Welcome Francesco Magnocavallo to Marketing AI CEO Chats

Welcome Francesco Magnocavallo to Marketing AI CEO Chats

AIContentGen Chats with Francesco Magnocavallo, Chief Product Officer of Contents.com

Transcript of the podcast:

Scott (00:04): Hello, and welcome to  Marketing  AI CEO chats. And I’m Scott Sweeney and I’m here with my co-founder from AI content. Jen, John CA.

Francesco (00:14): Thanks, Scott. Great to be here again.

Scott (00:17): And today we’re speaking with Francesco Magnocavallo. I hope I said that, right? Francesco.

Francesco (00:25): Yeah. Scott, don’t worry. It’s a good

Scott (00:27): Line. <Laugh> and he is the chief product officer@contents.com. And today we’re gonna be talking AI marketing and learning more about what contents.com can do for you. And so thanks for joining us.

Francesco (00:44): Yeah. Thank you for having me. It’s great to be speaking with you for the public.

Scott (00:49): And so we’re gonna get right into it. We want a little bit of background first Francesco. You have a very, very interesting background looking through your LinkedIn. I saw that not only did you do some content for hears communications and luxury brands, but the dichotomy of spending 10 years in hip hop in Milan is really interesting. And I’m just wondering how all that melds into you and your AI journey and where you are now.

Francesco (01:21): Yeah, so I figure basically it’s always been about creating content. So I had the opportunity and the lack of meeting pioneers in NEP pop, like phase two. He was he’s been in Milan, been friends for years and learning, you know, very different kind of writing that was wild writing, a personal alphabet. Nobody really can replicate. And you know, that’s coming from your soul. It’s not even it’s very different. So those were crazy times getting to know this culture, this great culture, and then doing some systems. So basically you know, this was really multimedia <laugh> at mm-hmm <affirmative> and often they’re doing freestyle, just getting your soul out. And later through doing websites, I got into content and I’m fond of remembering the very early days of blogging, like years 2000, and 2001, the atmosphere was very different.

Francesco (02:21): Everybody was a developer then in blogging, it was easy to learn. You, you could study, you know, IBM stuff, materials just early days of content designs. That was great in learning your way around content. Great times then when blogs exploded, we launched the company, it was a clone of Google media and incorporated that to be companies publishing a gadget Giese model and all that stuff. And we eventually sold the company. So, I remember I launched something like one blog every month for five or six years. Those were crazy times. We had a thousand orders writing for us in all <laugh>. And then we sold the company. I did some consulting and ended up at Hurst where I spent six years doing digital strategy and launching the digital operation for six or seven websites. And I had, I think I had the privilege of launching Esquire magazine in Italy and our per so our is 150 years old brand. That’s something it’s, it’s even, you know, difficult to think about this because this there’s so much history in there. And the company now is, is got incredible infrastructure and strategy in New York. So it was very interesting times as well,

John  (03:39): Francesco I’ve worked in the custom content industry as well, and that’s basically the custom content industry is the magazine industry either you know, public magazines or, or private corporate ones. And one of the things that I found, although I’m a digital guy, I was working with those magazine editors and writers. I found the discipline of that industry to be really interesting because, to me, it was as a digital guy, almost like writing an entire website in a month when you’re changing a magazine every month. How did that discipline affect you and how you think about content?

Francesco (04:18): Yeah, I think this is a great concept indeed because the freer the ecosystem and the more possibilities you have, the more discipline you need, the more strategy. So this is very true for digital as well. What I learned from the first magazine was really journalism in the sense of not really high brow, but high-quality journalism. There was some high-brow content. We published it in Esquire magazine, but, you know, doing really premium quality stuff. And that’s something I learned the hard way with print journalism, doing digital transformation, which is a very difficult activity. Sometimes was really rough to deal with people with very different languages, different, you know, a very different mindset, different professionals com everything was very the two sides, the digital and the print merging the two sides was an incredibly demanding task.

Scott (05:20): I can see that Francesco and I think in many ways AI content generation has a lot to do with digital transformation too. So it’s not just about the tools, but it’s about the process. So so let’s, let’s kind of move into that. I don’t know if you’d agree with that, but feel free to comment on that. Tell us a little bit if you want more about your AI journey, but then let’s go in and talk a little bit about contents.com.

Francesco (05:48): Yeah. Yes. So ma Milano, our founder, and executive officer, we, we were acquaintances from you know, 10 years ago. And when he see me as a feeling for openings on the market he ended up thinking I was the right person to bring some journalistic mindset to work and design the system with the engineers. So, he chose not to have a journalistic system designed by engineers, but by a journalist. So that was you know, my point of view. And I think it’s been really rewarding work working with my data science team, and my colleagues in data science. That’s very interesting. So then we added a computational linguist and I think, by the time we started merging and having a common framework in languages, things really improved a lot. So when I speak to clients in meetings with my sales colleagues, I find that I often speak the same language because I had the same problems and the same workflows that the journalists have. And so it’s very easy to bring something that creates value for them, with automation basically.

Speaker 3 (07:06): And Francesco, what perhaps we could get into the service of the software. What are the capabilities of the software? What does it do?

Francesco (07:14): Yeah. So Scott mentioned that you need workflows. You obviously need some technology and we work with open AI by the way, but you also need talent. So what you know, the defining characteristic of contents.com is that we blend human talent with technology. So we try to get the best of both words. That’s a very basic concept in AI-assisted or human in the loop. So basically the company had a copywriting marketplace from a Francesco few years ago and it kinda went out of fashion. You know, you cannot really speak about this sort of product with DC anymore because it’s, it’s very old, but it’s coming back as a strategic point because you can have a finishing layer and and and have the machine designed by a journalist and finished by a journalist.

