Meghan Keaney Anderson – Jasper – Leveraging AI in your GTM

Quote of the Show

AI is more or 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. 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.

Key Takeaways

  • Success is not just about net new revenue, but also about customer expansion within the existing base.
  • AI has the potential to transform everyday business operations and optimize marketing strategies.
  • We need to be cautious about over-reliance on AI and ensure responsible implementation.

Transcript

 

Jared Robin: 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, Meghan Keaney Anderson. Welcome.

Meghan Keaney Anderson: Hey, thanks so much for having me.

Jared Robin: I’m so psyched because as a user of Jasper and an avid fan of AI, I’m by far not the only one. It’s going to be good to, to dive in and just understand some of the inner workings and, and learn from you. So thank you. GTM as a whole is massive and we’ll talk about AI and GTM certianly. You’ve been the VP of marketing at HubSpot. You’re now the VP of marketing at one of the hottest, fastest growing companies in AI. Debunk a myth about GTM right now.

Meghan Keaney Anderson: All right. So here’s, here’s one that I think is so common and I, 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. And when asked the question of what’s your expansion play within your customer base, what’s your messaging to your customers? How are you upgrading them? How are you predicting their 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. When the other person is 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 that new people. So my 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 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. There’s so much opportunity within that existing customer base and they already like you.

Jared Robin: Why do you think the focus is net new, because isn’t a dollar worth a dollar? And you can make a very easy argument that a dollar you have is more profitable than a dollar to get.

Meghan Keaney Anderson: I think that’s because new logos are exciting to people. I think people care a lot about new logo counts on their company and how big, how many customers do they have and what’s the latest success story, what company they just landed that they wouldn’t have been able to land six 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.

Jared Robin: And it’s not just adding the CS department, right?

Meghan Keaney Anderson: No, I mean, we, that’s actually, that is, you nailed it. That is what people get wrong. Marketing is geared towards a 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, they’ll do it all through conversation. And that’s where success extraordinary people, extraordinary team, think about how much better they could be if they had a marketing arm, you know, attached to them.

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 a revenue driver for you, you should have the strategy to match it.

Jared Robin: Yeah, Mark Roberge, I interviewed him and he said something very interesting and I’ll bring the old HubSpot references. He’s wonderful,  really smart. 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 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 prioritize this?

Meghan Keaney Anderson: Actually, I remember Mark Roberge when he was at HubSpot, 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, we think what you want to fight inside a go to market motion is 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 going to solve for getting leads. I’m going to solve for getting signups. That is my goal. That’s my domain. I’m going to 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 got to close the deal, close the deal. You know, and then CS poor, 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 close. And now having to nurture this customer and fight against churn, carry the bag basically for the rest of the teams. That happens not because people are bad people or because they don’t, they’re selfish or they don’t think about their colleagues. It happens because the incentives or 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 as Roberge said, and certainly give your team, you know, it’s 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 life cycle 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 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.

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

Meghan Keaney Anderson: 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 that new business. It can come in reductions to churn. But like everyone’s goals will ladder up to that, um, ARR number, right?

Or it’s actually and, uh, like not just ARR brought in, but like, um, net. Um, 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. Um, 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. Um, 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, uh, driving at the same bigger thing.

Jared Robin: I love that. Um, it’s so important and, and we’re all motivated by money, but also our goals. And,so it’s essential now question that I’ve been hearing, um, in some leadership conversations I’ve had, AI is a new thing.

And it’s not a new thing. It’s a new thing to be accountable for, I should say. Yeah. And, um, you know, folks boards are saying like, how are you leveraging AI? Um, in your go to market strategy, give them an answer once and for all that they could write down and, uh, go for it.

Meghan Keaney Anderson: 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, 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 a hundred web pages on our entire like integration community. AI can help there. For some people. It may be we want to write, um, you know, five blog posts a week and we’ve got a team of two, could be sales emails, but find that specific use case first and then figure out. What are the right a I tools to help get that done and do that proof of concept with that use case. So you can go back to your board and say, yeah, you know, we decided that we’re going to use AI, um, 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 it these results, 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.

Jared Robin: That’s like using a chat GBT for asking them to come up with an original piece of content. Really good with the past, but um, 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 thousand plus employees, they really want to move the needle in a massive way with AI and understood the content is not, not a massive needle, but like what other, what are some other use cases or some examples that you’ve seen at that enterprise level? Like people like really leveraging it.

