Andrew Warner: Hey there Freedom Fighters, my name is Andrew Warner. I’m the founder of Mixergy, where I interview entrepreneurs about how they built their businesses for an audience of entrepreneurs who, guess what, are building their businesses. Joining me is someone who, in the early days of AI, experimented with software and had this mind blowing realization that this was the future. Even though, at the time, it wasn’t really… He ended up basically moving his whole business into this space, and as a result, he is now leading a company called AnyWord. AnyWord allows you to write using AI, and what’s cool about them is you first say what you’re writing. So you can say, I’m writing a tweet, I’m writing an article. And give it some context, and then it’ll start you off with that first draft and write along with you. And I wanted to have him here to talk about how he did this, and I’m looking at his eyes, and I feel like I’ve captured maybe 10% of the magic of his software. But I think that gives people a sense of what it is, and I should say this interview is sponsored by me.
I am looking for one other person who wants to create a podcast. If you want to have our team produce and publish your podcast, contact me. Andrew at Mixergy. com Alright. Yaniv, give me a sense of how many people are using any word right now and what the revenue is.
Yaniv Makover: We’re close to 10 million in revenue and there’s thousands of paying users and hundreds of thousands of free users using Anyword
Andrew Warner: okay, and 10 million over how long
Yaniv Makover: that’s ARR. Sorry.
Andrew Warner: 10 million annual recurring revenue profitable
Yaniv Makover: no, we’re growing. So we’re not profitable.
Andrew Warner: Where’s the biggest expense right now
Yaniv Makover: There’s a lot of acquisition and then R& D, right? So we have data scientists and AI engineers. It’s still a big part of our class structure.
Andrew Warner: So what you were doing before was you were helping publishers take their content and advertise it on Facebook and other platforms and messing around with different things. What are what’s one of the earlier? Large language models, these, what we now consider AI.
What are one of those ones that you were playing with in the beginning and what happened?
Yaniv Makover: early on we were like trying to make the grandfather of ChatGPT or the great grandfathers of a model called BERT and BERT was came to the scene early on by it’s like an open source model by Google.
And it was like solving lots of problems that like weren’t really hard to solve before. And we were messing around with it, trying to create like these ads for our customers. And it wasn’t that easy. First of all, the models weren’t as large, so they were, like, losing context, and they were, like, going off the rails.
But we had enough examples to get those models to write short sentences that were, like, really generic. Let’s say you wrote an article, and the post text would be you couldn’t believe this, or what did this guy do this time? And because the texts were generic, they were actually pretty powerful.
But one of the first things, or the early things, one of the results we saw was like we, we started playing around with it and like these models are like completion models. So like you give it a bunch of words and it completes the next word. When we started like playing around with like math, like 2 plus 2 equals 4, and then 4 plus 4 equals 8, and it was like, this was like 2018 or 17, and that was like mind blowing to me because it was like such a cool trick, right?
Like you, Basically, based on words, this model now knows math. By the way, if you give it like 8 plus 8, it would say it’s 20. But generally, back then, that was like, for me, it was like, wow, the implication of this is like crazy. And if you think about this this magic trick, this party trick, that’s ChatGPT.
That’s that’s LLMs today. That’s, it’s basically just through understanding words or this… The statistics of where words appear next to each other, you can now understand the world. When we saw those results, by the way, I was so enthusiastic about that, that I just went to the investors and I went to the company and I was like, wow, we’re going all in on this.
And I was trying to convince everybody that like investors and customers that AI is going to be writing. What they read and we’re helping people write what they read. I was like, nah, it’s not going to happen. It’s not going to know enough stuff. It can’t replace me. And and what’s so cool is when I talked to investors today, I was like, yeah, you’re that guy that told me that this is going to be a thing.
And it’s actually had a conversation like last week with someone. I was like, yeah, it happened. Yeah we were like very early because we saw that, just messed around with it and just worked. It’s pretty cool.