Francesco (08:13): So I think this is gonna be a very interesting concept if you been reading Andre in order with the magazine, that’s this article that came out just couple days ago, and this is their point. So there’s gonna be a deluge in AI content, and we don’t really know what school is gonna do in a couple of years or next year. So having a sort of blended approach where it’s AI, but it’s human definitely makes some sense. So this is a key concept. And in terms of a service we provide to the client, the client can often choose to have just a human professional working on his content, just the machine, if he wants to make it cheap and, and quick or a blend. So this is the this is something that’s very different because it’s kind of easy nowadays to just build you know, a front end on open AI or any other language model of your choice and build a little pipeline to do some pre-processing, but really to have a complex system. That I think creates a different scenario

Scott (09:21): For that’s very interesting Francesco and I, I love the approach because as we know many times you can’t, well, we, you never can just tell a machine what to write and have it come out. Perfect. Right? So you need, you need some inputs and you need some massaging. Tell us, I think everyone can understand human writing and everyone can understand machine writing. How does the blend work?

Francesco (09:56): Yeah, so it’s blended by workflows basically. So what we, we have and we gonna improve and build and invest in is newsroom workflows, basically. So a full system where there are roles, there are teams, and there’s the process of commissioning a piece commenting on a piece, reviewing the draft, approving it, and publishing. So the last mile in the system is connectors to the CMS. So you see, we currently have a WordPress and a Shopify connector. We are building an Adobe connector for an enterprise large project with a big consulting firm. And so it’s, it’s really a lot of different pieces that mix for, for to have something that’s not easy to replicate. You know, that’s, that’s kind of like our mode, our defensive mode, it’s so complex, it’s kind of a hassle. You cannot replicate it faster.

Scott (10:59): Excellent. And so as you look out at the AI landscape, where do you see the strength of contents lying as opposed to other systems?

Francesco (11:15): Yeah. I’m sure there’s some room in Europe because we got all these languages. I don’t want to speak about Africa because they got thousands of languages, but in Europe we got, we have a few billion, so that’s a lot anyway. So in this disrespect, we building native data sets and one of the characteristics is many competitors. They just translate everything from English because of large language models, they are proficient, and they are mostly proficient in English. There are a few great projects in Europe at the moment, but it’s still something that that needs to evolve a little bit. So we got French, Spanish, and Italian datasets, and the language model is working natively in those languages. So this is something where I think we can be strong because we work with datasets in four different languages at the moment. And that’s also something that takes a little time. It takes a little love to have journalists working on this. We don’t really just scrape data from the internet. Everything is, you know, manually edited and proofread and worked on.

John (12:28): Let’s go through some quick, rapid-fire questions Francesco perhaps we can ask a couple of questions about how you support the clients you know content strategy team approach around some of the following areas. How about ideas and research?

Francesco (12:50): Yes. So the idea of the founder was to have a suite of services covering the whole customer journey. So basically a content strategy journey going from media monitoring. And we got a pocket solution I think, is N cause it’s got a very strong signal-to-noise ratio. You can it doesn’t require you to spend the money of one of the enterprise or mid-market competitors, which usually costs from one or 200 to a few thousand a month. And of course, it’s working across languages with MLP. So across industries, keyword entities, fairly basic stuff. Then we got a brainstorming service which is basically a text box where you can work with a language model and do a semantics search test, which is very new. And I think this is gonna be the future of search. So not just getting 10 links, but getting, you know, a proper original answer to your search.

Francesco (14:00): So this is also where we can peek inside the mind of clients and get a little fresh data to see what’s going on. What are the needs and the pain points and the jobs to be done? Then of course the main, the main service is content creation where we can do copywriting in. As I mentioned before in assisted mixed hybrid, purely human or purely machine, we got a couple of different input styles. So one is the instruct, the open I G PT three instruct model. So it’s natural language and clients like this, a lot, the possibility of input having natural language input. I want an article like this and that they enjoy this, but the other one is purely a CEO routine. So basically you input a keyword and we do some sort of data science that zoom gap analysis with competitors and building an outline for the, for the article that’s you know, geared to, to generate organic traffic on Google.

Francesco (15:01): Then we got translations. Again, you can do this with machines or humans, and we are moving into multimodel. Of course, this is the big, the big research race at the moment between the large companies. So we’re gonna start at the beginning of September. So I don’t know when this interview is gonna be polished, but starting from September, we’re gonna sell text-to-image services. And we are in the process of refreshing the audio services. So basically we do a basic speech-to-text that’s a utility but there’s a lot going on in text-to-speech. So you can go to the very high-end Hollywood-level voiceover, or you can do many different types of services in with synthetic voices. And so I’m, I’m very interested in in this and some of the clients we began speaking about this topic in July, they very interested because that’s very glamorous that’s hype, but they can speak to clients about something that’s cool, and nobody has at the moment. So basically that’s the suite of services at

Scott (16:19): The moment. That’s very broad. I’m really impressed. And I noticed that you’re hiring for someone that’s gonna be using Dolly too very soon too.

Francesco (16:27): Yeah. We hiring for Dolly too. Yeah. <laugh> and, you know, that’s very interesting because the ideal candidate is, is somebody who knows about photography, illustration, graphic design. So it’s, it’s, it’s really, you know, it’s, it’s very, it’s, it’s very generalized across visual disciplines. And we got a, I think we got an incredible debt for Italy at the moment it’s going out next couple of weeks to our sales team. So this is very, very, very promising.

Scott (17:01): That’s very exciting. I’ve been playing with Dolly too. It’s a lot of fun. <Laugh> yeah.

Francesco (17:05): Yeah.

Scott (17:07): Excellent. John, do you have any more rapid-fire questions that you wanna follow up on, or is

John (17:12): Well, you, you covered a lot of it, Francesco. Yes. I did wonder about expansion and metrics expansion would be you know perhaps doing the general AI content generation, but then maybe for social media or something like that, you know, splitting content up. Yeah. Do you have any aspects of that?

