#109 - Meghan Keaney Anderson - Head of Marketing, Jasper - Leveraging AI in your GTM

Sales, marketing, RevOps, and customer success. It's sink or swim out there, and yesterday's strategies and tactics won't help you today. This is Revenue Today, and I'm your host, Jared Robin. Join me as we interview top revenue leaders in our community to learn what steps we could take right now to help you scale more effectively. Revenue Today is sponsored by Rev Genius and Rev Room, and we're on a mission to build trusted spaces for curious revenue professionals who are collaborating on the future of B2B GTM. Hey, dear friends, welcome to another episode of Revenue Today. Today I'm joined by a really exceptional woman who is the VP of Marketing at Jasper. Megan Keeney Anderson, welcome.

Hey, thanks so much for having me. I'm psyched to talk for a little bit.

I'm, I'm, I'm, I'm so psyched because as, as a user of Jasper and an avid fan of AI, I'm by far not the only one. It's gonna be good to, to dive in and, and, and just understand some of the inner workings and, and learn from you. So thank you.

Yeah, for sure.

All right, let's, let's come out, uh, you know, GTM as a whole is, is massive, and, and we'll talk about, you know, AI and GTM certainly, but I want to hear from you. You, you've, you've been the VP of Marketing at HubSpot. You're, um, now the VP of Marketing at one of the hottest, fastest growing companies in AI. Debunk a myth about GTM right now.

Yeah. All right. So, here's one that I think is so common. And if you're not doing this, congratulations, but I think most companies are doing this, which is you put all of your emphasis and all of your attention on net new revenue, right? And when asked the question of, what's your expansion play within your customer base? What do you, you know, what's your messaging to your customers? How are you upgrading them? How are you predicting their, you know, future path with your company, you get crickets. And it's because it's like that relationship challenge that people have when they're dating. It's always like, when the other person is, like, fresh and new, they're exciting, but then when they become, like, long-term and a customer, they're sort of forgotten about. And you really need distinct strategies for growth on both ends. I think far too many companies just forget to figure out how to grow within their existing customer base. And that's a much easier place to grow from than finding net new people. So, my, like, hands-down advice whenever people ask is always, like, do not forget about expansion within your customer base, especially for SaaS companies, especially for companies that have, you know, both horizontal kind of expansion opportunity and then vertical, where you can go up to a different tier, but you can also add things like seats or add-ons. So much opportunity within that existing customer base and they already like you.

Why do you think the focus is net new? Because isn't a dollar worth a dollar? And you could, you can, you can make a very easy argument that a dollar you have is more profitable than a dollar to get.

I think because new logos are exciting to people. I think people care a lot about new logo counts on their company and how big, you know, How many customers do they have and what's the latest success story? And, you know, what company did they just land that they wouldn't have been able to land 6 months ago? New buyers are just interesting, right? But it's really in your existing customer base where a lot of your growth and loyalty and fuel can come from.

Yeah. It's not just adding a CS department, right?

Right. Yeah. No, I mean, we, that's actually, that is, you nailed it. That is what people get wrong. They gear, they're like, marketing is geared towards new business, and we'll figure out upgrades out of our CS team, right? In our, in our standard conversations, we'll see if people are ready to upgrade, and we won't give them any marketing support, but, you know, they'll do it all through conversation. And, and customer success. extraordinary people, extraordinary team, think about how much better they could be if they had a marketing arm, you know, attached to them. And so, that's really what happens is marketing leaders, they wait until they're, you know, Series B, Series C, like much later stage to add in a customer marketing function. And frankly, like, we did this too at Jasper, you know, it was not among our first hires. Thankfully, we do have a, you know, customer marketing leader now. But it's, it should be earlier, I think, in your hiring. As soon as your customer base gets robust enough to be able to, you know, be a revenue driver for you, you should have the strategy to match it.

Yeah. Mark Roberge, I interviewed him and he said something very interesting, and I'll bring the old HubSpot references. I'm sure he's wonderful. really smart. You know, he was talking about CS, and now that we're on the NRR part of it, as success there or lack of churn being a function of the AEs that brought the deal on. Yeah. And how he compensated AEs specifically the second deal even more than the first. I guess the question is like, how do you see all the departments working interchangeably to like prioritize this?