Andrew Warner: Were you the kind of person who constantly messed around with different software, different ideas to see what the future was? Or was this just a random thing that was going to solve a problem that you were wrestling with?
Yaniv Makover: I don’t think I’ve, I’m not that person that like messes around with different things. I think this problem, like the whole understanding words and text, like it was something that I. I’m basically I’ve been obsessed with like for a long time. I’m just like really pay attention to what people, what words people use to when they talk and how they try to convince each other of things.
And I also like in the AI space for me I was trying to write a chat bot 10 years ago. It was horrible across Microsoft Messenger and just really, for me, this was always like the coolest part of AI. And so this just obsessed with this problem.
Andrew Warner: I see. It’s just a personal obsession. You knew this part of the future was coming and you kept dipping your toe into it, practicing it, playing with it, and now suddenly, Bert did something that was amazing and you said, the future is today or at least the beginning of it. We have to start paying attention and you paid attention.
I want to get back
into any word
Yaniv Makover: was trying to
Andrew Warner: the business that you…
That you formed based on what you discovered. But let’s go back a little bit before I told you that one of the issues that I have with telling your story is it feels unrelatable. You start off with these clients, like the New York Times that was paying you to basically buy ads for their articles on Facebook. And you said, Andrew, do you know how hard it is to get the New York Times to even pay attention to us? And I said, no, I don’t. So let me ask you now, how did you get. The New York Times to sign up as a customer. Walk me through how you did it in the early days.
Yaniv Makover: So just to appreciate the problem, like you’re I’m Israeli and for an Israeli to just get to American publisher or a media company. It’s like getting to the moon or something. I know absolutely no one that knows anybody there. And actually I was talking to all these, like Israeli media companies, cause Israel is a soft place.
So you can pretty much get to those people. And they’re like also completely disconnected from media companies and from us based media companies. And there’s this one person is where I remember he was like telling me. I can connect you to, I don’t know, the New York times or whoever, and it turns out they couldn’t.
And eventually I was just like just emailing cold emails and just approaching on LinkedIn and just nobody answered me for a long time. And then I started trying to connect to other entrepreneurs and other companies that were already selling into that market. And I found that, by the way, West Coast startups were for some reason way more helpful than East Coast.
Like the San Francisco versus New York so I don’t know why. And then I just I had a lot of some people were helping me and introducing me and then once you get one or two or three, four customers then you are, I don’t know, those five first customers are.
Impossible to get, super hard to get and then eventually I got to after 50 cold emails, I got the guy from the New York Times to answer my email and and I demoed them and I said, and this is like early days of when publishers were paying this was before publishers thought they had to pay Facebook to get users and traffic.
And I was like telling them, look, this is coming. And I had the demo and they, and he, and they bought into it and they started using Kiwi. And six years later, that guy is like the, he helped me choose the wedding ring for my wife. That was a good good partnership.
Yeah. Good friend.
Andrew Warner: I interviewed someone who was an intern for Gary Vaynerchuk, who buys ads on social media a lot. And he said, Gary had a realization early on that ads on Facebook. While everyone was angry at Facebook for charging brands to reach their audiences, ads on Facebook were pretty inexpensive. And so what Gary was doing was, he was buying ads on Facebook and sending it over to websites for his clients and arbitraging the ads.
It’s putting more, getting more revenue on ads on the websites than he was paying Facebook to get traffic to those sites. Is that one of the realizations you had that if people like the New York Times bought ads, they would make more money from the ads on their own sites than they were paying Facebook for ads? Is that it?
Yaniv Makover: Yeah. There’s all of them. I think in that ecosystem, there’s a lot of ways that publishers early on I think should, could take advantage, still are taking advantage. So first of all, the feed is basically a content place. It’s like not a, it’s not a place where you’re looking to buy something, but it’s a place where you’re looking to consume content.
So ultimately, the unit economics for doing an ad for content it’s very, it’s cheap, right? You could pay back then you could pay a cent per click. So like you get a cent per user. And and then the media companies, yes, could arbitrage that with they put like a lot more ads on their website, so they’re getting more than a cent per user.