Francesco (17:32): Yeah. You know, when you mention metrics, I think this is very interesting for the gigs of the NP gigs and the energy gigs because actually, this is evolving so fast. There’s no, there’s often no coded KPIs for energy. If you go into research, the pre-print papers, you know, there there’s, there’s no real standard at the moment. So I think this is very interesting and we working a lot on KPIs for the quality of machine translation of NLG. This goes from, you know, very basic like syntax grammar the, the flare journalistic flare, which is very difficult to, to, you know, to digitize, to compile, certainly because it’s you know, it’s, it is the most difficult to plagiarise to that there’s a lot of to similarity of translations, the quality of translation. So I think this is a very interesting area of benchmarking and having common KPIs for energy because often you see as I said before, it’s very easy to build a system, but the large language model will just give you average input.

Francesco (18:43): That’s not enough for clients if you if they’re demanding. So I remember a computational linguist. We were working this winter, relaunching the product, and this was scheduled for spring. So one day we were testing different pipelines, different data sets, and different models with opening, I had just an incredible acceleration around the end and the beginning of the year. And she, one day came into Francesco. We jumped from I don’t know about school grades in America, sorry, be patient with me. But we went from, you know, Italian of 14 years old to Italian of 20 years old. Huh. This is great Francesco. We did it. <Laugh>. Yeah. So this is really, this is happening. And I think it’s very interesting to go behind the scenes and know what the data scientists are doing, what the, what the competition linguists are working on, what these then pleasure and satisfaction.

Speaker 3 (19:40): Well, that’s great. That’s great. Thank you so much for, covering those different aspects. I really appreciate it.

Scott (19:48): So then Francesco, I have one kind of wrap-up question, and then if you want to make any final comments at the end feel free to do so, but I’d like to know you know, this is such a fast-evolving field right now, and everyone’s got all kinds of thoughts about the AI and content generation I’d like to know from you. One thing that most people believe is true about AI content generation, but you take a very contrarian view about it. And I think it’s not true at all.

Francesco (20:28): Yeah. So you see, I think a system that just helps you create an article is just some very basic task, and it doesn’t really give you a proper idea of what you can do with these models. They’re so powerful. You can do incredible things. And I think for large businesses, I mean, million URL websites a hundred million companies in, in the Italian market. So everything is different, in the United States on a global scale, but they got a different set of problems. They don’t want you to create one article for them. They want to manage a million hotel project listings. So I think that’s so much that we’ll come to the market in the next few years, because, you know, when I came to the company, I told the founder, I don’t really wanna do a high copywriting assistant, a Milano. This is so basic who cares about this? Let’s go after, you know, affiliation, let’s go after hotel businesses, let’s go after eCommerce. And so I think that lot is gonna come to the market in terms of specialized pipelines and companies.

John (21:36): Well, thank you so much for joining us, Francesco. We really appreciated the podcast. So it’s a great interview today. Yeah. Thank you very much.

Francesco (21:44): Thank you for us to me. It’s great to be here with you

John  (21:48): And thank you to our audience for joining us today. We’ll see you next time.



Marketing AI CEO Chats Welcomes Harish Kumar of CrawlQ

Marketing AI CEO Chats Welcomes Harish Kumar of CrawlQ

AIContentGen Chats with Harish Kumar, Founder of CrawlQ

Transcript of the podcast:

Scott (00:11): Hello, this is Scott Sweeney, and welcome to AI content CEO chats. Today we have Harish Kumar, founder, and CEO of CrawlQ and he’s joining us to talk about how their company is solving content teams content design issues. And this is my co-founder John Cass. 

John: Hi. Thanks Scott. Hi Harish. Thanks for joining us today.

Harish (00:39): Hi, thanks Scott and John having me here. It’s pleasure to speak to you and happy to answer your questions.

Scott (00:48): Fantastic. It’s great to have you. Thank you. So I, you know, I was, I actually curious, I know there’s an actor named Harish Kumar, are you any relation?

Harish (01:01): Well,  to be honest there are more Harish Kumar than you can imagine. <Laugh> so I’m one of them, but I’m not an actor and I’m not going to perform today. Like Harish <laugh>. I will be staying true to myself.

Scott (01:17): <Laugh> perfect. Great. Excellent. Well, I wanted to clear that up before anyone asks that question. So let’s jump right into our, some of our questions. Tell us about yourself Harish and your AI journey.

Harish (01:36): Thank you. So myself Harish I have more than 18 years of experience in the industry with data machine learning. And mostly my background is product design engineer. I think my AI journey started last in four or five years. And it was mostly because of my background with the product design engineering. I have been leading product teams in different complex environments from Ernst & Young, you know, EY, who’s a consulting company, and then big banks and be small or big. The most important roadblock that I faced in my profession was the silos between product silos, marketing and silos between sales teams. So when I started to explore this problem, the problem was deeper than you can think because none of these teams, even when I started within a marketing or within the product team they were not speaking in the same language and the root cause analysis that I did myself was that they were not clear enough on who is their target audience.

Harish (03:00): Mm-Hmm <affirmative>, they are up there going on, who, who is their audience, and that that’s the fundamental cushion that was kind of lacking. And I started thinking, okay, if we can create a common language across sales, marketing, and product, and then I realized this need to happen within marketing, within sales, within product development, because silos are everywhere. Silos are not only between these three arms but also within. And the problem was not only with the big organization, but the problem was also with the smaller companies, even a startup, even if I one person CEO, he’s thinking in a different sales marketing and product development, the three minds are working in silos and that’s a fundamental problem for many of startup failures, business failures in big organizations, projects are not delivered on time in, in budget many repercussions are happening. So I think that’s an interesting investigation that I started and underlying mechanism that I started because my background was not marketing or sales because I come from product design.

Harish (04:13): So I started thinking in terms of customers. So CustomerCentric centric approach, like what pain points my customer have. And I started applying this idea of jobs to be done by customers, understanding their pain points. Then obviously once you start talking in broader terms, then you see there are different concepts, like people are saying, I have, I know what is my ICP, ideal customer profile. Someone tells me, I know who is my target audience. Someone, someone is saying to me, I know what is my audience persona? And then someone says, okay, buyer persona. So everyone within marketing sales or product are talking in different terminology, even who is their target audience and the definitions around it. So the framework that I put around crawl queue is that you start with a broader niche within a niche. You go to sub niche and you go to micro niche and you apply jobs to be done framework to narrow down your micro niche.