Yeah, yeah. Actually, I remember Marc Roberge when he was at HubSpot, his, his sales team, they used to get clawbacks if you take kind of the incentive and the compensation away if the customer that was sold didn't last a certain amount of time. Right? And then, it sounds like he's also recommending, like, adding in an additional reward if not only does a customer stick around, but they stick around and expand and upgrade, which makes all the sense in the world. I mean, I think that we think what you wanna fight inside a go-to-market motion is just the natural instinct for every individual division to only solve for itself. Right? They solve for the nearest goal that it has. So, marketing, I'm gonna solve for getting leads, I'm gonna solve for getting signups. That is my goal, that's my domain, I'm gonna stick in my lane, right? And it kind of doesn't matter what leads, as long as I get the number. And then, once I get the number, I'm gonna hand it over to sales, and they carry it on. There's a natural impulse of, like, just thinking in those boxes, and sales thinking, like, I just gotta close a deal, gotta close a deal, you know? And then, CS, poor CS at the end of the road, having to deal with the bad leads that marketing brought in, and the bad deals that sales closed. And now having to nurture this customer and fight against churn, you know, carry the bag basically for the rest of the teams. That happens not because people are bad people or because they're selfish or they don't think about their colleagues. It happens because the incentive structure that we've set up and the goals that we have set up are very much tied within the division. So, If you can do as Robert just said, and certainly give your team, you know, its primary goal, which is in your own function that you can fully control, but have a kicker goal, like a secondary goal that expands into the longer lifecycle of the customer, that's worth having. And that will bring— that will create a team that works better together. Because if you're in sales, you want to make sure that your CS counterpart is fully set up to give that customer the best possible onboarding, because if they don't, your numbers get hit. So, I think that's just a natural thing that most go-to-market teams have to fight against. And you can fight against it culturally, in that you make sure that your leaders are spending a lot of time together, and that your teams are talking. You can fight against it structurally, in terms of, hey, you embed everybody together in the same meetings. Or you can do it in terms of the incentive model. And I think that's a nice triad to try to hit.

Yeah. And in my head, the KPIs was the biggest thing and being incentivized thereof. I'm curious what you all do from a KPI standpoint to encourage and double down on, you know, this fact.

Yeah. So, for starters, everybody's goals ladder up. To revenue. Now, that revenue can come in many different formats, as I was saying. It can come in the expansion from the customer base, it can come in net new business, it can come in reductions to churn. But, like, everyone's goals will ladder up to that ARR number, right? Or it's actually, and, like, not just ARR brought in, but, like, net. And so, That helps give you the framework, and then you can kind of boil that down to, okay, you know, Angelica, on lead generation, your job is to generate this many sales qualified leads, because we know that this many sales qualified leads will turn into this many deals, will turn into this much revenue. That's how you contribute to that. Then you can go to your content team and say, hey, your job is to get this much traffic, because we know this much traffic converts into this many leads, et cetera. So, I think it's a matter of giving everyone their own goals to own and their own KPIs, but making sure that there's a hinge that those KPIs hang on where they're all connected and, you know, driving at the same bigger thing.

I love that. It's so important. And we're all motivated by money, but also our goals. And yeah, so It's essential. Now, question that I've been hearing in some leadership conversations I've had, AI is a new thing. It's not a new thing. It's, it's, it's, it's a new thing to be accountable for, I should say.

Yeah.

And, you know, folks' boards are saying like, how are you leveraging AI in your go-to-market strategy? Give them an answer once and for all that they could write down and go for it.

Yeah. So, I think the answer is not like, oh, we're trying a bunch of different tools. I think the answer is, you know, go-to-market leaders need to take a look at their strategies and, you know, the way that they work as a team, and find the places in that workflow that are the heaviest, right, that create the greatest amount of friction. And develop, like, a pilot use case for your team where AI could help, right? So, for some people, that may be, wow, we've got to get up 100 web pages on our entire, like, integration community. AI can help there. For some people, it may be, we want to write, you know, 5 blog posts a week, and we've got a team of 2. It could be sales emails. But find that specific use case first. And then figure out what are the right AI tools to help get that done. And do that proof of concept with that use case, so then you can go back to your board and say, yeah, you know, we decided that we're going to use AI for the purposes of repackaging our blog posts into ebooks and social content and making distribution better for our campaigns. And so, we ran a pilot. We got this result, we saw this amount in terms of time reduction, we saw the same or better results in terms of downloads and interaction with that content, et cetera. But always start with the strategy and not the technology. You don't just like plug in AI and hope things will be better. You got to be intentional about how you use it.