And then that was like and there’s a fine line between the what’s the user experience that a user has, but there’s a lot of other advantages. Generally, if you’re a brand and you’re trying to get impressions with a, like a user then those like social channels are one of the best ones to get them through a publisher.
The publisher is actually creating some content. They’re they’re gonna get a lot of love from the platform, so the cost per impression is much lower. And then the brand, ultimately, there, there’s just like the math works. And I think that’s a big part of that top of the funnel ecosystem. So publishers play a really important part.
They are the influencer, basically. So people follow them. They have reach. And it’s even if they pay for that reach, it’s still subsidized because they have a brand name. So there’s a lot of things that they bring into the ecosystem.
Andrew Warner: Got it. And so what you realized was, brands, publishers can pay for ads if they are willing to look at it, the numbers will make sense. They could then sell sometimes just branded ads. I don’t know what luxury product is on New York Times, but if… If Gucci likes to be associated with the New York Times content, the New York Times will sell them those big ads that will give that platform to them. So that makes money for them. And the other thing that you added was intelligence. You said we’re not just going to randomly be throwing ads up on the Facebook feed. We’re going to understand which consumer group is more likely to see which article and how do we write the right ad. to promote it. So you were both seeing the opportunity in buying ads and social for media sites, but also in customizing to the audience, improving the ads and the whole thing needed to be really streamlined.
And that was what Kiwi was doing. Am I right?
Yaniv Makover: this is like the origin of performance writing, which is what AnyWord is about. Performance writing is, what do you have to write that will work to persuade someone to do something? To drive intent, to think about something.
And different audiences need different words and for different goals. You’re trying to get somebody to click on an ad, you’re trying to get somebody to buy something. You need different words for different audiences. And to me that was like, almost insane that all these publishers are writing all this content and they’re doing it the same way they did it in 1905, right?
But the content is getting read on some feed, right? And then that feed knows who’s reading it. Where they live, and LinkedIn knows your job title Twitter knows a bunch of stuff about you, Facebook knows a bunch of stuff about you, and they’re still like writing it the same way. And so Kiwi was basically, hey, this is something we’re going to solve.
We’re going to look at all the words in the article, and then figure out, or people want to read it, who wants to read it, and then more importantly, will they do what you want them to do, or like your business objective, like they want to subscribe, or they’re going to click on something, or they’re going to subscribe to your newsletter.
And then and then that is something you can now control distribution. It was clear to us that paid distribution is going to be the way forward for most of these companies. And from there, like we always started about performance writing and now AnyWord is all about performance writing.
So AnyWord came out of Kiwi and it was clear that some writers were doing better than others. Some publishers were doing better than others. They knew their audience better and they also are like to to defend them. They had a bunch of problems. Like they’re writing for lots of different audiences.
So even if you’re a niche publisher, a media company, you still have a very diverse audience. Audience and you’re writing about different topics and different themes. It’s not easy for you to get it right every time. And and we also saw that, they had tendencies. So the writers or the copywriters and the writer had tendencies to pretty much do the same thing.
And it was like a, it was like three years that everybody was like doing clickbait and then that went away. But generally we thought, oh, this is a data science problem. This isn’t like a, this is something that we can crack and we can crack with with ai. So that’s when we started working on that problem.
We had a hunch that this is solvable We actually couldn’t solve it. The tech wasn’t there yet until Bert came to the scene Like, okay, we can solve this and a lot of other problems will get solved after this.
Andrew Warner: The original version, was it human beings who were reading the articles and then writing the social media ads or was it software that was doing, it was people who were writing it?
Yaniv Makover: we had, we still have two cooperators, but we had a team and they were writing the posts for these media
And we were testing them to see if they knew how to like which posts would work better or which copy would work better. And they didn’t agree with each other. So we give them like pairs of texts and they have to guess which one worked better and they didn’t agree with each other.