Harish (05:20): And then within the context of MicroAge, I identify an ideal customer profile and I call it based on demographics. So roles, age, income, location, those kind of demographic factors, D remind within the micro niche, your ICP, then this is one set, right? The demographics mine, one set, and it is ICP. And that determines to whom you are going after. So for the sales team, for the product team, it’s very clear that we are going to this geography. These are the people with the experience. This is a group that we can study more or understand more. So you have a clear approach to whom we are going after, but that doesn’t solve the problem still. So you still need a lot of people, which are not only your ideal customer profile but also the people who are going to amplify the impact. Right?

Harish (06:21): So then I call another person and call audience persona. So audience person is more based on semantics, like the topics of interest it’s is, is more related what kind of authority or topics. And that includes everyone being an influencer in that field. So for example let’s take an example, like there, there are many people who are influencing CMO as a role, right? CMO is the role. And there are many people who are influencing and they, there are thought leader on the topics pinpoint of CS, right? So then this is audience persona. So now there is an intersection between audience persona and the ICP, your ideal customer profile. So based on demographics and based on semantics and the intersection, I call it buyer person. And that buyer person is dependent on the psychographic factors. So going into deeper into problems, desires, and outcome.

Harish (07:22): So to start with, I want to correct here that crawl queues, not an AI writing tool is a research tool is a personal building tool that starts with ICP. It helps you to do we get clear your audience persona then intersection it defines the buyer persona. And this is the buyer that you develop your customer journey from the top of the funnel, middle of the funnel, and bottom of the funnel. And once you are up with the research, the tool automatically also helps you to create content, which is highly to a stage of the, of the bio personnel are in the top of the funnel, middle of the funnel, or bottom of the funnel. I started this company in 2019. When I started, it was a very high level template with an Excel template, Google sheet with trying to ask a lot of ion with the people.

Harish (08:17): And I started working with five clients. So everything that you’ve to see in CrawlQ is created from scratch as in framework, as in a combination of different ideas from job to be done, then a background from product design engineer and try to address the needs of marketing and sales as well into it. So it’s, it, it, it was a framework. It evolved into a research tool. And then I applied artificial intelligence, NLP GPD three, and all the data that I could pull from Google, Reddi, and other sources to get the right information and to create a very structured research output that also feed dynamically to the content creation. So that’s, that’s how the whole part, and of course, it was a bit longer, but you can ask me for more specifications.

Scott (09:14):  Well, what I find interesting Harry is that point that you started at the beginning where you’re talking about those different silos and there’s no conversation amongst each of the different departments. And so that focus on the research is, is both hopefully to solve that problem across the different departments, and then also have a single mechanism for communicating within those departments as well. So that’s really the focus isn’t it, which is, the research? And then you do the the actual content creation. So I, I would suspect that most of the clients that are coming to you, you know, when they look at the software, they’re looking at the AI content. So how does that, how do you meld that in what the software does between the research and the content creation, you know, what are the outputs like how does that actually produce for the clients?

Harish (10:10): Sure. So of course I applied this software for myself also, and I tried to find my buyer persona. And it was not an easy one because you see the AI content writing as a niche has evolved, and there are many players in this niche, and it was very difficult initially to differentiate, but when they start and they come and they see a completely different way to create or understand how the content should be created. And obviously it created a filter mechanism. And also I did a lot of rework on how I wanted to target my audience. So my current focus is on brand strategist and content strategist, because those are the people who are linking pin between product team sales team and marketing team. They’re creating kind of overlays on these silos, right? These, are the people who are responsible for brand strategy, and that’s where my current focus and target is where to solve the problems of the brand strategies.

Harish (11:16): And slowly, of course, SA founders, accelerators people who are validating their business ideas or coming up with the new business ideas tool can be highly useful, but I’m very conscious of how I open up my niche and also how I market it. So my current focus right now is on the brand strategies, and I cannot, of course I created segments, but most of my customers, they are staying or working longer with me are either content strategies or business consultant or agencies who are serving multiple crimes, both for research purpose, and also for content creation.

Scott (12:04): And what, what do you think is the strength of the product with the clients that you’re, you’re, you’re, you know, you’re working with those brand strategists, what do you think is the strength for them?

Harish (12:14): The core strength of the crawl queue is the ability to pin down a specific micro niche. And the moment they realize this they open up the main differentiating value of CrawlQ, because most of the other options that are available in the market produce very generic content. Why, because most of them start with either a topic or keyboard and artificial intelligence right now is a limitation because it’s probability best model. So if you, if you give any kind of input, which is generic, then there is a more room for this massive neural network to go in tangential direction. So people are okay, they want to get their time cut or short shortened, to write something. And many people are good enough when something is generic. They’re good is when good enough is good enough for them.

Harish (13:15): But when they come to crawl queue it’s eye opener for them that how crawl queue can zoom in to a specific micro niche or a specific marketing or sales angle, and then take them through a very unique content. So it’s, it’s like it’s some upfront work that needs to be initiated because not only the keywords that you input, but more inputs about your business problem desire. And also there’s a lot of automation from the, where we were one and a half year back. And now, so you only need to supply maybe two or three inputs, and then it creates a person or ideal person for you. And obviously, you are going to humanize those inputs and rework on those inputs to make it your business specific. And once you do that, the, the results are outstanding. They’re clearly diff different from what you can get from any other alternatives, for example,

Scott (14:13): That’s great. Harry said your approach is very different than almost any of the companies that we’ve seen. I don’t see someone else starting with persona and go to a micro niche, tell us how that helps a content designer or a brand manager in terms of working with research or briefing or the actual writing optimization of content expansion, etcetera.

