out there that are being pushed to do, you know, utilize AI, but at the same time, they might be partnering with a company like Google or AWS that has very strict brand guidelines and how we go to market, you know, and and align to partner, you know, partner co-funding criteria. We'll make sure there's a governance layer later and laid into what they're utilizing AI to help support. But I want to touch on the memory stuff because I think this is huge because you know, working with a lot of partner marketers, I'm always hearing about running always on programs, right? And, you know, I've been running quarterly programs for partner marketers for for decades. And it's always like, well, what learnings can I take that's actionable that I can actually put into my next quarterly program and help it actually do better? And I've seen every wrap up, you know, under the sun, and a lot of them are like, okay, X percent are director level and above, or X percent are in this industry. And, you know, we saw this intense signal as the highest, but not a lot of it is actually something I can take and put into that next program to actually help it perform. And I think what's what's interesting about what you guys are doing with this memory layer is like there's a there's a programmatic layer of taking information and programmatically optimizing programs in real time. So that like, let's say, you know, Mary engaged with something, what can we learn from that? Now someone from her buying team comes into the program two quarters later. Okay, what work, what didn't work with Mary that we can utilize to optimize emails, landing pages, program components in real time, you know, to engage that person. Or if there's another company out there that looks just like that company, how do we utilize that information too? And it's all done at a programmatic layer.

SPEAKER_01 25:32

Yep. Yeah. And that's the thing is I think, again, I think that the two things you have to have is you have to have the memory because that's that's what ties everything together over time. You have to have the governance. So we know not to reach out to Mary when they're about to uh, you know, do their uh end of quarter reporting, you know, then at the beginning of the next quarter, whatever that might be. And then those two things together then enable the ability to do personalization. So again, personalization is it's not the mail merge with a first name, you know, dear insert first name Mary. Um it's genuine intelligence about the account, it's genuine intelligence about that person, the contact. So now as things evolve and you're two quarters in uh to these campaigns and these programs, it's a it's a compounding effect. Think about, you know, we as humans, we get better as we learn things. You know, you think about uh a kid learning to play piano uh as I did, or or guitar as I still do. Um, you know, learning a song, you you figure out the you know the notes and the structure of it, and you just you just keep getting better and better with it because you've memorized how to play the song. Um AI works a lot in the same way when it has that that infrastructure, that memory and that governance saying, this is how you play the note, this is when you you know hit that power cord, whatever song you're playing. And the the whole idea is that these these aren't like separate features. This is all part of a single system. And that's a system that we've uh deployed and and helped you guys with at Partner Vista because it's it's the world's smartest consultant with that perfect amnesia. It doesn't work if the binder only remembers certain things. Uh, it doesn't work if it doesn't follow the rules, it doesn't work if it's assembling something fresh every single time. So it's not like you're having to, you know, um repeat and redo it uh the same things you're doing in the second quarter, the third card. You can compound it and you can learn from it. And so the system itself programmatically will say, hey, we're we're gonna be much better in in the third quarter than we were in the first quarter because of all these things we've learned, all these things we've memorized, that context continues to be additive. It gets uh, and the one of the things that we do is we compress it. So it's super cost effective. One of the things we're really proud of is um we've gotten this to the point where we've been able to save companies up to 88% of the cost of their AI, their token utilization. So think about if you're in Claude and you've got a bunch of AI agents and you're running through a you're a CIO and you're spending $100,000 a month on Claude, we can save almost up to 88% of that cost because it's almost like a zip file. You remember the days of where you'd have to zip things up and hard drives and floppy disks were limited in storage space, you have to zip things up to make things small. It's the same idea. Context can all be kind of zipped up or compressed and then utilized later on by these uh agents to deliver that personalization. So the cool thing is memory actually makes it cheaper uh to operate, makes it more effective. Uh the customers get a better experience. You can deliver a better uh partner marketing experience for uh for your customers, and and it's it's kind of a win-win-win for everyone.

