AI’s Revolutionary Impact on the eCommerce World | Valon Xhafa

Valon Xhafa

Matt Edmundson: [00:00:00] Well, hello and welcome to the e-Commerce Podcast with me, your host, Matt Edmundson. Now, this is a show all about helping you deliver e-commerce. Wow. Yes, it is. And to help us do just that today we are chatting again with the mesmerizing. And talented, uh, Valon from Bahamics. We're going to be talking about AI and how it's disrupting the whole world of site traffic.

So you're not going to want to miss this one. Is AI still as cool as everybody thought it was a few weeks ago? We just don't know. We're going to get into all of that. But before I do, a warm welcome to you. If this is your first time here with us on the show, we just chat about eCommerce and all things to do with how to grow online businesses like you.

I am an eCommerce entrepreneur. I have my own online businesses and so I'm very fascinated by this whole topic. And to help you we do this [00:01:00] show, but of course we've also got the newsletter which you can subscribe to on the website at ecommercepodcast. net. Every week we send out to you the show notes and the links from the show, as well as some other good stuff which is coming your way.

More details soon, so stay tuned, make sure you subscribe and I'll let you know more about that as we get closer to it. Now Let's talk about Valon, who previously worked as an AI scientist at Google, which, let's be real, not many of us have done, and he's worked at other research institutes developing sophisticated AI techniques and algorithms.

Whatever that all means, right? Now, Valen is always looking for innovative methods to use AI to improve the online shopping experience at his company, Behamex, which is a great company. Do check it out. Behamex. com. Now, it is, uh, 18 months since Valen was last on the show. January 2023, we released Behamex.

Uh, the episode, Valum, when we were talking [00:02:00] again about AI and how it works with abandonment, uh, car abandonment and all that sort of good stuff. Uh, but today, let's carry on that conversation. Welcome back to the show. Good to have you on, man. How are you doing? I'm good.

Valon Xhafa: Uh, Hey Matt, thanks for having me. Great. Doing great. Enjoying the whole, um, huge interest, huge boom in, in AI since we last spoke. Um, now that I remember it like January of 2023, a pivotal moment in AI, for sure. Um, a lot of great things happened during that time. And I think that that month, that month is something that it's probably going to go down in history as a turning point in terms of like interest in AI.

And the primary reason was that AI before used to be like this cool thing, great thing, you know, but mostly in the back end. The normal show, the average show would never actually see how that works and the impact of it. Well, probably like [00:03:00] indirectly, but not like so directly, you know, so, uh, it was a great, a great, a great turn point for sure.

And then, you know, like the release of chat GPT and all the different language models, um, you know, like this has a huge impact to, you know, like reach a huge, huge mass of, of, you know, like people to see that actually AI has a huge impact. So, um, and this part, a huge interest all over like different industries, pretty much, which is, which is great.

Right. So, um, we're happy to ride that wave, if you can say so. Um, we saw a huge interest and a lot of expectations. Uh, but yeah, very interesting. Yeah, it's

Matt Edmundson: fascinating, isn't it? I mean, I, you know, January, 2023. That was turning point in AI, I think predominantly because that was when our episode was released.

I think we single handedly changed, you know, the whole nation industry around AI, but that's okay. [00:04:00] If only that was true, right? Um, but it's, it is interesting the journey that we have come on with AI and how it started off with this huge bang. And everybody was talking about it. Everyone still is talking about it.

It doesn't seem to have gone anywhere. Now, I know that when we were chatting before we hit the record button, um, you were like, I hope AI doesn't go the way cryptocurrency goes. What do you mean by that? Because I think this is a really interesting idea.

Valon Xhafa: A lot of, a lot of, uh, hypes took place in the past, right?

We have, uh, we had like the metaverse, which didn't really last as long, which is great. Um, we had a lot of like other hypes in the past, you know, like remember, uh, I was like 2015, 2016, the chatbot era, where everyone was like fascinated with chatbots, uh, but they couldn't actually deliver because the AI was not there yet.