Harish (14:47): Right? So when, when you zoom into a kind of a team structure where brand manager is responsible for producing content streamlining the different silos, marketing sales, and product, and also I think most of the brand managers in CMO CMOs are also responsible for creating a ecosystem where they can pull all the available data and technology resources together. What I observed most of the time is there is a mad address to get more and more tools, but nobody’s brainstorming like how to get best out of that, right? The available technology. So right now we are in the face where there is hype, but as, as people settle down, we are still going back to the fundamentals. And the fundamental here is to understand the pinpoint of your audience, the old method to do this was surveys, questionnaires, focus, and group studies, but these methods are hard to scale.

Harish (15:50): And also when people try to implement those methods they’re prone to biases of how you design those discussions. So most of the teams currently, they’re not aware that we can shortcut this process by using some, smart AI tools like roll queue, right? But the moment they start working on it, they can realize that how it can collect short their time. Now, in terms of organizing the team, I would say that you would be hiring agencies or expensive market research, or you will be reverse engineering this customer problem from the mass amount of data from Google analytics, from everywhere. But in my approach, you are still back to the basics. You’re trying to understand this one particular customer you’re making a hypothesis about this. And you are validating that hypothesis by creating content. So you have a research team, you, one person who’s going to do the research.

Harish (16:44): You have three or four people who are going to create content. They are rapidly going to they’re rapidly going to create content and validate the actual signals that come from customers from reviews, from their interaction at the customer support desk, and from the emails from internal systems that they have created. And then, the more they can give feedback, look back to crawl queue in the research, the person who’s doing research or responsible for research, they can speed this process faster and create more ROI because they a don’t, they don’t have to hire expensive research marketing agencies or to market research agencies, which is by the very, very expensive you see to collect that kind of consumer insights and data on that level is, is a very difficult job and very expensive job. So they don’t need to hire those people.

Harish (17:36): They can work with CrawlQ, but someone who is a domain expert in that area is needed to validate those inputs and also to validate the market feedback. Once you have that function sorted out, right then rest is very automated because you can hire as many as virtual assistant. They don’t need to think about again and again, who is their neat micro niche or ideal persona. Everything is set to preset as a, as, as research. So you can create multiple preset or research. You can clone them, you can AB test them. You can apply different marketing angles to the different stages of the customer journey. So I, I think it’ll be great cost reduction because they can consolidate this research function into one person, and then they can scale the process of content creation by hiring virtual assistant, which need not to reinvent the wheel, but they just follow the, the, the research that is already there. And there is an internal AI within crawl queue, which take care of your research and the content creation. So there’s a linking pain, I call it Athena. So every time you can train Athena is almost like your virtual AI assistant, which makes sure that all the research that is done by Athena herself based on your initial input are also connected to the output. And she’s writing intelligently on all the information that is there and validated by your team.

Scott (19:03): So is there some metrics and dashboard that your customers receive that they’re able to review and maybe provide human input in terms of the waiting of the importance of the data that’s coming back in?

Harish (19:22): Sure. So right now we, we are still developing other metrics, but mm-hmm, <affirmative> the most important KPI right now is every content that you produce from crawl queue, you get in a score, how much it is semantically related and co with your initial audience research. And there are some parameters, of course you can play around, but the, the, the better the score, I mean, if score is a hundred percent, then you are almost repeating your research in your content, right? And the score is zero. That means your content doesn’t make sense with your with your initial research, but the content is good enough. Let’s say 75. And about then I call it. You are getting just from your Fred I, well, Fred, your audience is a thousand audience. So, Fred, Fred is a person who is, who has peers. He wants results. He has desires. And if your score is more than 75, then you are going to get definite definite just from, from your Fred, this how we play around with single metric right now. And that’s my goal, also not to create multiple metric and confuse user, but play around with one single metric and if necessary, try to create additional signals, which form the computation or explanation of this single metric. So I still want to drive a single metric in terms of ensuring that what you create as an output is very consistent and streamlined with your audience persona.

Scott (21:02): Excellent. Good. Thank you for that explanation. It’s very unique and I think it has a lot of value for the target audiences that you’re talking about. I have one question that I like to ask because it usually spurs some really great thought and ideas. And it’s this, what’s one thing that most PE people believe is true about AI content generation, which you don’t agree with whatsoever. You think it’s false,

Harish (21:37): Right? Right. most people who use AI, content writers, believe that AI can write unique content or create unique information, which I don’t think is true because all AI models are trained on an existing set of information. So unless you heavily I intervene with this process or humanize your input. You cannot create unique content because if you start with one topic, whatever you feed into it, it cannot generate unique content because it is already trained on a vast amount of internet data. So regardless of this perception, people are happy what content they get, but they are just diluting the value on the internet because there’s already such a content existing there. And that’s where this neural network has learned this. So my approach to this is to really break at every point of entry your data into this neural network, where you’re calling this machine big machine to inject your interventions, and more, you do more possible that you get an outcome, which is unique.

Scott (22:56): That makes absolute sense. You, you’re still including the, the human in that element. So, well, thank you. Thank you so much for joining us, Harry. You know, we really appreciate you joining us on the AI marketing CEO chats podcast today.

Harish (23:15): It’s my pleasure to talk to you, both of you

Scott (23:19): And thank you to the audience for supporting us, and we’ll see you the next time.

Scott (23:24): Take care,






Marketing AI CEO Chats with Jeff Coyle of MarketMuse

Marketing AI CEO Chats with Jeff Coyle of MarketMuse

Let’s chat AI Marketing. Welcome, Jeff Coyle of MarketMuse!

Transcript of Marketing AI CEO Chat with Jeff Coyle of MarketMuse.

Scott: Good morning. This is Scott Sweeney and I’m with my co-founder John CA welcome to the AIContentGen video blog. And today we’re talking to AI content generation companies. And today we have Jeff Coyle with us from MarketMuse. He’s the co-founder and chief strategy officer of MarketMuse. Welcome, Jeff.

Jeff: Oh, thanks. I look forward to our discussion today and also really your shirt and the logo.

Scott: Hey, thanks a lot. Awesome. You know as you probably know both myself and John are background in a long time in marketing, so we’ve bootstrapped a lot of what we do and we created this logo. I love it ourselves. So, yeah, so it’s a lot of fun. Thanks for mentioning that.  Jeff, we wanna start out by just finding out a little bit about yourself and your background. You wanna tell us a little bit about yourself?