It's like using ChatGPT-4. asking them to come up with an original piece of content. Really good with the past, but you need to learn a bit more about it. Now, it feels like that's like a pretty sound strategy, but from an enterprise perspective, like 1,000+ employees, they really wanna move the needle in a massive way with AI. And understood that the content is not a massive needle, but like what other— What are some other use cases Are there some examples that you've seen at that enterprise level, like, people, like, really leveraging it?

Yeah. So, enterprises need to think differently about AI. I am gonna answer your question, but I wanna talk a little bit about, like, the enterprise use case, because I think it's important. So, there's a big difference between using AI in your enterprise and, like, toying around with it as an individual user to write rap lyrics about your dog, right? At the enterprise, you need a— first of all, you need security. Right? And so, there are differences in the platforms in terms of the amount of security and privacy that you have, that you need to have a— like, you need to understand those differences, and you need to have a set of standards for security in your use of AI across your company, like, full stop. Secondly, for the enterprise, I think you need to make sure that you can Truly, like, integrate AI in a reliable way into your workflows so you can understand, you know, you can rely on it, you can know it's going to be there, you can make sure that it's going to, you know, be in the tools that you use and not just like a copy and paste deal, because you have to equip your whole team. And then finally, I think, like, the problem with most baseline AI tools right now I'm, like, very passionate about this, is they're amazing. Like, they're magical. They can string together incredible sentences, but the output—

And rock music lyrics for your dog.

Correct. Rock music lyrics for your dog in the style of Radiohead, like, awesome stuff. But for business, the outputs can be pretty generic. And this is a problem for businesses because In a world where, like, content is commoditized, and anyone can create tons of content, no matter the size of their team, like, brand differentiation, and brand personality, and brand affinity, that stuff is gonna matter more, right? And so, I think it's really important for an AI— for an enterprise company, that not only are you using AI, but that you've got an AI that can train on your brand voice, and on your brand standards. And on your, you know, things like accessibility standards, so that you can not only have speed, but you can have control as a, you know, marketing leader or a go-to-market leader of those companies. So, that is my diatribe on enterprises and, like, why I think the needs are actually distinct, and why it's okay, I think, for some of these enterprises to be taking a beat to figure out their approach to AI and not just immediately diving in. Now, Your question was around use cases. I'll give you a couple. One of my favorite use cases of AI that doesn't get talked about that much is— so, in my time at HubSpot, we became a global company. We talked a lot about being global, you know, global first. So, not just taking, like, the Americanized English language content and then just Google translating it to, German, or Japanese, or any of the other regions that we served. And in order to really be global first, we had a pretty intensive localization process that happened across anything that we put out, whether it was, like, a product launch, or customer communications, or the app itself, right? The, like, the way we change language inside the app for users. And it was a heavy lift. I mean, we're talking a team, you know, dozens of people on the team, massive amounts, hundreds of thousands of dollars to localize all of that. One of the nice things about AI is it's not a dictionary. It's not a straight translation because it consumes language as it's written in language. It picks up things like, local idioms and metaphors and phrases. And so it's a much natural— more natural translation of content into different languages. Now, that to a company to be able to do that instantaneously and really quickly and to do so in a reliable way, that's a massive cost savings, time savings, and ideally, it means that you can open up to new markets more quickly. Right? Like, the number of times that we haven't gone into a market, the companies haven't gone into a market because, yeah, we just, we, we don't have the resources yet to hire out a full team in market to do that well. This helps with that. Now, I want to be really clear, this does not mean we do not need localization staff. We absolutely will need localization teams to Like usher that process to make sure it's right, to fine-tune it, but they're gonna be able to do a lot more with a lot less time and a lot less money.

Yeah. I'm, I'm curious, do, do you know roughly the amount of people it took and the amount of time it took, if you know the money or not, but like, to, to make that happen? And, and then how would that compare in, in your estimates doing it AI-driven?

I mean, at HubSpot, we had a— I'm trying to remember. I think we had a localization team of, let's say it was between like half a dozen to a dozen people like in-house, and then they worked with contractors and/or agencies, localization agencies outside of HubSpot, and those numbers could have been, you know, in the scores of people. To be their full operation, right? So, they would sort of run it in-house, contract it out, use services to do that first pass, have eyes, you know, native eyes on the ground to sort of check it. And they moved, like, they had it down to a system, but it just by nature of having to pass through that many people and, you know, just the volume of content, It was time-consuming. So, that's about, like, the amount of people we had. And then, for dollars, you know, I know the dollars. I don't feel like I— I don't want to, you know, reveal what HubSpot was spending on localization, so I probably won't share them.