Meghan Keaney Anderson:  So enterprises need to think differently about AI. I am going to answer your question, but I want to talk a little bit about like the enterprise 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, first of all, you need security.

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. 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, you can rely on it. You can know it’s going to be there. You can make sure that it’s going to, 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, uh, they’re amazing.

Like they’re, they’re magical. They can string together incredible sentences, but the output music lyrics for your dog, correct? For your dog and 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, brand differentiation and brand personality and brand affinity, that stuff is going to matter more.

And so, um, 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 go to market leader of those companies.

So that is my diatribe on, um, enterprises and like why I think the needs are actually distinct and why it’s okay. I think for some of these enterprises 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.

My, one of my favorite use cases of AI that doesn’t get talked about that much is, um, So what, 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, you know, German or Japanese or any of the other regions that we served.

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, um, 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 consumesl anguage 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 going to be able to do a lot more with a lot less time and a lot less money.

Jared Robin: Yeah, I’m curious. Do you know roughly the amount of people it took and the amount of time it took?

Meghan Keaney Anderson: I mean, at HubSpot, we had a, um, I, I’m trying to remember, I think we had a localization team of, let’s say it was between like, um, half a dozen to a dozen, dozen people like in house, and then they worked with contractors.

And, or localization agencies outside of HubSpot, and those numbers could have been, you know, in the scores of people, um, to be, 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, they moved. Like, they had it down to a system,  but it just by nature of having to pass through that many people, 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, I know the dollars. I don’t feel like I, I don’t, I don’t want to reveal what, what HubSpot was spending on, on localization. So I probably won’t share them, but it was this pre public company where it wasn’t out there, it was not pre public company. So I, I also, you know,  but yeah, I mean, it’s significant. They’re not small dollars.

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

Meghan Keaney Anderson: I have a marketing bias, cause that’s my background. And I think about like, what I love is like, if, if I’m rebranding the entire website, doing a complete end to end, what we call a tier one launch. I can now spin up like the starter assets for an entire launch in five 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, 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’s 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.

Jared Robin: Like as a marketer, are you going to be able to say, look at your CRM or input that you want to create a fine tune 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 that like, is that coming? Like, there’s actually a product next week that does just that.

Meghan Keaney Anderson:   I mean, like, yes, the short answer is yes. And so, you know, the, how well that all works will get, you know, developed. Yeah. Over time and we’ll 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, it underscores the importance of like having critical thinking, thoughtful, strategic people, customer-focus people, brand focus, people on your staff to make sure that you’re using that well, right? Because 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 can also be used to do like pretty much 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.

Jared Robin: 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 Elon Musk and Sam Altman on it? Probably not, but they probably have input on, on who is.

Meghan Keaney Anderson: I mean, if you saw the, the, you know, um, testimony earlier this week with them all meant, like, I think that there is this, this technology is developing at a very fast pace, a pace that we have not seen in quite some time, um, it’s all relative.

There’ll be something that outpaces us in the future, but like it’s moving and it’s moving now.

Jared Robin: We have a million users in like five days, I think.

Meghan Keaney Anderson: I don’t know the exact numbers, but it’s and even just 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, um, 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, um, and I think Sam Alton was, um, 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.

Jared Robin: 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 can take the AI out, right? Like, um, That you’re seeing, that’s like keeping you up at night.

Meghan Keaney Anderson: Uh, well, a big one is, um, so most of marketing, and again, I apologize for the marketing bias. It’s what I grew up in. Um, but you know, most of marketing is about lik figuring out and developing acquisition channels. So finding channels that will bring people into your websites that then, and then optimizing your site so that people will convert and sign up, right? That’s, that’s a lot of what marketing is.

The channel mix and the varying influence of each channel is about to change significantly cause of AI, so Googlejust revealed a couple weeks ago. how they’re going to bring AI into their search engine results page, and that’s going to have massive implications for organic, i. e. search traffic as a 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 was spending a lot of time thinking about diversifying my 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.

Jared Robin: What channels are you hedging with? Where, where’s your mind at? Of course, use diversity away from there, but still the tea.

Meghan Keaney Anderson: Yeah. I mean, I think it’s, it is about multiple channels. It’s also about just like understanding what’s happening in search. So there’s a few, let me talk a little bit about that, where I feel like Google search is going and being is doing the same thing in a slightly different way, but, you know, I think search is going to be a chat dominated experience. You will ask the question, you will get it answered in conversation with a, with an AI, right? Um, beneath that search experience,  you’ll see, 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 going to be harder to secure.