Jeff: Yeah, sure. So I have been in the content strategy lead gen search space for now 24 years. I went to Georgia Tech for computer science, my background’s in computer science with a specialization in usability. So usability theory. And I also worked on some of the earliest search engine information retrieval work during my time there. Wow. I worked at a company called knowledge storm from 2000 to 2007. We were one of the first people who were selling leads to software companies. So we were convincing IBMs and Dells of the world to have content on their sites. Wow. Where they weren’t even, you know, they were like digitizing, like scanning brochures was like a big stretch. Right. But how did we generate leads with that? How do we market across the buyer journey when nobody even were thinking about that?

Jeff: So we were selling millions of leads you know, a month to software companies. And I managed in-house and I was a product manager for them. We were acquired in 2007 by tech target who may be familiar with the major business to business technology and certain niche B to C publishers who sold leads to solve our companies primarily. And then also has now become a data company where I led their in-house team from search content, traffic, anything that was people going to a website and then turning into something good was you know, managed by my team there. When I left there to go work at a private equity firm, right before that time I met my now co-founder AKI who had built the earliest technology for tech for market news. And it was technology that really focused on natural language processing and topic modeling.

Jeff: And it was focused on really telling the story about what it means to be an expert on a concept. And that was something that I had been looking for for a very long time. And it worked and it cut a, you know, 40-hour process down to four minutes. And this was now over seven years ago. When I went and had, when I left tech target few, few months into another gig, I AKI reached out and said he was really gonna take this to market and wondered if I wanted to be, a late co-founder of market news. And then the rest is history jumped right off that cliff landed and bounced a few times. And now we have, you know kind of a, we created the market for content optimization and now our continuing to create for the content strategy and content intelligence markets that kind of don’t still exist.

Scott: Wow. Yeah. Thanks so much. Well, that’s quite a background. You know I, I could tell you some stories about myself in the pre-internet days, even too. Yeah. <Laugh>

Jeff: You can still find some of that stuff if you look hard enough

Scott: Doing it for a real long time. Absolutely. That’s great. What’s one thing I found doing a little research on your background, Jeff, is that you actually are a brewer and have a tap room.

Jeff): Ah, yes. <Laugh> so, yeah, I’m the co-founder of a silver bluff brewing company. It’s a microbrewery based in south Georgia in Brunswick, Georgia, the golden ISS. So I’m the co-founder and did all the branding identity work. And I am, don’t spend a huge amount of my actual physical time because when you’re, you know, a SAS company eats up the majority, however, yeah. The business runs really well. We have an amazing team there. US Open 2020 silver medal winners. So we’re not just fooling around in the garage. We’ve got, a pretty significant organization and operation going there with a really talented team.

Scott: So that’s great.

Jeff: I love, I love beer and brew and it’s, it’s, it’s amazing, my it’s, it’s 95% sanitation and 5% everything else. If you’ve ever known anyone, who’s a brother, if you don’t like to clean, you should just stick to drinking. That’s what I say. <Laugh>

Scott: <Laugh>, that’s great. Super actually, it’s kind of interesting. I just ordered a keg for a very large family party this Saturday for my father-in-law’s turning 90 and oh, wow. Yeah,

Jeff: What was it? You’re in, you’re in Northeast. So it’s gotta be

Scott: Yeah, yeah. What kinda beer?

Jeff: Yeah. Right. I gotta ask

Scott: Ganett of course. All right,

Jeff: Cool. I actually was in a call that’s fun, fun aside tangent. I was on a call early on in fundraising for market use live. And we were at the venture capital firm or private equity firm. I forget who had been the major investor in NA GSET when they reached up. No kidding.

Scott: Oh,

Jeff: So yeah. And there, if you go look it up, I don’t remember exactly who they were, but you look up VC NA against it. It probably is like 2014, the 16 timeframes they actually had funding from someone who also funds SA companies, which is just super unique.

Scott: That’s crazy. I actually met the CFO on Cape Cod just going into a beer store on the way to, you know, going into where we go for the summer. And he just started telling me about it and I have a son, in Rhode Island. So they’ve, they’ve done a great rebrand, really excited about

Jeff: That. Huge, huge rebrand. Yeah. It’s good standard around water.

Scott: So let’s get into this you know, MarketMuse. You’ve been, you guys are, you know, probably old timers in this industry now, right? Oh yeah. And so we have like questions. John, do you wanna kick off question number one for Jeff, or I can

John: Absolutely. Absolutely. So so what, what exactly does the software do?

Jeff: Great question. So we work with the entire content life cycle. So we’re able to analyze a topic basically and say whether it, what does it mean to be an expert on that topic? Right. And so then we apply that to all the most common workflows that content teams, content strategists, and GMs and editor inchi editors in chief, but also SEOs run into in their life. Right. And we don’t want them doing them manually. So we’re able to look at a page and say where it maybe has gaps from a lens of quality and comprehensiveness. It’s not exhibiting signals of expertise and give insights on how to improve an existing page, or if you haven’t begun authoring a page we have the ability to create a content brief. But it’s not just a report which a lot of the industry has kind of evolved.

Jeff: And, you know, when we first launched our initial content brief, there, there was no content briefs in as software in the market. Now there are 50 different things calling it 50 different briefs. Right. so one thing I always tell folks is to look at what is that brief, how customized is, is it just a report that some other people are using it’s like inside the application, or is it a brief we’re able to give you a way to build your own briefs that are customized. We’ll also help you build them using our customization, we have custom forms. You can do a managed brief or even more specific customization. We have solutions that analyze the competitive landscape for a particular term from a lens of quality, who’s got great high-quality content that doesn’t also have keyword ideation solutions built-in questions, analysis, internal and external linking recommendations.