So it literally took us like almost a decade. 10 years in research and [00:05:00] development to be able to come to a stage where chatbots can actually formulate Good questions or can formulate cohesive questions, you know, they are still not at the level that Most people expect to be

yeah,

Valon Xhafa: but they are far more superior So literally in a nutshell the quality of chatbots that we have right now is a quality that clients expected back in 2015 and 16.

Yeah, right So it took us a long time and it took us like, uh, like to, to actually perform a miracle in terms of AI to be able to pull something off so that we can gain the interest from, um, the customer and the industry back to where we are. So what I mean by that is that whenever there is a hype, It's usually super hyped, um, and then expectations are risen, but then, um, we're, we're assuming the industry starts to realize that actually, um, expectations are not met.

Yeah.

Valon Xhafa: And, [00:06:00] uh, the interests are to, uh, fade away. Right. I don't expect that AI can do that. The hype is going to land where crypto and blockchain landed because when it comes to AI, there is a huge impact all over the world in different industries. The impact is clear. It's measurable.

And

Valon Xhafa: it's not just transactional, you know.

Um, so, uh, it's not gonna, you know, like it's not going to land where it used to be before 2023. But it's going to go on waves, right? And these waves are going to be directly, you know, like, push by innovations and new tech that's going to come out every single day, right? So we see this, like, even if you, for example, one interesting thing is that if you, if you, for example, even if you just go to Google Trends and search like AI, you'll be able to see this trend.

And there were like some kind of like waves. And then there was some increase in these waves. And these particular increases on the trend. [00:07:00] of users searching for that, they came particularly because something was released, something new was released, a new model or a new tech or a new company or something, right?

So the great part is that, uh, the whole, uh, investment community, uh, VCs, they are like, um, putting a lot of money into development, which is great. It didn't used to be like this at this scale, uh, before pandemic. So this interest is going to lead to new innovations, which hopefully is going to like push to newer and newer applications in different industries, like we're doing it here with, uh, with Behemix and eCommerce.

Matt Edmundson: So what, um, what sort of new innovations do you see on the horizon? I mean, the time of recording, it's July 24. Um, where do you see it going the next sort of, I don't know, 6 12 months? Can we predict that far in the future where AI is concerned, or is it more, we're struggling to predict the next 6 12 minutes, let alone the next 6 12 months?

Valon Xhafa: Yeah, for [00:08:00] sure. I mean, like, statistically, and based on where the needs are, based on where the constraints are, it's definitely going to be focused on, um, on building, um, language models with higher accuracy. This is where the focus is right now. Um, and not only that, but also building language models that can, um, you know, like spit out words, uh, faster than usual.

Yeah. And they are more like cost effective. This is gonna be huge demand. Um, the reason why is this, the case is that the existing state of, of, of training and building, uh, language models, running them on, on, on cloud is, uh, highly ineffective. It's not cost effective, it's not financially, it doesn't make financial sense in the long run.

If there are no innovations to improve that, right? To put into perspective, for example, like just a few months ago, you needed like an NVIDIA GPU, which costs like two grand on average, you know, like bare minimum, to run a [00:09:00] language model that can, um, that can process a prompt within, you know, like a minute.

That's, that's a scale and this scale is literally, this scale is like unaffordable. Like think about like, how many prompts that they handle per day, like millions of prompts.

Yeah.

Valon Xhafa: So the majority of these language model companies, they're actually losing money. You know, by being able to process and, uh, you know, like handle all these requests because the status, the state of the language models and the hardware is not optimized yet.

So in the next few months, probably a year or even two years, the whole focus is going to be on optimizing these, making these models more efficient so that we can have these for the long run. Otherwise, this is not going to make sense financially. Right.

Matt Edmundson: That's really interesting. I've not heard of that site.

I've not thought about costs of actually me typing [00:10:00] something into ChatGPT and ChatGPT giving me the answer. I've not thought about how much it costs them. Especially because, you know, very expensive, very expensive, very expensive, which is intriguing, isn't it? So, I mean, you're, I mean, Bahamux is an AI company, you're using AI technology, you've worked with Google and other companies, you know about AI, you've incorporated this into your product.

Um, into your own company. So how have you dealt with this technology barrier yourself? And if the cost to entry is significantly high, how have you guys dealt with that?