Was this pre-public company where it wasn't out there?

It was not pre-public company, so I also, you know. But yeah, I mean, it's significant. They're not small dollars.

And what other examples do you have, like, that are some cool use cases?

You know, I get— so, I have a marketing bias because that's my background, and I think about, like, what I love is, like, if I'm rebranding the entire website, doing a complete end-to-end, what we call a tier 1 launch, I can now spin up, like, the starter assets for an entire launch in 5 minutes. Like, I'm going from— it's insane. I'm going from, you know, a month-long process of generating blog posts and video scripts and, you know, full social calendars for not just the brand, but all the executives, to being able to do that in a matter of minutes. To get that starter collection of content. Now, again, we need to go back in and make the tweaks and, like, make sure that it all fits and then, you know, do the finishing touches on it. But that kind of, like, acceleration of an end-to-end campaign is really meaningful to me. I think when you get outside of, like, the content generation side of things for AI, you look at, like, AI agents. The amount of, like, being able to consume enormous amounts of data and then visualize it very quickly, that can really help open up insights for companies and is a good use case of AI summarization. I think Slack just introduced their AI tool. I don't think it's out yet, but they announced it.

Yeah.

Where you'll have the ability to, like, we've all experienced in Slack having just, like, an endless thread of a conversation that you joined too late, you'll have the ability to quickly summarize that. So, it's really going to seep into every single aspect of how we create, interact, consume, you know, make judgment calls. And so, if you can think of a use case, there's probably an AI approach to it. And that's what I think— people talk about, like, why... God, I'm so sick of hearing people talk about AI. It's all anybody talks about anymore. That feeling, like, I get it, but like, that is why, that's why people are talking about it so much, is that like, this is actually going to dramatically change the way that ordinary everyday things happen in businesses.

Like, as a marketer, are you gonna be able to Say, look at your CRM or, or input that you want to create a fine-tuned ICP based on the quickest deals closed matrix with the highest ACV, and you want to find what's in your CRM that you're not focused on to put it out there, and then look in the World Wide Web for things that aren't even in your CRM that should be in there. Is, is that like— Is that coming, like, if there's actually a product next week that does just that?

Yeah, no, that's here. I mean, like, yes, the short answer is yes. And so, you know, how well that all works will get, you know, developed over time and will get better and better. But yeah, I mean, that's the kind of power we're talking about here in terms of the ability to consume, present differently, create, distribute, optimize, like end-to-end, there's a role for this. Now, with that comes great responsibility. I think it underscores the importance of, like, having critical thinking, thoughtful, strategic people, customer-focused people, brand-focused people on your staff to make sure that you're using that well, right? It's just a piece of technology, just like the internet itself. Like, it can be used to create incredible things, to accelerate innovation at incredible rates. It can also be used to do, like, to put a bunch of dribble out on the internet and to do horrible things as well. And so, I think, like, you know, AI doesn't become extraordinary until we do, right? And so, we have to step up as go-to-market leaders to make sure that we're thinking about the broader context of what we're doing, and we're not just taking shortcuts because we're lazy, and that with the time that we get back, that we're reinvesting that into the business in meaningful ways.

I love that. Um, and, and we don't even need to go tangential on the, the AI, um, agency that'll be in the government and stuff. That's coming. The question is, is Elon Musk and Sam Altman on it? Probably not, but they probably have input on, on who is.

Yeah, I mean, if you saw the testimony earlier this week with Tim Altman, I think that this technology is developing at a very fast pace, a pace that we have not seen in quite some time. It's all relative. There'll be something that outpaces this in the future, but it's moving, and it's moving now. Yeah. They

hit a million users in, like, 5 days, I think, or something ridiculous. Yeah, yeah.

I don't know the exact numbers, but it's— and not even just the user count, but just, like, the actual capacity of the technology is getting better, and better, and better. And we have not yet seen, because it's harder, like, we have not yet seen the pace of, like, public policy thought and regulation thought match that. It's happening. Like, there are really brilliant minds in government, and nonprofit, and businesses themselves that are working on this problem, but the paces are off, right? So, we do need, and I think Sam Altman was underscoring this even in his testimony this week, of, like, everybody wants a focus on this, whether you're business side or You know, or a user or government, like, we need to make strides here and we need to make them pretty quickly.

It's an exciting time. Now, I'm curious, you know, going back to the GTM, like, what are some challenges as an AI company going to market that— and you could take the AI out, right? That you're seeing that's like keeping you up at night?