Jeff: And then our premium offering analyzes an entire site and understands where it has strengths, weaknesses, and competitive differentiation. So that’s where, you know, the important decisions are made. A lot of folks want to jump to the end and get content, but maybe they shouldn’t even have created it in the first place. Or it’s not gonna have an impact, even if it’s the best page ever. I like to say this one a lot, but cuz I have a visual layout. It is always near me as I can go write the best brand new iPhone review and I can go throw it on John CAEs, blog.com and it could be the best thing in the world. It’s not gonna impact my business at all. Right. I go throw the same review on CNET and it’s gonna own, and it’s not just because of links it’s because I have exhibited expertise.

Jeff: I have exhibited topic authority, which we represent as breadth and depth of coverage, quality of coverage, comprehensiveness exhibition on particular intents that I have written about reviews. I’ve written about phones, I’ve written about electronics, so I deserve it. Right. a lot of those folks are really writing whatever, not semantically related to anything I’ve ever done. And the expectation is that one page on a PA on a topic is enough to get it done and it’s not reality. So we’re the only in-market solution for content intelligence and strategy that tells teams how much content they should create on topics. How hard’s it gonna be? So it effectively gives you know, a business a real predictive return on investment and predictive expectations of what that investment should be in the first place. So I need to go write 50 articles about you know, promotional tap handles in order to own that topic.

Jeff: Right? Well, am I willing to invest in that or not? Right. Those are the types of questions that a lot of teams don’t even know to ask. Because the industry is this industry from a writing perspective is very much run by the mass writing and SEO user profile. But the real tough decision-making is made by the GMs, by the editors in chief who have to decide what they’re gonna invest in in the first place. And that’s where briefs are critical, cuz they create that source of truth. So the GM says, I need an article about the best phone conductive headphones, right? They don’t just say that to a writer and that’s it. If they do that, first of all, the writer’s gonna be completely inefficient. They’re gonna go, okay, well maybe I can use this G B T three thing over here and then they send something back and the GM’s like, that’s not what I wanted. Right. And that feedback loop is devastating to teams. So our goal as a business is to improve your hit rate on picking what to write, to know how much to write, and also improve the communications between decision-makers, writers, and SEOs. That’s where the real loss the unknown losses happen in our space. And that’s what we’re looking to. So

John: I remember going to the basement of the Arlington public library a couple of years ago and seeing ake speak about you know, his new tool and which, which was sort of focused on the topical SEO stuff at the time. And it was kind of interesting cuz I’ve been working in SEO for 20 years or so. You know, I was with port interactive with Ian Laurie on, on the west coast. Right. That

Jeff: Very

John: Well mm-hmm <affirmative> and I think what struck me is the time was that it was edging towards how Google was changing. But I, I think a big factor of that is, you know, you talk about content strategists or content designers it’s what do you need to write about? I mean, I, I think that’s what we’re getting at here with some of these new tools that the AI content generation industry is providing like yourselves, right? Is helping the companies to understand what you need to write about, right?

Jeff: Yep. Well, no, you’ve nailed it. And, and it’s really, it’s, that’s the evolution. I think that the next phase of evolution for this market is people getting to the decision, making processes and kind of getting out of the this ground swell or the excitement about kind of cheating or <laugh> gaming a system. It’s just, that it’s not a path to longevity. And that has always been the case, but the SEO world, as you know, you’ve been in this space you know right, you know, around probably injured it right around the same time is, is it cycles, it cycles with new technology will come out, then it breaks into how can we use it to game the system then it’s, how can we build real sustainable workflows for business? And then new technology will come out and that same happens.

Jeff: And we have just seen this all happen with product content over the past few years with the Amazon affiliate boom and massive investments in that. And then you’ve seen, you know, at the end of last year, the crash from product reviews, update where if you aren’t actually reviewing the products and you, you write a review for it, we go and get ya. Right. and then you see, you’re going to see that again, there’s a huge ground swell in generated content. That’s not checked and then you’re gonna see police of that ensemble approaches to detection and ensemble approaches to detection are already in place in house in various shapes and forms. And you’re gonna see what the impact of that is. And you know, it’s gonna be tough when people are using outsource writing professionals who are using these types of technologies, who knows what’s gonna happen.

Jeff: Right. but that’s, so the ebb and flow aren’t unusual here. So in my, in my situation, you know, with market use, we’re looking at the entire content life cycle, all the decisions that get made each one can either be manual or have some automation or some artificial intelligence, automation components to increase performance and efficiency and impacting each stage has always been our focus. And if we can improve your hit rate on what, what you said, John decision making, I like to think of it when we were talking about baseball and, and batting average, and then also slugging percentage, right? So if more of your content you publish or the content you touch is successful, whatever success means to you, let’s say you’re the, and the average team that we profile is about 10% efficient, right? So one article out of 10 does what they expect it to. That’s terrible. That’s why content teams are you know, considered to be like some sort of voodoo, right? Let’s say that’s 30, 40% efficient. Right. And that changes everything for that team. That’s huge. I mean, that changed everything for that team.

Scott: Right. Jeff, you mentioned something that tickled my ears as because as a former CMO and also, you know just, I consult with many different companies on business in general, they’re looking for ROI and you said predictive ROI. Can you just expand on that a little bit more?

Jeff: Yeah, sure. I can give, you know, piles of examples, but the core value of market use is predictive ROI for content. So being able to say how much content needs to be created on a topic to either maintain or grow your presence and your authority on a concept gives you the basic infrastructure to be able to ask for budget and answer the question. Why, why for content, instead of just saying nothing relates to data, I mean, which is most of the case, or you’re fighting rankings, or you’re doing tail wagging the dog, you know, justification where you’re like I am to update this page and had words to it. Right. Well, what if that won’t have that impact, right? How much content do we need to create? How much competitive advantage have all the other aspects of the CMOs efforts your efforts impacted our business?