And also it turns out that if you give them the same I’m like data set to rank copy, three months later, they didn’t agree with themselves. Like they had different results. So the biases for people about what works are aggressive. I was like, okay, we, this is definitely a problem that, that, that needs solving.
And just people need help, like how to write the right way for every topic.
Andrew Warner: got it. So it was first people who are reading the articles, writing the ads, matching the ad to the article, and then you kept saying, we’re going to find software that’s going to do it better. And the more that you saw the results of people’s writing, the more you realize we have to find software because. People come at every article and every audience with their own biases and software can actually look and say what words will really match with which audience and which articles that we’re trying to promote. Got it. Okay. So you’re doing all that. I told you the other thing that was intimidating about you was that you had early on raised 9.
1 million in funding is what I saw in an old New York Times an old TechCrunch article that Google’s Eric Schmidt’s innovation endeavors and others had put money into the business and you said, Andrew, it wasn’t that easy. In fact, the first person who offered to give us a check offered to give us 250, 000, but he had a lot of restrictions.
Who was this person?
Yaniv Makover: So actually the Eric Schmidt fund, the innovation fund, they gave us our first check early on. And then it wasn’t. That check came with stipulations, like a seed round, it was pre seed, that was, back then it was called seed. And they gave us like a really small part of the round. The stipulation was we had to get 800, 000, and they put, they gave us 250, 000 from that.
Andrew Warner: They said, we’ll give you 250. We want you to prove this out, but we’re not going to give you only 250. Go and finish this round at, what was it? 800, 000, you said?
Yaniv Makover: yeah, you have to get 800, 000 in the next 60 days
Andrew Warner: so go find 550, 000 from other investors and only then will we give you this 250. We don’t want to be the only ones. Okay. And 60 days is all you have to do it.
Yaniv Makover: So they were making me jump through the hoop, let’s see if this guy can actually get more money from other people, and he can actually lead it, and it was like a, I actually. That was hard. When you need to get other checks, I was in the Valley and Silicon Valley back then.
And it was like, you had to get checks from people. And then you’re just like, you have, 60 days and I worked really hard. And I had a, I couldn’t, I didn’t sleep. I had a sty. I don’t know if you call it in English, like a sty in my eyes. It’s like super pressure. And then. I think a day before the 60 days was up, I had a I had the 800k and one of the, like one of the investors was pulled out the last day before I had to go.
And this was like, I don’t know, 150, 000. And I was now missing that, I’m going to miss the opportunity. That’s it. If I was going to miss the opportunity, the startup will die, right? I don’t know if people are aware, like startups have like the dynamics and momentum. And you have co founders and if you miss on something that everybody was just like move on to something else.
And it was like make it or break it. So I one of the early kind of our customers slash partners. It’s like we were doing a it wasn’t even on the product roadmap. We’re like doing some of a project for them that was connected to what we’re trying to build. Like scrappy stuff that startups do just to survive.
And I called them and I said, look, if you’re not, if you’re gonna either invest in us. Or we won’t do this project because the company is not going to exist. And they like stepped up into the round. I had to like caress them into it, but I was still missing. And then I had to bring in 20K for my parents.
I was like, I need 20K. So you got to your parents and I need an allowance. And this is and then I got there. I still had 790 or something like that. And then there was like a meeting. I came in to the partner and innovation endeavors. And it’s okay, I have 790.
He said okay, fine, let’s do this. And that’s how we started.
Andrew Warner: Why wasn’t it easier to say, look, Eric Schmidt’s investment company, this is the guy behind Google, super smart. They believe in us and they want to come in. They just want others to join in. Will you join Eric Schmidt? Why wasn’t that social proof enough to convince people?
Yaniv Makover: First of all, I was, I made all the mistakes in the world. I thought this was like my first time, right? I was basically… I never oversold it. I always undersold. I always said, Hey, if you come in and if I have 800k, then I would have enough to run. I was like, I wasn’t like I wasn’t overselling it.