Well, a big one is, so most of marketing, and again, I apologize for the marketing bias, it's what I grew up in.

It's awesome.

But, you know, most of marketing is about like figuring out and developing acquisition channels. So finding channels that will bring people into your websites and then optimizing your site so that people will convert and sign up, right? That's a lot of what marketing is. The channel mix and the varying influence of each channel is about to change significantly because of AI. So, Google just revealed a couple of weeks ago how they're going to bring AI into their search engine results page, and that's gonna have massive implications for organic, i.e., search traffic, as an acquisition channel. And the part that keeps you up at night is, it's not yet entirely clear. We know what it's going to look like, but it's not yet entirely clear what that's going to mean for traffic back into websites. And so, if I'm a go-to-market leader right now, and I am, just so happens, I'm spending a lot of time thinking about diversifying my acquisition acquisition sources and finding new ones to help compensate for any changes and unpredictability that may be ahead in terms of search behavior, acquisition from search, et cetera.

What channels are you hedging with? Like, where's your mind at? Of course, use diversity away from there, but spill the tea.

Yeah, I mean, I think it is about multiple channels. It's also about just understanding what's happening in search. So there's a few— let me talk a little bit about where I feel like Google Search is going. And Bing is doing the same thing in a slightly different way. But I think search is going to be a chat-dominated experience, right? You will ask the question. You will get it answered in conversation with an AI, right? Beneath that search experience, you'll still see organic kind of links to websites to sort of support that query and response. So, those blue links aren't going away, but they are gonna be harder to secure. Because when you think about, like, the real estate of a search engine results page, right now, it's 90% blue links and, like, a little bit of... A little bit of like FAQ boxes and snippets, but it's, it's mostly links. I think that's going to reduce drastically. Um, but new search vehicles are going to get added. So one of the things that Google introduced is this idea of, um, pulling in more multimedia in the results and then also perspectives content. And so for example, when you search for a topic, you will get the generative AI response, you'll get the ad clicks, the ad, sorry, placements, you'll get a couple of organic results. And then you'll also get perspective content, which could be like, hey, people on Reddit say this, or here's a TikTok video answering that question. That's, that's not AI related. But that is a new shift that Google is making that to me says, I would invest in, you know, user-generated content. I would invest in— I'm going to say influencer, and then I'm going to underscore that I do not mean like Hollywood influencer, or like, you know, depending on what your company is. I mean like micro-influencers in your field, your customers. I would invest in them because they're going to suddenly be as influential on a search engine results page as is the website that you poured your heart into. So, I'd do that. I think that I would— everything old is new again, I would invest in brand. Like, in a time where, like, information gets commoditized, content gets commoditized, because everybody can churn it out really quickly, I think, you know, brand voice and brand affinity is gonna matter a lot. Like,

Wasn't it always important? I guess people just found channels that were faster and easier and more direct line attribution.

Yeah, I mean, it's always been important, but it's like, for a while, you know, the cool— I don't mean to knock it because it was actually a pretty powerful thing. Like, the cool thing about early internet and like early search results is by optimizing a blog post and putting the right answer in place, with zero ad dollars. This actually used to be the early promise of HubSpot. Like, with zero ad dollars, you could compete. If you were a no-name brand, you could compete on the same level as, like, Procter& Gamble or as, you know, Nike, if you answered the question in the right way. And I think that, like, you didn't have to spend a bunch of dollars building up your brand, doing brand awareness advertising. Because you answered the question best, and you answered it first, right? That part, I think, the performance marketing is— the balance is shifting a little bit, where I think that it's gonna, first of all, it's gonna be harder to answer that question first because, you know, there's not gonna be any space on the search engine result pages. But then also, like, you know, in a world where, like, generative AI is answering most questions, you know, having a brand that can kind of break through that where people hear from word of mouth or they just had a good experience, like that's going to be more powerful.

When are we going to operationalize word of mouth?

I have great thoughts on operationalizing word of mouth.

I mean, as a community runner leader, Um, and I don't want to go too tangential, but community—

Exactly.

So community sits above inbound, outbound, nearbound, tomorrowbound, whatever, right? Um, community is not another strategy, although companies look at it that way. In, in my humble opinion, I think it's an output from culture and above that, society. So it's like more like getting towards the meta level, um, of that, but People, you know, in regards to go-to-mouth— go-to-mouth— go-to-market, word of mouth, you know, it's just the dark funnel, it's dark social, it's—

Yeah.