Valon Xhafa: Yeah. So, uh, there were like a few measures. Um, we as a company, um, we as a company, uh, we're not, uh, highly focused on language models. Um, and the primary reason is that language models, they still lack in, in reasoning and, and causal reasoning, right?

Um, language models are also very hard to, uh, explain how [00:11:00] they came up with a specific answer. Um, but at the end of the day, you cannot trust language model to, uh, come up with a calculation or estimation or a prediction about something and, and, and ask language models to provide you a budget. very much.

Strategy or something. This is something that, um, mid enterprise clients, but also other clients as well, they're not going to really trust, you know, so because of these, this effects of hallucination and a lot of other things, language models are not at that point yet. Instead, we use, like, deep learning models that have, that we can implement the causal reasoning, that we can trace back.

Um, how this prediction, how this result came to be and be able to see if that makes sense or not, because that's what also clients want to see. If you, if you, for example, suggest a client that you should invest this much money into this strategy for marketing, you know, and you're going to get this much ROI, they want to [00:12:00] actually see the traceability of that reasoning, which is something that's almost impossible in language models today.

So this is first, but still. This process is still, um, we're like, um, you know, like it's not, it's not cost effective, you know, it's still, uh, we're expensive and still needs to be scaled. And for that reason, we, we build our own, you know, like data centers. We both, uh, we've, we've acquired a lot of, um, um, you know, like GPUs, graphic cards.

We build our own data centers from the beginning on. Which is highly important for every AI company out there. I understand that the GPUs, they get older and older with time, right? And like, you know, like every 18 months, you know, like the capacity doubles based on Moore's Law, you know? Uh, but still, still, in the short term, even in that short term, in that 18 months period, the ROI is clear on building your own, even mini server.

Transcribed [00:13:00] Yeah, versus, uh, versus using called because cloud is highly expensive, especially for companies that are just starting out or even they want to scale. So it's a combination of both pretty much.

Matt Edmundson: Well, yeah, I, it's, it's interesting. I mean, you know, How you've done it and how you've approached it.

Um, and I'm, I'm curious, what have you discovered then, you know, you've been working with AI, you're, you know, more than the average bloke on the street, Balint, uh, about this whole thing. What have you discovered about AI over the last, well, since we last spoke, that's maybe a bit surprising, that's, or that's really helped or that's making some big changes in eCommerce.

Valon Xhafa: Yes, uh, so there is a growing interest from, um, from eCommerce brands, um, that they, uh, they see the capabilities of AI and for that reason, they want more automations. So in a nutshell, [00:14:00] AI, um, is primarily here to assist us, help us on, on, on things and tasks. That we've performed manually, that we've spent a lot of time that we shouldn't have spent a lot of time.

Yeah, right. It's not here to replace us completely. It's here to help us transition to things that we as humans are capable of doing, like reasoning, creativity, and so many other things, right? And leave these manual, redundant, repetitive tasks To

AI,

Valon Xhafa: right? And for that specific reason, um, AI is, is, is great for, for these cases and, and brands, they want to see automations.

They want to see that a lot of their day to day redundant, repetitive tasks are automated. And this can go from like reducing car abandonment. To optimize their organic traffic, to optimize their SEO, to optimize their social media, to optimize their organic traffic in different, like, let's say, TikTok [00:15:00] or Instagram or whatever, right?

So they, um, the majority of the brands, they do a lot of, like, repetitive manual tasks that are daily that can be automated. So this is the common interest and the common trend that we see these days in eCommerce, and AI is perfect in these cases. Why? Because if you want to automate something, you need to understand that task.

You need to understand how things come to be. Which is, uh, what AI literally does, right? AI has this capability of predicting things when you have a high accuracy of predicting an outcome. You can use the same process to also explain how did that outcome come to be. But we already discussed that language model, they still don't have this reasoning capability.

And based on that, you can run automations. So, uh, we have one of the, one of [00:16:00] the main focus for us in the last few months was on being able to, um, increase organic traffic

with

Valon Xhafa: automations running on AI. Why organic traffic? Well, there are a few things that changed since pandemic. First of all, before pandemic, um, money used to be cheap, low interest rates.