I was trying to be very transparent with every investor and I had to meet all the other investors and it’s just like every mistake you shouldn’t do as like a, an entrepreneur. And it was very early, so we didn’t have a lot of traction. We, nobody knew us and we were like outsiders.
It wasn’t easy. It wasn’t easy for us. It wasn’t easy for me. It wasn’t like the days of, it wasn’t that easy to raise money back then. It was like, it was harder. It’s 2013 way harder than, instead I think, all the way to 21 or 22. And you had to have traction and you had to prove something.
And we had, that was just early days for us. So yeah, it wasn’t
Andrew Warner: much did you have built when you got funding?
Yaniv Makover: So we had a pretty good demo and we had a bunch of paying customers already. One of them turned out into an investor and we had the same kind of vision about the problem and insight about this is people still writing the same way and the feeds have all this data about users Why aren’t they writing for those users?
What can we do to fix this problem? And we ended up going to publishers because publishers were actually were you know, it was easy to prove to publishers, performance That was just something that was easier. And so they really cared about finding the right audiences and stuff like that
Andrew Warner: How did you end up with with innovation endeavors as one of the investors?
Yaniv Makover: Actually, how was I introduced to them? We were part of an early on we went to an accelerator This Accelerator, this is like not the Accelerator you have today. So this is like an Israeli Accelerator that had like a house in the Bay Area in Menlo Park. And they would take five Israeli startups, they put them in the house.
Like big, one of those like TV shows.
Andrew Warner: like, Big
Yaniv Makover: would like,
Andrew Warner: Yeah
Yaniv Makover: with five tech teams.
Like a super smelly house. It wasn’t like, yeah, it’s something I would recommend. And then you’d go there and you spend two months in Menlo Park. And you have demo day, right?
So in demo day innovation developers came there and that’s how we met them.
Andrew Warner: So you did all this. Software was built. New York Times is a customer. Eric Schmidt’s investment firm is investing. New York Times is investing too. Others are in. And then at some point you say, I’m switching this whole business over to become AnyWord.
I think we could allow anyone to write. How is that? Did you start a brand new product from scratch at that point?
Yaniv Makover: Yeah. That, it’s not it’s so Kiwi, which is like our publisher facing product and service grew really fast. And was for like, past our series A, we were, we decided to turn it profitable because the publishing space wasn’t big enough for us to grow. And if we looked at other and our technology was like language based.
So if you go to another market, let’s say we had Le Monde. And so like the biggest newspaper in France, there’s only five newspapers. There’s a, you have to, like every market, there was, it wasn’t big enough. And so we knew that the opportunity to grow within that space within that product was it took us time for it to dawn on us that our product is niche for publishers and we can’t just take it to other customers.
Like they had some brands and businesses look like publishers or content marketers, but they have different problems. And our product was becoming more and more. Niche and solving problems for publishers and then while we were trying to attempting to solve problems for them for publishers, one of the problems we were trying to solve was like, how can we have an AI write better for them than the post or the ad copy for them?
Because we were having people do that before that or their copywriters and then when we had this like internal team that was working on that and it was like low key. And at some point when we saw that there’s stuff we can do here, that is we weren’t convinced that this would work, then there is a problem where you have already a revenue and you have lots of customers and we are trying to grow this new thing, it will starve out because every time there’s a problem with the customer, your resources are going to that customer, especially if it’s a profitable company.
It’s and we weren’t in a position to fundraise because, we don’t have anything yet. So we made like a conscious decision that every person that we’re hiring to work on AnyWord is not going to look at, even know the code stack of Kiwi. And then even if we wanted to, we couldn’t like hijack them or take them to the original product.
And then over time, just AnyWord grew bigger and bigger. And then today there was like completely separate teams. Kiwi uses the AnyWord API, but generally. Separate teams, separate stack, separate products.