Whatever. Like, I'm curious to hear your thoughts on all of that.

Yeah. I mean, I think that if you think about community as a channel, You could drive— And I know it's more than a channel, but most channel owners, whether it's search or community, you have to invest some of your time into growing and building that channel so it's healthy. And you invest some of your time— so basically, you invest some of your time into putting value into that channel, and then you invest some of your time into extracting value from that channel. And you never want that balance to be off. And the parallel in search is you put value into search by creating content for search queries that are underserved, and then you extract value by optimizing the clicks off of that and the conversion points off of that. In community, you put value into that community by investing in the people and building the connections and the experience that's going to make that community literally grow and make it more active, right? A healthier community. And you extract values by doing so by, like, at the right moment and at the right time, leveraging that community. for your business. And so, I think, like, in some ways, I hate to boil it down to a channel because it's people, not just, like, pages on the internet. But if you do think about it as a channel—

Every channel is people, is how they're behaving or how you're going and grabbing them.

That's right. Yeah, that's a good— no, that's a good correction. Like, I think it helps frame the approach a bit and also helps frame the importance because the reason I do that is because A lot of people think about community, and they think about it as this, like, squishy thing. And they're just like, ah, it's nice to have. We do social, we have Facebook groups, like, things are happening out there. And they don't think about it as a strategic thing. And so, in the long run, they actually undercut community. You know, the community manager is the first to be out the door, or the least, you know, lowest funded, or what have you. And that's a mistake if it's a strategic channel. When we hired someone to lead content and community at Jasper, it was very important to me that they report directly into the leadership team, like, they report directly into me, they're not, like, 2 degrees down, that they thought about this as a strategy. And so, I looked for that kind of leadership in who we hired. We ended up with a great community leader. That's a bit of a tangent, but I do think that, like, companies are gonna need to invest in community because they're gonna have more power, right? And I think they're gonna get more measurable. There's lots of tools out there now that are making it easier to measure. You can speak to, you know—

I'm advising one now, and I keep giving them feedback. I'm like, all you have to do is partner with Slack, and then I'm thinking like, well, there might be some difference there. You partner with the tools that integrate with Slack, that get out sentiment, get out all of this, no problem. And figure out how people, assuming that the community is in Slack or Discord or a third-party tool.

Yeah, we were talking about this yesterday too, around like, there's all sorts of different types of communities. So just like there's different social channels there and different like paid channels, there's different types of channels within the community channel. Your employees are a community, right? Mm-hmm. So, how do you invest in your employees and their belief and experience and understanding of your company so that you can leverage, you know, their voices in a mutually beneficial way, like when you've got an announcement to make, or when you're trying to bring people in, and how do you equip them, right? So, one of the— I'll go back to an AI use case that I like is, By getting our entire community, our entire employee base into Jasper, when I have a product announcement, I can go into Jasper and put a blurb in about what is the product announcement that we're rolling out as a, like a brand voice, a memory inside Jasper. And then when every single— and we can notify the company, and then whenever they're on their social platforms, they can use Jasper. right within the platform, to pull up an original piece of, and, like, co-write an original piece of content about that announcement that's in their voice, but talks about our product, and to do that at scale, right? So, imagine every member of a 6,000-person company being able to do that. That's sizable, right? We think about reach, like, your employee base sometimes has enormous reach. And then, You do the same with your most loyal customers. You do the same, you know, in your broader community plays. And that's— then you don't worry so much if Google's sending you less organic traffic because you've got a force.

I always laugh when I go onto LinkedIn Sales Navigator and I'm looking at people like different companies that like I've saved when they have a product announcement and you could see like, like 1 to 2 engagements on each. And these are big companies from everybody and it's just like copy and paste the same thing. And I'm like, I'm like, this is— you could argue very easily that doing nothing might be neutral at worst, probably better. Yeah,

it's really funny. I'll give you an example from inside Jasper. The same— I'm gonna have to tell her I'm talking so much about her. But this woman, Meredith, who runs our content community strategy—

I'd love to meet her. We'd probably get along.

Yeah, she's got We had a big product launch. We had a launch that had Jasper Brand Voice, which is the ability to, like, train off your brand. We had this video that we were really proud of that a woman, Bria, on our video team had created, and it's incredible, like, awesome video. And my instinct, like, I'll be honest, my initial instinct was, let's get every member of this company that video and have them push that video out. And Meredith rightly pushed back on me and was like, That is going to look like a wall of spam on social channels because we're all gonna do it at the same time. We're all gonna, like, if they have a video, they're not gonna write anything original, they're just gonna say, you know, a line about the video. And it's just gonna interrupt people in their day, and they're not gonna have a good experience with the video. And countered with another way to do it, which is, let's make it easy for everybody to write their own personal take on this launch. Mm-hmm. 100% the right call.