Cause 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 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 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 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, 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 the website that you poured your heart into.

So I do that.  I would. 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 going to matter a lot.

Jared Robin: Like, wasn’t it always important? I guess people just found channels that were, were faster and easier and more direct line attribution.

Meghan Keaney Anderson: 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, 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 are a no-name brand, you compete on the same level as like Procter and Gamble or as, you know, Nike, if you answered the question that 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 answer 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 going to, first of all, it’s going to be harder to answer that question first because, you know, there’s not going to 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.

Jared Robin: When are we going to operationalize word of mouth?

Meghan Keaney Anderson: I have great thoughts on operationalizing word of mouth.

Jared Robin: I mean, as a community runner leader. And I don’t want to go too tangential, but community sits above inbound, outbound, near bound, tomorrow bound, whatever, right? Um, community is not another strategy, although companies look at it that way 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 market, word of mouth, you know, it’s just the dark funnel, dark social it’s whatever.Like, I’m curious to hear your thoughts on all of that.

Meghan Keaney Anderson: Yeah, I mean, I think that if you think about community as a channel, 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. Um, and you know, the, 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 generalist, people’s how they’re behaving or how you’re going and grabbing them, right?

Yeah, that’s a good. No, that’s a good correction. Like, I think, 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, Oh, 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, to be out the door or the least, you know, lowest funded or what have you like, and that’s a mistake if it’s a strategic channel, like when we hired a, you know, someone to lead content and community at Jasper, like it was very important to me that.

They report directly into the leadership team. Like they report directly into me. They’re not like two degrees down that they thought about this as a strategy. And so I looked for that kind of leadership in, uh, in who we hired. We ended up with a great community leader, but. Uh, that’s a bit of a tangent, but I do think that like companies are going to need to invest in community because they’re going to have more power.

And I think they’re going to get, they’re going to get more measurable. There’s lots of tools out there now that are easier to measure.

Jared Robin: I’m advising one now like, yeah. All you have to do is partner with, uh, Slack. And then I’m thinking like, well, there, there might be some difference there. You partner with the tools that integrate with Slack, that, 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.

Meghan Keaney Anderson: We were talking about this yesterday too, around like, there’s all sorts of different types of communities. Just like there’s different social channels. There are different like paid channels. There’s different types of channels within the community channel. Your employees are a community, right? 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?

When you’ve got an announcement to make, or when you’re trying to bring people in, how do you equip them? Right? So one of the, I’ll go back to 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 that whenever they’re on their social platforms, they can use Jasper right within the platform to pull up an original, you know, 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 6000 person company being able to do that. You know, that’s sizable, right? We think about reach, like your, 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 place. And that’s, then you don’t worry so much if Google sending you less organic traffic because you’ve got a force.

Jared Robin: I always laugh 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 one to two 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 that very easily them doing nothing might be neutral at worst, probably better.

Meghan Keaney Anderson: It’s really funny. I’ll give you an example from inside Jasper, the same, um, I’m gonna have to tell her I’m talking so much about her, but this woman, Meredith, who runs our content and community strategy.

Jared Robin: I’d love to meet her. We’d probably get along. Yeah.

Meghan Keaney Anderson: She’s got a, we had a big product launch. We had an, a, launch that, um, had Jasper brand voice, which is the ability to like train off your brand. We had this video that we were really proud of, um, that, uh, woman Brianna, our video team had created. And it was, 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. Cause we’re all going to do it at the same time.

We’re all going to, like, if they have a video, they’re not going to write anything original. They’re just going to say, you know, a line about the video. And. It’s just going to, it’s going to interrupt people in their day and it’s not, they’re not going to 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.

100% the right call.

Jared Robin: I can’t wait until you have a team of a hundred, 200, 2000 and they do their own videos. Each. That’s cool. Yeah. Um, there, there’s some tools that are like, 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.

But, but like, even if, yeah, the more authentic it could look, because at the end of the day, um, the posts that perform the worst in social are the copy and paste are the promotional posts of the brand. I don’t have the data behind that outside of seeing it.

Meghan Keaney Anderson: There is data though, like text, text does better.Um, you know, for sure. LinkedIn penalizes links, like those sorts of things.

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

Meghan Keaney Anderson: it’s very possible to do it. Um, it’s a direction we’re heading in. It is not something that we have today.