Andrew Warner: And so eventually it just started to take on its own life. Why not then say we’re gonna spin off Kiwi? It’s two different companies now. Why are we running two?
Yaniv Makover: Essentially we did spin off, so Kiwi has its own CEO. It’s just under the same cap table, so they have everything, like mostly their own office, their own marketing, everything is different. Just from a financial standpoint, it didn’t make sense to… Also, there’s synergies between Kiwi and AnyWord. So Kiwi is where we, that’s our origins.
That’s our, how we understood the space. And there also Kiwi resells AnyWord into the publisher space. So if publishers want to use generative AI or performance writing they’ll use AnyWord. Also, I think what’s really cool about our space is that today AnyWord is not even used as another.
Genitive AI tool. It’s used as a platform to power your Genitive AI tool. So you can use any word with ChatGPT or AI Notion or AI in Canva and any word is basically the intelligence above that what’s gonna work? It scores your copy. It tells you how it’ll work for your audience and stuff like that.
That is QE as well And we still believe that there’s a lot of upside in the publisher market. So it’s not like we’re like
Andrew Warner: So that’s the part that I was looking at your face when I introduced what AnyWord was and I saw that I was just capturing A bit of it and to be honest with you It’s partially because I know when I go to your website. I can pick what kind of product I write And I think blog post is the main one that you do but I can pick the type that I want And then it customizes the writing experience for that one.
So for example, if I wanna write a tweet about an interview that I did, I could take the u r l of the tweet, put it into any word after selecting that. I want it to be a tweet, and any word will write a few tweets for me. That’s what I see, that kind of experience. But there’s also, I think it’s the Chrome extension that plugs into any writing that I have anywhere, including on chat, G P T. Including a notion that somehow interacts with my writing there
and uses AI to make it better.
Yaniv Makover: 70% of the any word product is basically adding your enterprise data into any word. So what worked for you and your ads, connecting to your social accounts, putting a, some code on your website, understanding all the messages for your web for your company so we can personalize and just not taking that data.
And Indexing it and understanding it, who your target audiences are, what worked for you in the past, what didn’t work. And then, we take that like understanding and we leverage that with any words on proprietary data about what actually works in language. And then using that, you can basically install a Chrome extension.
We have also like native integrations to other channels. And our idea is that your marketing stack as a team, you’re probably going to use five or six applications that have genuine VI. You’re not going to use just one. Shadgy PD might be one of them, but you might be, I don’t know, using MailChimp to write your emails and you’re missing now that, that whole kind of like brain behind all of them.
So a, that they stay connected to each other on brand and also MailChimp doesn’t know what worked for you in your ads. And it doesn’t know what you’ve written on your website. And ChatGPT doesn’t know that either. So you need to tell ChatGPT, Hey, why don’t you use this benefit and talk about this talking point and address this target audience and write it in this style.
And then this all came from, we always knew that generative AI is going to be like a thing or we, not always, but since five years back. But then we always thought okay, now you can hit a button and generate 8, 000 tweets and they all sound good. Which one are you going to use? And then before a generative you would write five tweets.
And then, okay, A, B test all of them. That’s not a big deal. And then send out the best one. But you can’t A, B test 8, 000. It’s just too expensive. We came from that space of performance marketing. So we understand how expensive and improbable, impractical that is. So we’re always focusing on how do we rank those 8, 000 tweets?
How do we tell AI to generate the right one? Or if they generate 8, 000, that’s fine. How do we pick the best one? So any word is that platform for performance writing. And then yes, you can in in some cases for ChatGPT, you can download our Chrome extension. And that Chrome extension will tell ChatGPT what to write about.
It will augment your prompts. And also if you generate some stuff with it, it will tell you. Which text will work and which won’t in chat with you or any of your workflows.
Andrew Warner: I see. And so that answers also the question of why AnyWord when there’s so many other tools, including the ones built into now Google Docs and Notions writing process. There’s so many different tools for doing AI writing in other platforms. And what you’re saying is the difference that AnyWord brings. Is that you are unifying the brand voice, writing in their voice across all these platforms, and then predicting how well it’s going to do.