Jeff: That’s the branding, the identity, the off-page factors, links, and just the power of the site. Right? And so having all those things distilled into a topic, specific metrics can tell us information, like I just described it can say, okay, well, I mean, here’s a great example, a B2B technology company that work with I use this example a lot but has two product lines and they want to grow leads 30% to each product line. Okay. Well, a typical B2B technology company, what happens, you get 50,000, you’ll get 50,000, but that’s not the reality of content. And that’s where businesses do it wrong. And so what market use can say is, well, to grow 30% in this one, the segment’s gonna cost you eight times as much as the other one, cuz you don’t have an existing competitive advantage. So you gotta write 150 articles on this and update 80. Well, for this one, you only have to create 30, right? So measuring and managing and predicting return on investment for content changes the way that CMOs both reports define and then justify their investments. So I know for example, what the content item that Steve jet, my head content strategist should write next on our blog. It’s gonna have the biggest impact on our business. And having that knowledge is the ultimate power for content teams.

Scott: Great. Thanks. Yep. That sounds that’s, that’s pretty exciting. Mm-Hmm <affirmative> so I think you gave us a really good overview. I mean it’s very comprehensive. Is there one main focus that your company really what’s does a sweet spot for, for market news?

Jeff: Yeah, I think it’s it. Well, it’s role dependent is key and that’s really tough. That’s why it’s tough to sell into this world of content and strategy and SEO and and, and writers is what a writer loves. Isn’t what the CMO loves. All right. So you see all these products that you’ve profiled with this visualization at, you know, visualizations that you do. And I love those, but you can’t sell the same product to the CMO as you do to the writer. They’re just, they’re not looking for the same stuff. Right? so from my perspective, I like to think of the aha moments with market muse for each role. And so if I’m a writer I’m writing and by the way, if you want your writers to write what don’t, you want them to build great narratives, you want them to build and focus on production value.

Jeff: What don’t you want writers to do keyword research <laugh> you don’t want your writers necessarily worrying about SEO. You want the data they have at their disposal to naturally yield and optimize page. That’s where a brief comes in. That’s where data about competitive data. How can I differentiate my page? So those that drive against in our case debriefs and the applications are really built for writers. The SEO’s aha moment is all the stuff you do manually. I used to do it manually. I have lots of tears to cry. And so when an SEO sees a 10-hour workflow getting knocked down to a minute, that’s their moment. And that’s really where the page-level optimization goes from a strategist or editor’s perspective. The aha moment for us is that personalized metric for difficulty. How hard is it gonna be for us to grow on this topic? What pages should I update? So they can give direction that’s back to data, not just backed with subjectivity. So where we focus, we’re focused on decision-makers, cuz they got the budgets <laugh> and then we’re focused on providing a great writing and SEO experience. Terrific. Mm-hmm <affirmative> good.

John: So, Jeff you know, how do you support the client’s content design team’s approach in, in some of those areas for the, you know, the content strategy approach, you’ve talked a little, you talked a lot about research and ideas and also about the briefing. I don’t know if you’ve anything else to add there, but what about perhaps writing optimization expansion metrics, some of those other factors in the, in the whole process?

Jeff: So those the kind of, well, we have an on-demand basically per me, an on-demand content inventory or topic inventory or keyword inventory that gives you all these decision-making capabilities, you can create content plans based on any slice and dice filter data, data point. So I can say, for example, you know, what are the five pages that I should update on my site? Or maybe the five pages from this section of my site that are gonna have the biggest impact on performance. I can turn that into either a content brief for each one or I can actually go do the work myself and doing the work myself inside the applications would be analyzing the page. How can I optimize it, analyzing the competitive landscape? What’s the haves and have nots of all my competitors here. Where should I add internal links? So it’s those manual workflows.

Jeff: All those can get also distilled in a brief, which can be sent to a writer in house or external. And those are really where our core areas are. We’ve been in and out of the generation market. And we are considering what are ways that we can do that more appropriately for our real market, which is the kind of business decision makers where generation has to be woven into a workflow to as almost an assistant, not a replacement because that is the future. And that’s our hypothesis is the future is how can natural language processing and generation components be woven into the entire workflow so that it is the ultimate you know, writer’s block defender, it’s the ultimate kind of ideation component, but it’s not focused on draft development.

Scott: Got it

John: Great, great. Super. So Jeff, this has been great. It’s been wonderful to have the opportunity to learn a bit more about the company and ask you some questions, and see your success in brewing, 

Scott: Which Is excellent. You happen to have a tap handle handy. Oh boy, of your brews

Jeff: I do, here we go. This is my Mexican Lager, this is our flagship. And that was bluff.

Scott: And you buy that at your beer garden. Is that right? 

Jeff: Just, you can get that in the beer garden or the tap room cool, right. About to have our second anniversary open on July 1st. So it’s yeah. Awesome. It’s a cool, cool project is definitely a passion project. And one that is, is super special. Mark amuse is doing some amazing things as well. And I think, you know, to be able to take kind of the two things that I’ve the most passion for and turn them into businesses has been a fun part of my life.

Scot: Congratulations. That’s awesome. I have one final question for you. And it’s one that I love to ask people. It’s it’s what’s one thing about AI content generation that most people believe is true, but you think is not

Jeff: All right. Good question. One thing would be that God, I have so many things but, one thing is that there are methodologies of the past that involved copying competitors, right? Or aggregation or stitching of competitive information in a generation. And those, there’s still a perception that one can rush to the end of the content process and actually get a draft and edit it more efficiently, more efficiently, all in than doing it with a repeatable process. That is still the myth, the myth of. And I’ve got this thing that is now going to add efficiency without having thought through the process. I’ve seen it work so few times in practice that it, grinds my gears and I wish for folks to really do the analysis for themselves, if they are using any sort of software, any sort of generation, do the analysis of understanding how much content do we create, how much time did we actually touch it, how much resource the true cost of content is one. And then the true cost of an effective page of content is two. So the biggest myth I have is how much content actually costs.

Scott: Great. Thank you. I appreciate that. Very, very insightful.

John: Well, thank you, Jeff. We really appreciate you joining us today. And thanks for joining us on the AI content video podcast, and also thank you to the audience for supporting us. We’ll see you next time.

Scott: Great. Pleasure. See you take care. Yeah.