Ads used to be cheap, so the common strategy before was like, you get more money, you throw this money into ads, and you're gonna grow, bring more traffic. Simple strategy, clear, um, strategy here. But things have changed, right? You had all of these, like, privacy updates from Apple, um, money's not as cheap as it used to be, unfortunately.

Right, and we can see this not only in the U. S. But all over the world, pretty much, so that strategy of just like getting more money, raising more money, um, getting loans [00:17:00] or whatever to throw into ads because ads are, are cheap. It's not really working. It's not as scalable as it used to be. On the other hand, um, the, the number of users on different social media and different, like, let's say, on Google searches or TikTok is skyrocketing.

So, there is a distribution of focus, and, um, from this, because of all these different changes, There is also a clear change in the trend on how brands bring traffic now. They are, um, they are not relying completely on bringing traffic through ads. They're trying to distribute this. They're trying to bring more traffic through different other channels, potentially organic.

Because the organic traffic is way more valuable. In a one to one basis than with paid or other different channels, because the intent is clear. So the question now is how, um, how can we [00:18:00] establish ourselves? Is there a way to understand a strategy? Because, um, because of paid marketing used to be, uh, You have such a huge impact, Matt.

Um, there are so many platforms out there that help you, you know, like with paid and help you optimize things and get ROI and build strategies and this and that. But in terms of organic, it's, it's way more complicated. Because you have, for example, for the majority of the brands we work with, which are primarily mid enterprise, Or maybe let's, let's kind of like step back and let's simplify things, right?

If you have a small store, you're just getting started, the fastest way to bring traffic are ads, no doubt about it, right? So we have, we have clients that are all like on Shopify. Uh, few, few hundred thousand traffic, uh, the majority of the traffic is paid, but that as you start to move towards a mid market, then enterprise, there's distribution of traffic changes.

Yeah.

Valon Xhafa: So the [00:19:00] organic traffic, which is primarily coming from Google search results. All of these start to take more and more portion of the traffic.

Yeah.

Valon Xhafa: So in general, for example, based on numbers that we have, 30 35 percent of the traffic is organic for mid enterprise, for the clients that we have. For smaller sources, like 5%, 10%.

Max, but this traffic, uh, accounts for like 50, 55 percent of the revenue. That's how much the impact is.

And

Valon Xhafa: because of that, because of that, there is a huge interest. There is, it's very important to establish your brand as you move towards mid enterprise market. Because relying completely on ads, especially these days, um, it's not cost effective.

You're not, it's going to be very hard to break even. It's going to be very hard to, to, um, to scale pretty much. [00:20:00]

Matt Edmundson: No, it is. I I've seen, uh, uh, it's interesting, uh, hearing you talk about this because it's one of the things that I've noticed a lot more people now are looking at SEO. Again, everything comes in cycles, isn't it?

SEO was really trendy a few years ago, and then it sort of stopped being trendy because ads became easier. And now it seems like SEO has become the big thing again. You know, how do we, how do we, how do we grow our organic traffic? And I'm intrigued by this topic, Val, and I'm actually quite pleased to talk about it because Recently, Google have made changes, as best as I understand it, to the search algorithm where they're trying to sort of push out websites that are trying to use AI in many ways to bump up their organic rankings, right?

So it's almost like Google have caught on to this idea that people are trying to do this now. Um, So, on one hand, I hear what you're saying, you know, AI can be used to help SEO. On the other [00:21:00] hand, I hear comments like Google's, you know, penalizing, maybe penalizing is the wrong word, but they're certainly cutting off sites which are heavily, heavily, not heavenly, no, but heavily sort of AI influenced.

How do you deal with that? Yeah,

Valon Xhafa: that's a worry, that's a worry, um, that's a worry. Question. So, um, Google usually or primarily penalizes what we've seen from the data. They primarily penalize, um, different strategies that are not that ethical, like, for example, um, leak insertions, uh, or automatic leak insertions, you know, or different type of ways that try to find loopholes In the process to scale the CEO, um, you know, like in a fast, risk scalable way, what we're saying here is that, um, the state of the, uh, of the market right [00:22:00] now, as it is, um, trying to build and establish yourself.