Yaniv Makover: Yeah, what we’re trying to sell to what we found out from enterprise companies that they’re using AI now to write a lot. It’s not performing as well as they had their expert writer do it because that expert knew what worked for them and expert had all the institutional knowledge about the organization.
And the AI just doesn’t have that. And then we want to get them to use, yeah, great, now you’re creating content at scale but it needs to perform at least as well as before when your content marketer or your writer or copywriter were writing it. That’s what any word is the value proposition to enterprises.
Andrew Warner: How did you get to that realization that’s what people want, that’s what your customers want?
Yaniv Makover: It’s like it evolved over time. A seminal, so we always we’re trying to solve the performance problem, right? So for publishers, we’re trying to get the right, the best ad. We understood that they get it, right? If you get, you write a better ad, it will work better.
So we knew that was a problem we want to focus on. But early on let’s say before Chachapiti happened, like in, before December last year We had to bundle our data and our performance prediction inside text generation. Because most teams didn’t even have generative AI. So they had to have that and we had to provide that.
But then after ChatGPT, something really good happened for us. Okay, we don’t have to now, incorporate, like we can separate those two functionalities and then focus on what we’re really good at, which is performance and performance prediction. And then now we can, any other tool. So we knew performance is not a big deal.
Every marketer needs that. So it’s not a hard sell to understand. Understanding that generative AI is going to be everywhere. We need to take care of the performance part of it. That’s like a, I don’t know, a hunch that we had. And then once Chantrypty was out there, we already are talking to customers and understanding what their pain points are.
Usually they’ll tell you it’s not writing with my tone. It’s not doing it’s not as great as if I were to write it and it doesn’t perform as well. Like bland in some respects. I was like, okay, I know what that, what you’re talking about. It just doesn’t know your product, your company.
It doesn’t know what works for you.
Andrew Warner: that was my issue I didn’t realize that I can go in and be that granular about my voice And so I did put in one of my past interviews and I asked Any word to write a tweet about it and it was too stilted and it was presenting it as if a third person had done The interview and what you’re saying is that’s the generic thing that you get if I want to get something more To me, I need to go back in and start telling any word what my voice is like, giving it examples, I think. And things like that to make it better examples, links, writing style prompts. And then once I do that and get it dialed in, it’ll write in my voice throughout. And that’s the magic here.
Yaniv Makover: Oh, and also give examples of things that didn’t work well for you. That’s almost as important as things that did work well. And
Andrew Warner: I didn’t realize it was a place to do that.
Yaniv Makover: Yeah if you connect your ad accounts, your social posts your website you obviously have tried some stuff that didn’t work, let’s say you posted something on LinkedIn, didn’t get as much engagement, that’s something that you can train a model on.
Okay, this is not the right way to present Yaniv Makovar as a guest maybe we should talk about his nice eyes or something like that,
Andrew Warner: And that’s in brand voice where I do that, where I go back into the message bank and I say, I
Yaniv Makover: It’s called copy intelligence, and copy intelligence, you just need to copy. You just need to connect your channels and and once you connect them, we have the bad and good examples automatically.
Andrew Warner: I see that. I’m seeing copy intelligence, analytics, talking points, custom models, web automation. So it’s
Yaniv Makover: So if you go to integrations first, that’s where you connect resources integrations, that’s where you connect it. And then you go to, you can create a custom model and then you can depending on the tier you’re at. And you also see what’s actually the top performing talking points, like what worked for you, what benefits actually you should talk about.
And then all that goes into the editor. And now you can. Pretty much regenerate stuff.
Andrew Warner: Where do you think all this is going? The easy answer is that people throw out is, I’m going to see AI in everything. If you type on iMessage, AI will help make it better. Give me more specifics. What do you see happening if we sit here and talk five years in the future? with AI
Yaniv Makover: Yeah, I think first of all like I think there’s so many applications to generative AI, which I think is cool. AI is not new. People have been working on AI for 30 years and there’s been like great stuff and understanding images and all that. But I think the generative aspect of it, there’s just so many applications that are amazing, disruptive to spaces.