I, I can't wait until you have a team of 100, 200, 2,000 and they do their own videos each.

That's cool. Yeah.

There's some tools that are like, eh, with that now, like they're okay. The reason why they're like, okay, is because like the video is small and it actually like looks like they're actually saying it and stuff.

Oh yeah, yeah.

But like, even if Yeah, the more authentic it could look, because at the end of the day, the posts that perform the worst in social are the copy and paste or the promotional posts of the brand. It's— I don't have the data behind that outside of seeing it.

There is data though, like text does better, you know,

for sure.

LinkedIn penalizes links, like those sorts of things.

So You know what's interesting, like, in going into, like, in my head, how Jasper uses Jasper, does Jasper also take in, like, like, a full feedback loop with that, like, how it performed so that it could recalibrate, so to speak? Like, like, and how would it do that? Because LinkedIn doesn't have an API that's easy. Maybe Twitter, but, like, I'm curious.

Um, it's very possible to do it. Um, it's a direction we're heading in. It is not something that we have today.

I mean, then you'd be every social media person's best friend ever. You're close to it already without that.

We are very aware of the need and pain point there. So I'm not going to reveal our product roadmap, but it's definitely something that we— a problem we're excited to solve.

I love that. A Revenue Today exclusive rollout.

But

I

didn't give you a timeline. I've learned my lesson there. I don't give timelines.

Oh, let's, let's think logically here. Q3 is a wash. No, just kidding. Um, how do you use AI outside of Jasper? This is what I'm curious. Like, like, I have no doubt— I mean, you gave a couple examples there of how you use it, but what else are you using, or how else are you using it?

Yeah, um, let's see. Uh, well, inside Jasper we use, um, You know, video and audio editing AI. So like Descript has great audio. I think Riverside actually probably has some audio and video editing.

Yeah, we use Jasper. Like after this, the takeaways will be done by Jasper, I promise.

Awesome. Very cool. Oh, that makes it super easy.

We're supporters.

Love it. That's great. That's a— we love that use case of like, how do you take an audio, translate it or transcribe it, and then turn it into a bunch of other promotional. But I love You know, a bunch of these podcasting tools now will put together, like, they'll use AI to recommend, hey, this bit of the podcast was really good. And so, we've gone ahead and cut, made a 15-second cut for a social promo of your podcast using this soundbite. I love that kind of thing because that's time-intensive.

Can we pull a quote out too?

Yeah, you can pull out quotes, all that stuff. So, we'll use that. Internally, we use all the, like, you know, Otter does good kind of meeting summaries based on AI that are getting really good. Yeah. You don't have to be taking notes as much, or if you miss a meeting, it helps with remote. Personally, outside of Jasper, I use—

Can you hook Jasper up to like a Google Sheet and make it Otter?

You can hook Jasper up to a Google Sheet. We just announced a partnership with Google where it'll be an add-on. With, um, no, it's gonna be— I'm telling

you, like, this year with Google, like, how different is this? Does this eliminate the need for Otter, like, for your team? Like, you could just have Google Sheet and just like that, like, why not?

Yeah, I mean, Otter's got good tricks up its sleeve too. I think that this, this time is just like bursting with innovation and new ideas. And so, like, I would not count a single company out right now. I would also not say that any company has it locked up. And I think that that's really good for the space. Like, I think that, you know, people talk about, like, oh, is, like, every company's gonna get into AI, and there's so much competition now. And, like, my personal take on it is, like, yeah, we're all gonna be just, like, lapping each other, like, back and forth again and again, and that's good for innovation. So, I don't know, I kind of welcome that time. You know, assuming that we can continue to surf it and, and, and end up on top. But, uh, yeah, I think Otter's gonna do great things too.

You bring up a good point. How could AI fail? Like, like, like we've seen things on top of the moon, um, Ethereum, but like, how, how could we— yeah, you know, how do we know AI is gonna be around? How, like, what are some vulnerabilities in like just the, um, The absorption of it across the market and stuff?