Out there by building guest posts, for example, which is a common process. It's where it's, it's where a straightforward process, right? There is nothing wrong with it, right? Um, in this way, by not really knowing with which people you should partner up to write guest posts or blog posts or other things. You know, and, and doing this, which can take time, but, uh, on the other hand, if you do it wrong, if you do it with the wrong type of people, just because a Google AI algorithm, um, can penalize these cases and actually damage your position instead of helping you, we don't believe that's the right way.

Right? We do believe, we do believe that, um, like with the ads, where there were a lot of platforms that help you to optimize the ads, optimize the budget, understand, uh, who are the target users, the same approach can be taken, and we're [00:23:00] taking for, um, the organic traffic for SEO in this specific case, right?

So, if you want to write a guest post, for example, um, relevancy. Or in SEO in general, relevance is very important. It's the most important factor out there. But you don't really have data or platforms that offer you data about relevancy. How is that possible? We still rely on cases, on data that are based on domain authority, for example.

A thing that, based on the data that we see, has almost no impact. Oh wow, okay. That's good news. So relevance, relevance Matt, as in information. is the highest impactful factor out there in SEO. And there is nothing wrong about measuring it and understanding how relevance has an impact on your rankings.

Right? Because relevance can be measured with even models that Google publish [00:24:00] themselves, open source. Right, you have the bird, for example, that you can use to measure relevance and being able to, you know, like, see how relevant is a content that you're writing for your site with a keyword that you want to rank.

What's wrong with it, right? There is literally nothing wrong, pretty much. So, take into account that relevance has the highest impact and how often you publish things. And how often other people talk about you, which means that they, uh, uh, build backlinks or they, um, build, you know, like links that go to your site.

These two factors have the highest impact right now. And we see this with data. But still, this is like a, you know, like a high level overview because there are so many other things that these two factors can be broken down. It's not just like the relevance of your content with a keyword, but it's also how relevant is this company that is talking about you.

Yeah. [00:25:00]

Valon Xhafa: It cannot be your competitor, which means it cannot be highly relevant, but also it cannot be a company that has nothing to do with your, uh, with your domain or industry or whatever. So in a nutshell, based on the data that we see is that the differences were a slight, because if you think they're called like the relevance from zero to 100.

You know, the difference can be like 10 points or something, 10 percentage points. It's not that high, but we as humans were unable to actually, uh, without measuring relevance, come up with a relevance that is, that has that precision. So, taking all these different things into account, we've, uh, we've established and we've, uh, we were able to measure relevance, to be able to explain the rankings, to be able to understand what has an impact, which.

What kind of content should you write? And by content, I mean, not like just using language models to produce the [00:26:00] content. We've tested this and we've tried to ask different language models to generate or rewrite the content, Matt. And we measured the relevance with a specific keyword or a specific, uh, title or whatever.

And we've seen that whenever you were generating something or rewriting that thing, the relevance was becoming less and less and less.

Matt Edmundson: Right.

Valon Xhafa: So what this means is that the most important factors that is out there in SEO relevance is not really being taken into account by a lot of content writing tools out there.

They're just writing it and trying to put all the different keywords and trying to stuff it with keywords and trying to optimize or maybe even the best case scenario. They're trying to see what the top competitors on the, on the first page are doing, what keyboards they have. But guess what? Based on our data that we have, um, just because a domain is ranking first, doesn't mean that they're all perfect.[00:27:00]

You know, just because the domain has, let's say some backlinks, doesn't mean that these backlinks are state of the art. The idea is being able to actually understand, um, how the relevance has an impact.

Yeah.

Valon Xhafa: Paul, do you write content that are relevant? And relevance is here to stay, because relevance is a metric that is highly scalable to be calculated when it comes to the engineering part.

Domain authority is way more complex than actually relevance, you know. And relevance actually gives a more semantic meaning to your content and the keyword. It's not just like, is your keyword in your content, but it's more like how, Related that content is and being able to measure it. So these are like few things that we've actually seen and now we're able to not only, um, not only tell you that this content that you're writing is not that relevant with the keyword you're trying to rank, but also use all this [00:28:00] information to also understand where to publish that content.