I think in our space I think one thing that people tend to think, which I disagree with is that. Oh, we’re going to be bombarded with this like synthetic content and we’re just going to just give me too much And I was like no you’re already bombarded with content doesn’t matter if somebody in some person And I don’t know wrote it in their garage.
There’s lots of people and they’re writing a lot of it They’re all trying to get at you with emails and social posts and whatever and so you’re you’re already maxed out and in the content that you’re getting now They’re going to see use there was no shortage of of spam in the world.
And how is this going to get AI generated spam? It’s probably going to be better. It’s probably going to get better than those weird emails you get from somebody that, that it’s not relevant. I think in the overall I think digital experience people will have is going to be better.
And I think on the other side. On the especially specifically we, sell to marketers. So I think marketers can finally focus on what matters, right? If you think about this technology it’s an enabler. So they could really focus on their strategy, on their, on the core values of their messaging.
And now that they have that, okay, like saying it in 50 different ways, that’s solved. So you shouldn’t waste your time on that. And there’s just so much time and effort wasted on that. I think. The way I see it and describe it like is that this is like a calculator and the calculator did not replace mathematicians.
You still have to set the equation and then solve it. And then the, so the calculator is just a calculator. The marketer still needs to set this really complicated and interesting equation. And that’s where creativity comes in.
Andrew Warner: I like this answer because it’s just so you and I should have expected it I think of any word as being the AI writing platform for everything if I’m even writing a letter to my kids teacher I think any word is supposed to be the answer, but you keep bringing me back to no We are for marketers.
And more importantly, we are for performance marketers. And that’s why you are answering based on the future for marketers and for consumers of marketing content. And that’s also why now, as I go through the site, I see that the integrations don’t include just random things. They are my Google ads can be integrated.
My LinkedIn ads, you keep wanting to see, did the content that people wrote using any word. Perform the way that they want it to. Is it in line with content that has performed for them? Even if they’re writing a blog post, it’s not have they just explain the concept? It’s have they explained the concept well to the audience that they want to reach in the voice that they’re writing and everything else?
And is it likely to persuade somebody to do something marketing related? And that’s what any word keeps coming back to.
Yaniv Makover: Absolutely.
Andrew Warner: I’m going to leave it there. Thanks so much for doing this. I know we’ve been having a. Some tech issues. I will say that, you know what, here’s the thing, doing a podcast is amazing because I get to meet you, I get to know your software and have you walk me through it and frankly sometimes people’s teams walk me through it.
All amazing. The audience response is going to be other people who are either influenced by what you’ve done and are grateful to me or will open my eyes to new assets, to new features, to new something. Or maybe it’ll be some random thing like I happen to. Be in a foreign country one time and someone says, I heard that interview you did with Yaniv of any word.
I love it. Can you come over? Let’s go and hang out and they’ll open my, they’ll open me to a new experience. The challenge of podcasting is what you just saw here, Yaniv. Tech issues galore. For some reason, our connection has just been so bad and we’re using top high speed internet. Both of us were using good software.
It just happens. And then there’s going to be other issues and other issues. The reason that I’m bringing this up is I should say that. We have had these issues for years. Our team has edited, our team has published. We deal with this all the time. The biggest issues of them all is which guests and how do you get the right guests?
We’ve dealt with that. If you’re out there and you’re looking to create a podcast and you need access to this kind of a team, this kind of resources, we’d be happy to work with one good fit for our organization. We’ll do all that for you. So if you’re interested, here’s my email address, andrewatmixergy.
com. M I X E R G Y. com. And if you’re curious about the software that we’ve been talking about, it’s such a great domain. Anyword. com. Anyword. com. Go check it out and let me and Yaniv know what you think about it.