Yeah. Well, so, I think, like, there's how can AI fail, and then how will companies that are AI companies fail. I think that whenever there's, like, a major advancement like this, there's always, like, a burst of companies that come up around it, and then there's a consolidation that happens. That's just a natural flow that happens. So, I think, like, some AI consolidation will happen, AI companies that started you know, will realize that what they built is really just, like, a single use case and not truly a company. And you'll have companies that fail in AI, right? Yeah. No one is protected from that. Like, we are very painfully aware of, like, we need to keep innovating to stay in this game. As far as AI, the technology, how it can fail, so I think you have to begin with the fact that it is deeply flawed. from the get-go. Like, AI was built by absorbing, like, you know, just massive amounts of content and data, and that's how it learns. In that data that it's absorbed, it means that it's inherently biased. It's absorbing all the biases that we have. Yeah. It's inherently underrepresented, because no matter how big the slice, like, you're still making a choice about what you're including and not. And so, I think that, like, you know, I get very concerned about us using, relying too heavily on AI for very important life-altering decisions, like, does this person get a loan or not? Does this person get, you know, what's the right, like, healthcare route for this individual? Things that are really, truly important. I think that we need to be really careful about an overreliance on AI and make sure that Certainly, use AI as an accelerant to sort of help get to decisions faster, but make sure that people are not only, like, in the room, but, like, equipped to watch for the places that AI can fail. That's one. I think there's a whole field, and this is longer than we have time in the podcast, but there's a whole push right now— Yeah. a bunch of people who sort of built the beginnings of AI to, like, make AI more explainable. So, right now, I remember hearing a quote from an anonymous source that said, like, AI is more of, like, more like a petri dish than it is a math equation, in that we don't always know how it got to the conclusion that it got to. So, there's a big push right now to build more explainability into AI. We should be able to root back the decisions that AI made to get to that conclusion, and we can't today. I think that that could be a point of weakness or failure for it in the future. I think that explainability is important. It's very hard to do. We have to figure out how to do it.

What excites you about the future of AI?

I mean,

what excites you about the future, period, I should say? We could take it anyway.

Yeah, no, I mean, I I'm a tech optimist. I think that we need to not over, like, it's back to that point of, like, I get immediately skeptical about people that are too fearful of technology, and I get immediately skeptical about people who are too, like, enamored with it. And so, I guess I'm probably more of, like, a tech realist, but I have a bent towards optimism. I think that if we use this technology well, or any piece of technology well, it can open up tremendous opportunity. I think, you know, I guess I'm a tech realist and a human optimist is probably the best way to say that.

I like that.

I think we can do this. Like, I think it's gonna take stepping up for all of us. I think we need to own the responsibility that we have. But in many ways, like, the only thing that's ever really held back Our best ideas has been our ability to, like, convey them and execute them at scale. And so, you think about, you know, the founder who has an incredible idea, but is awful at pitching that idea because maybe English isn't their first language, or they're not great communicators. And so, that idea doesn't get funding or sits on a shelf. If AI can help that person communicate better, maybe that idea gets funded, maybe that's world-changing, right? So, I like AI's capacity to open up opportunity. I also think there are ways in which AI will, you know, without being checked, will hurt, you know, and will create problems that we'll need to address, that we already need to address. So, that's my blended answer of, like, tons of opportunity.

Yeah.

But also, we got work to do.

Let's end on the tons of opportunity, change the world, happy vibes. Meaghan, how can folks get in touch with you?

I am just Meaghan at Jasper. I'm still active on Twitter. I, like, you'll pry Twitter out of my cold hands. So, I'm just @meghkeeney on Twitter, LinkedIn, all the normal places you can find me.

Thanks so much for such an awesome conversation. It's, it's really been humbling to speak with you.

Oh God, likewise. Thanks so much for having me.

Okay. And everybody, thank, thank you for listening. This has been another awesome episode of Revenue Today. Um, we'll see you next week. Thanks so much again for your time, Meg.

All right. See you later.

Thank you, friends, for joining me. That was another great episode of Revenue Today. If you're looking to listen to more episodes or for the show notes, go to revgenius.com. For all my friends in the Rev Genius community, it was awesome to spend this time with you. Please DM me any feedback or ideas for future podcasts in our Slack channel or on LinkedIn. If you're not in Rev Genius, join us. It's revgenius.com. It's free and it's fast to join and really for all levels of revenue professionals. For senior leaders, we just launched a private community just for you called RevRoom. We know it gets lonely out there, and we've built a tight-knit group of senior leaders collaborating on the future of B2B go-to-market. Looking forward to seeing you all there.