You know, if you, for example, if somebody wants to write about you, you can actually simulate and predict if that's going to help you in the ranking or not. Even before you publish an article somewhere, that's how impactful the process is. So far it used to be like they tried to write as many guest posts as possible, some were helping you, some were backfiring, you know, but that's pretty much it.

It was completely blurred. The AI now is actually building a clear path and this clear path, you can take actions like a GPS, where let's say you want to write 10 guest posts, all you have to do is literally just get a list of domains where you want to publish these guest posts. And you'll be able to predict the impact in terms of ranking that [00:29:00] these individual guest posts will have.

So if you see that some are bad, why would you publish there? Go somewhere else, you know? So that's what I'm kind of like talking about here. We're talking about like being able to have a GPS and navigation when it comes to building organic traffic in the right way, right? It's not about like It's not about like hacking the system or finding loopholes in the Google algorithm in terms of like inserting links where they should not be and we have seen this for example we see cases if if an article or a backing or a guest post talks about you but then at the same time they talk also for another 10 companies Transcribed You know, that's not as good as just talking about you.

And it's clear. So Google is literally penalizing all of these different unethical [00:30:00] ways of building backlinks. And yes, based on the data that we have, backlinks have a huge impact still. And it makes sense because you are more popular when other sites talk about you, which is also like for us in general.

Would that make sense?

Matt Edmundson: Yeah, totally. So, it's not like, um, AI is revolutionizing the principles of SEO, so the principles are still the same. Good quality content, good backlinks, relevancy, and so on and so forth. What you're saying, where I think AI has struggled is, well, I guess where everyone has used it, like, you know, people like me, as you go to chat, GPT or Claude or, you know, whatever you're.

Model Of Choices and say, write me a blog post on, I don't know, pens, you know? And so it goes away and it writes you an SEO optima what it thinks is an SEO optimized article on, on pens, which you're then going to edit, change, and [00:31:00] publish what you're saying as best as I understand it actually is that's, that's the worst way to use AI where SEO is concerned much better is to think much more big picture, much more strategically.

Much more, you know, let's think about relevance and and let's look not just at the micro here. Let's look at the macro How is that going to work in the in the bigger picture if I've understood it?

Valon Xhafa: Yes, exactly So if you just ask so we've from our end we've identified around like 1000 Different Factors, Relevance, Backlink Factors, On Page Technical, all different things that are really important to be measured and taken into account if you want to build a backlink or if you want to write a content or if you want to optimize something when it comes to SEO.

And what we have seen is that the level, the level, the margin of you taking an action that can help you versus, uh, can damage [00:32:00] you is pretty close. Right? We're talking about like few percentage points in relevance that can help you in ranking higher versus damage you.

And

Valon Xhafa: because of, because of the language models, they don't have this information.

They don't have these 1000 different factors that need to be taken to account when you write this article or this content. They, in the majority of the cases, we have an accuracy. So it's like 30 percent accuracy in terms of writing a good article that meets all these different criterias that would help you to rank higher.

We have seen that it doesn't really work. The reason why is that when you write a content, for example, based on the results that we have, is that that content, you know what, it cannot be like highly relevant to your, uh, homepage, for example, because, and then you're kind of like, you're kind of like [00:33:00] damaging your homepage, which is the most important part of your site, right?

Yeah. But also cannot be that, uh, dissimilar or it can, it, it cannot have a low relevance when it comes to the homepage. So where is it like that? What's the sweet spot here, you know, and language models, they don't have this information. They don't have these 1000 different factors to take into account.

You know, and it's not only that, but it's like, for example, if you build a gas post from, from, uh, from a different domain, and they are linking to you, not only the article that is talking about you has an impact, but even the homepage where that article is coming from. And the relevance of that homepage to your homepage and to your article and to your keyword has a huge impact.

That's how deep it is. Language models, they don't have this information. So what does this mean? Because relevance is a factor that measures the relevancy between different [00:34:00] articles, different content, and it is the most impactful factor out there in SEO that you cannot even I don't think we had a tool to measure anywhere else, but we had to go and build a tool to measure it and being able to offer this to our clients.