Jared Robin: 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, of the need and pain point there.

Meghan Keaney Anderson: Um, so I won’t, I’m not going to like reveal our product roadmap, but it’s definitely something that we, a problem we’re excited to solve.

Jared Robin: I love that. I’d review today. Exclusive. We’re all out.

Meghan Keaney Anderson: But I didn’t give you a timeline. That’s that’s what I’ve learned. My lesson there. And I don’t give timelines.

Jared Robin: Oh, let’s, let’s think logically here. Q3 is a wash. No, just kidding. 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.

Meghan Keaney Anderson: Uh, well, inside Jasper, we use, um, You know, uh, video and audio editing AI.So like Descript has a great audio. I think Riverside actually probably has some audio and video.

Jared Robin: We use Jasper. Like after this, uh, the takeaways will be done by Jasper. I promise. Awesome. Very cool. We’re supporters.

Meghan Keaney Anderson: Love it. That’s great. That’s it. 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, um. You know, a bunch of these podcasting, tools now will put together, like they’ll, 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. Um, I love that kind of thing.

Cause that’s, that’s time intensive.

Jared Robin: Can we pull a quote out too?

Meghan Keaney Anderson: Yeah, you can pull out quotes, all that stuff. Um, so I’ll, we’ll use that. Um, internally. Um, we use all the like, you know, Otter, um, does good kind of meeting summaries based on AI that are getting really good. You don’t have to be taking notes as much or if you miss a meeting, it helps it with remote.

Personally, outside of Jasper…

Jared Robin: Can you hook Jasper up to like a Google sheet and make it Otter?

Meghan Keaney Anderson: You can hook Jasper up to a Google sheet. We just announced,  a partnership with Google where it’ll be an add on with, no, it’s going to be, I’m telling you, like, how different is this? 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, it’s like every company is going to get into AI and there’s so much competition now. And like, my personal take on it is like, yeah, we’re all going to 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 is going to do great things too.

Jared Robin: You bring up a good point. How can AI fail? Like, like, like we’ve seen things on top of the moon, um, Ethereum, but like, how, how could we, you know, how do we know AI is going to be around?How, like, what are some vulnerabilities in like just the, um, the, the absorption of it across the market and stuff? Yeah.

Meghan Keaney Anderson: Well, so I think like there’s, how can AI fail and then how will companies and that are AI companies fail, I think that whenever there’s, um, like. 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. It’s just a natural flow that happens. So I think, like, some, um, a, I come consolidation will happen. Companies that started, you know, will realize that they what they built is really just like a single use case and not. Not truly a company, and you’ll have companies that fail in AI, right?

Um, no one is protected from that. Like we’re very painfully aware of like, we need to keep innovating to stay in this game. Um, 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 a 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. It’s inherently under-representative because no matter how big the slice, like, you’re, you’re. You’re still making a choice about what you’re including and not. Um, and so I think that like, you know, I get very concerned about us using a 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 over-reliance on 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.

I think the, there’s a whole field and this is longer than we have time in the podcast, but there’s a whole push right now by 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.

Jared Robin: But what excites you about the future of AI? I mean, Or what excites you about the future period, I should say. We can take it anyway.

Meghan Keaney Anderson: I, I’m a tech optimist. Um, 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.

Um, and so I guess I’m probably more like a tech realist, but that, but, but I have a bend 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, I’m a tech realist and a human optimist is probably the best way to say that I think we can do this.

I think it’s going to 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, you know, the founder who has an incredible idea.

But it’s 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 I can help that person communicate better. Maybe that idea gets funded. Maybe that’s world changing. Right? So I like a eyes capacity to open up opportunity.

I also think there are ways in which I will. You know, without being checked with will hurt, you know, and will create problems that we’ll need to address that we already need to address. So, um, that’s my blended answer of like tons of opportunity, but also we got work to do.

Jared Robin: Let’s uh, let’s end on the tons of opportunity, change the world, happy vibes. Meghan, how can folks get in touch with you?

Meghan Keaney Anderson: I am just Megan at Jasper. I’m still active on Twitter. Uh, I like, you know, pride Twitter out of my cold hands. Um, so I’m just Meg H Keaney on Twitter. Uh, LinkedIn, all the normal places, uh, you can find me.

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

Meghan Keaney Anderson: Oh God, likewise. Thanks so much for having me.

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