SPEAKER_00 28:26

No, it has been. And it's it's been fun working with you and learning all this because it's, you know, we've been able to integrate this into our partner Vista programs to have always on, you know, pipeline-driven engines, but you know, partner marketers are just still buying leads from us, right? They're not having to figure all this out. It's systematically baked into the programs. The more you leave it on, the better it gets. And it allows partners just to spend more time where they want to spend time. And that's with their partners, right? And thinking about go-to-market strategy and and all the fun stuff and not building programs and taking them down and rebuilding and and doing all that stuff. So we've covered a lot. We've covered personalization, AI, uh, you know, memory, governance. Um, anything else that you think we need to just touch upon before we leave, folks?

SPEAKER_01 29:09

Yeah, no, I'd say uh, you know, first thing I'd recommend is just experiment, play with AI. It's you know, it can be it can be dangerous if you do it wrong. So be careful where you point that weapon, if you will. But uh it's it's it's absolutely changing business, it's changing the economy, it's changing the market. So um I, you know, I I think I I posted something on LinkedIn uh a few months back. It's like you can either be the sheep or the wolf, you know. Uh yeah, it's coming for all of us in in in some ways. Uh, and I say that mostly joking. Some of it can be uh a little scary if you think about it in the context of you know the Terminator movies or or the Matrix movies. But um, all joking aside, I think it can be a very, very powerful uh capability for for any any partner marketing, any marketer in general. Um and there's you know, like anything else, there's there's ways of doing it right. Uh, there's ways of getting it set up right, there's ways of partnering with the right people that that know how it's working in the right way. Uh, you know, we love to partner with our customers as we partner with you, Rick, and and your team. So um it's you know, we're all learning together. Uh there's I don't think there's any true experts on AI, AI if you look at it in the context of uh, you know, 10,000 hours spent uh, you know, really delving into how exactly AI works. Um But uh I I think there's a lot of us that have been doing it you know a long time and and we know kind of what to do and what not to do. Um but yeah, we're here to help. Uh we're here to uh you know work with anyone. One of the things that uh that we just uh launched uh this week is uh something we call CRM AI operators. So we're now helping our customers at no cost. It's it's open source, it's an MIT uh free uh license where our customers and and just people want to check it out can go to our our website at personize CRM AI operators, they can check that out. Um and uh download and get it installed. It's a it's a GitHub repo. It's I won't get in all the the tech stuff behind it, but it's really easy to kind of get it set up and test it out. And it'll do things like what we do for per uh for Partner Vista with Persenize. Um, you know, it's basically like a CRM operator that's always on, really smart, it's learning, it's got memory, and and it can uh do a lot of cool stuff for your business. So uh encourage people to check that out. But uh and it is always if if folks want to reach out to me, I I'm sure you can put my my email uh up on the uh the podcast here or feel free to share that.

SPEAKER_00 31:24

But uh Yeah, we'll share we'll we'll share your LinkedIn for sure on the on the the show notes. So if people want to reach out, they can connect with you and and yeah, we'll we're gonna be doing more too as we kind of go to market with our own little product launch and how you guys are integrated in this. So we'll have some more educational sessions where we actually talk more about what the product is too and you know be a little more salesy in a webinar as opposed to just the fun stuff here on the podcast. But but Matt, thanks for coming on, man. This was a lot of fun and uh like always, I always learn a little bit more about AI when I talk to you. So I appreciate it.

SPEAKER_01 31:51

Yeah, and likewise. So it's great working with you and the and your team and uh look forward to more conversations.

SPEAKER_00 31:56

Awesome. Thanks, Matt. Okay.

SPEAKER_01 31:59

Bye.

SPEAKER_00 32:00

That's it for this episode of Never Go to Market Alone. If you liked what you heard, subscribe, leave a review, and share it with another GTM friend. For new episodes or to see how we're helping partner marketers succeed, visit partnervista.co because friends don't let friends go to market alone.