Um, this means that a backlink that used to be good a few months ago, or a guest list that used to be good a few months ago, it doesn't mean that it's going to stay with that quality forever. Because relevance is a measure of text content. And as soon as, let's say, the homepage of the backlink changes, you know, not the article, but the homepage, this also means that the relevancy can decrease, which also means that the backlink quality can decrease.

So SEO as a channel to bring organic traffic, it's not a static system. It's not a static process. You build one good backlink with high domain authority, it's going to be forever like this. No. [00:35:00] Because the Google algorithms. Change and they try to optimize all the time and also all the sites change and because relevance is the highest impactful factor out there, relevance can also change when somebody changes the content or you change your homepage or you move things and you change stuff.

So whenever you change something, things are going to, the relevance is going to change, which it can have a huge impact on, on your ranking. Does it make sense, Matt, or?

Matt Edmundson: Yeah, it does. It totally makes sense. And I'm really intrigued to see where this all goes, Valen, because it's, I do see that organic traffic is going to become more and more of a big deal again.

And I, it's an obvious thing with the way that ads have now gone, um, I see social traffic becoming more and more of a big deal, you know, being discovered on social channels, because hashtags don't really work. So how do people find me on social [00:36:00] media? How do I grow those channels? I, I, this is all organic traffic, isn't it?

And using, Using AI to give us a competitive advantage on that and to help us do that right and well in a way that's going to work with those platforms, as opposed to trying to find a cheat code backdoor in for a little while, um, I think is, is exciting. I think it's one of those things that I'm really intrigued to see how it develops because I don't see many people talking about it.

Um, I see a lot of platforms talking about the micro. I don't see. Many people talking about the macro and how it all sort of fits together. So I think that's interesting. I think it'd be a bit of a game changer. So yeah, it makes total sense. Um, I'm intrigued to see how this works with you guys as well, how Behamex sort of handles all of this, um, going forward, I, I, I'm, I'm utterly intrigued.

Valon Xhafa: It's a very interesting, it's a very interesting, uh, it's a very interesting space because as you said, I can [00:37:00] definitely confirm, uh, social, which is, uh, a channel for organic traffic besides SEO, um, it's growing super fast. Right. And, um, and when we talk about like automation, so we talked earlier before, right.

Um, you don't need to, why would you want to be an expert in something that changes all the time? Right. Because a lot of people talk about like the Google recipe, which is something that is a very interesting or interesting talk. When I hear about, uh, a lot of SEO people talk about the Google recipe and, uh, you know, like there were a few leaks from Google about what kind of factors they use and they were talking like, we didn't see the recipe.

What's the recipe? There is no recipe. That's a problem. There is no recipe. Even Google, they don't know their own recipe. Why? Because the time when, when people, when engineers at Google, [00:38:00] and also other companies, used to sit down on their computers and write a recipe, an algorithm, manually, themselves, to optimize something, is long gone.

The

PageRank

Valon Xhafa: algorithm was a recipe, because you could trace, you could, you could understand the whole in and outs. It was a descriptive algorithm. The current algorithms that Google uses and the whole, probably, not the, probably, but the whole world uses, like, these are probabilistic algorithms. There is no recipe there.

And the way you train these algorithms to rank something, it's the same way that you train a language model to spit out text. You get, uh, a lot of different tasks. You do a lot of different tasks. You see how a site is performing, if it's on the first position versus second position. So Google tries to optimize the click through rates on the first position, on the first [00:39:00] page, on the second page, and third page, right?

And they have these large algorithms. So, there's a lot of things that try to optimize the click through rate. The chances that a user, when they land on Google, they're going to click something. That's what they're trying to optimize. So the recipe here, it's a large model that is constantly learning and changing and adopting things.

The relevance Is the key component, which is a huge difference from before where domain authority used to be a key component. But still, these algorithms are trying to optimize things and improve things all the time. And they are changing all the time. So there is no recipe. If you still try to go after the recipe, you will never find the recipe.

There is no recipe. We don't have a recipe. We don't have a recipe at Behemoth on how we build the algorithms. Because we, we ride deep learning algorithms. Behemoth. com Right? We create all these different architectures and we play with the architectures, [00:40:00] but even if Google gives you the architecture of the rankings, what can you make out of it?

