Content Marketing Plan Created by AI? Interview with Brandon @ Ceralytics

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Alexander Ferguson 0:00
Artificial intelligence machine learning, these emerging technologies are changing the way we live, work and do business in the world for the better. How is AI actually being applied in business today, though? Let’s look at content marketing. This week on UpTech Report, I share my interview with Brandon from Ceralytics, who’s intelligent platform basically tells a marketer exactly what content they should be creating to generate more traffic and sales. I asked him in the interview, Why can’t someone just do it manually? And also how the technology behind it works? Let’s jump in. With me here, I have Brandon Anderson with Sara Linux, man, thank you so much for joining me, why don’t you give me the quick 32nd spiel? What is senolytics? What

Brandon Andersen 0:45
is your product? You bet. So Ceralytics is a content intelligence platform. And what it really does is it takes the guessing out of content marketing. So what we’re doing, were identifying what topics actually work on your site, what topics your clients and your prospects actually care about? And what topics your competitors are having success with, that you need to use on your own website to get the success that they are and even surpass them?

Alexander Ferguson 1:11
Couldn’t someone say, then well, I can kind of do that with my team already. And we can just look at our competition, what they’re doing, we can look at our content, do the research. So why would I even need your product?

Unknown Speaker 1:21
Absolutely. And you can’t, you absolutely can. And this is something that has been done by agencies for basically, as long as websites have been around, agencies have been trying to get to this information. And the way that they do it is they usually take some poor summer intern, they say, Okay, your job is to read every single page of content here. And what you’re going to do is keep an Excel spreadsheet, but the page but what it’s about, and then you’re going to make this whole spreadsheet of every single page that we have, sometimes be like, you know, a few 1000 pages takes though, for an intern the entire summer to do by the end of the summer, they now have a categorized audit of all their site content. And then they start putting metrics to it. And they say, Okay, well, you know, based off of this, they do pivot tables, and they do that. Alright, cool. But what they, you know, don’t realize that as well, this audit started three months ago. So everything’s already out of date. So by the time they have actionable data, it’s out of date. So that’s, that’s the thing that we’re filling it is we’re saying, Yeah, you could do it, you actually can do great. And if you’re small, if you’re a tiny company, do it by hand, that’s fine. Do it, like, take take a couple weeks and do it. But if you’re a mid sized company, if you’re a larger company, and you need to do this at scale, and you need to do it timely, this is the way to do it.

Alexander Ferguson 2:40
In today’s age, you have to be able to quickly modify and change because your competition is doing the same thing. So then question is, obviously, this is automated, that’s how it’s able to happen so fast, you’re able to do all the research and correlate it and provide them this feedback, this insight to your clients. How is AI artificial intelligence, machine learning playing a role in your product?

Unknown Speaker 3:04
Okay, so there are two major components where AI comes in. First is just identifying what topics are pages about. What it basically is, is it uses natural language processing and natural language processing, basically goes through a page of content, whatever you give it, and it’s going to identify what different things are within the page. So sometimes just just looking for things like nouns and verbs and all that, well, what natural language processing that we use does is it actually goes in and identifies What’s the thing that this is actually about. And so it’s keeping track as a read through it says, okay, you know, I recognize that there are a few things that we’re talking about here, here are some ideas that are very similar. And it pulls all that together and says, okay, at the end, I think that this was really about three, these three or four topics, like, that’s what I’m going to put in front of you and say, This is what this piece of content was actually about. And so that’s what we use the natural language processing for. Now, interestingly, natural language processing has been around for a very, very long time. And it’s really become commoditized. And one of the places where you can get it from I mean, that’s like, that’s a throw any stones here, but IBM has IBM Watson and Watson is spectacular, and it won Jeopardy and you know, it made like a big impact. And so they actually have it available where you can just feed Watson information, it’ll give you information back. And so for us, we said, Wow, that makes a lot of sense. So we went with Watson and that became our our calling card for a while is hey, you know, we use Watson, we use lots of use Watson. What was great about it is that we were getting results back really quickly. What’s it’s like super fast and actually very affordable. The bad thing was the results were not great. And for us, that proved a challenge. So even though you have something like IBM and IBM Watson doing this information, they are made to basically handle generic information, it’s generic to them, they don’t care if you’re giving them an encyclopedia page or a website or a bunch of comments from, from Yelp, they treat it all the same. And what we realized is that websites are very different. And we actually ended up taking the data that Watson brings back to us. And we have to do a lot of massaging in terms of the algorithm itself to say, Okay, we know what web pages are. And we know how people read web pages. So before we even give Watson anything, we need to actually give Watson some rules on every single page. And you can imagine how hard that is because every site is different. So we use that process first, and then we get natural language, then we bring it back. So there’s like a whole step to do that. So that’s actually just the first place where we use AI. The second step is for your competition. So for your competitors, we don’t have access to their Google Analytics, which we did, we don’t. But we still want to give you actionable insights about what your competitors are doing and where they’re having success. Because we don’t have a cut and dry place just to pull information from and say, oh, yeah, this works. This doesn’t. We had a, you know, a big process we were going through at the beginning of the company, of identifying what things actually relate to traffic. So we’re looking at things like okay, well, how much like, what about a keyword that has high volume, that they’re ranking really well, for? What kind of traffic does that drive? It’s, we built a model for that. And then what about social shares? You know, if you have social shares that are brand new, yeah, that’s currently driving traffic, but you have 2000 social shares on a post, that’s 12 years old are, you know, probably 12, but maybe five years old, that’s probably not going to be doing much for you right now. You know, that’s, that’s not a post that is going to be driving traffic right now from social. So that social signal is kind of antiquated. We don’t want to we don’t want to pull from that. So we basically had to teach this thing and say, Hey, depending on when and where things are shared, and where they rank for certain things and all this information, we then say, alright, based off of that model, here is how much traffic we think this particular page or list in our case topic, is that getting. So those are the two places natural language processing, and then looking at the competitor to competitive data.

Alexander Ferguson 7:33
Thank you, again, so much for sharing this great insight for more information, where can people go to and who’s the best type of clientele for you?

Unknown Speaker 7:41
You can go to Sarah linux.com You’ll find us there. And for our clientele. i We range everywhere from agencies work with us to help with their process. We have a lot of success with b2b companies, anybody who has content that they are creating to become thought leaders. We are the tool that you need to identify what you should be creating, when, where and why.

Alexander Ferguson 8:03
That concludes the audio version of this episode. To see the original and more visit our UpTech Report YouTube channel. If you know a tech company, we should interview you can nominate them at UpTech report.com. Or if you just prefer to listen, make sure you’re subscribed to this series on Apple podcasts, Spotify or your favorite podcasting app.