Nothing. You know, it's a clear concept, right? So there is no recipe because everything is embedded on these large, So, there you have it. I hope you found this video helpful. If you have any questions, please leave them in the comments. I'm Matt Edmundson, and I'll see you in the next one. This is Garnet.

It's going to give you a good score that, well, you were able to handle this user that I brought to you and the user is happy because they're coming back to Google. That's how it works. It's a win win for both. You write great content, you optimize your page, users save more time, they convert, maybe they buy something, and you and Google share the revenue.

Right? That's how simple it is. But there is no [00:41:00] recipe. So why, why, why do you have to, for example, learn things that are changing constantly and that they don't actually have value? Where these things can actually be automated. And there are so many of these instances and cases out there in the market.

Not only within eCommerce, Matt, but all over different industries.

Yeah,

Valon Xhafa: that, uh, we are trying redundant things, repetitive things, things that we should not do. Instead of focusing on creative stuff, creative thinking ways to build new things, to come up with new challenges, we are kind of like, I'm not saying wasting, but like spending our time on these things that they don't really have a huge impact in the longterm, but they are more repetitive.

If that makes sense. And I do believe that AI is going to really automate a lot of these, a lot of these cases. I don't want to say like, you know, like replace jobs, but I'm saying like, give you [00:42:00] actually more time to think about things that have a higher impact in terms of like creativity. And last but not least, Redundancy.

So

Matt Edmundson: fantastic. Well, so many questions in my head, but I'm aware of time. Um, and it's been a fascinating, as always, Valen, a fascinating conversation about the industry and where it's all going. And I, I love that when you were saying there is no recipe at all. In my head, all I could hear was the kid from, I don't know if you ever saw the movie The Matrix, where he goes, there is no spoon.

Uh, that's, there is no spoon. Um, and so that's what I heard, maybe showing my age now. Um, if people want to reach out to you, if they want to find out more about what's going on with you, find out more about how maybe they can, you know, how you can help them with their SEO with Behamex and stuff. How do they do that?

What's the best way?

Valon Xhafa: Uh, they can reach out to me directly on LinkedIn, um, or they can just reach out, um, [00:43:00] can just go to bmx. com and reach out from there. So two ways, two different channels, uh, happy to talk, happy to discuss, happy to help. Uh, we do believe that, um, we do believe that a lot of, um, a lot of, um, things within eCommerce are going to be fully automated.

Or maybe 90 percent automated, because we have seen this case, Matt, in a lot of different industries. I'm bringing this example for the end. Like back in the 70s, stock trading used to be completely manual. Over the phone, everything else, right? Like, we do SEO and a lot of other things right now, manually.

And, uh, there were a few people who tried to, um, you know, like, start to build algorithms because the first computers came out. And here was the biggest issue. They didn't have data to train these algorithms or build these algorithms because there were no CSVs files and there were, there were no data. So they literally had to go to libraries.

And read the books, [00:44:00] historical price data, and get these prices manually and write on these kind of like disks that they used to have and build these algorithms. But they were successful, because there were no algorithms back there, and they started to make a lot of money and change the industry. Now, very few people do manual stock trading over the phone and all that stuff.

That job is dead. If somebody does stock trading for a company or something, they're probably just managing computers doing the algorithms at a high frequency rate, and you cannot really compete with these algorithms. In my opinion, this is how a lot of things are going to change in the future for good.

When we started working on this, um, on trying to understand how to optimize and bring more traffic from SEO, we had the same issue. We literally had, we couldn't find data about relevancy, we couldn't find quality data about backlinks, we couldn't [00:45:00] find quality data about literally almost nothing. So we had to go and collect all the relevancy and all the different factors ourselves manually and build a system to, to collect this data at scale.

Because we didn't have that. So I'm comparing these two cases as, as examples on how the stock trading used to be versus how the SEO is right now and where the SEO can be in the future. It's going to be, it's going to be, it's going to be automated at a high level, pretty much.

Matt Edmundson: Yeah, well, I'm looking forward to seeing where it goes.

Um, I, I am looking forward to seeing where it goes and in stock trading as well. I'm, I'm still looking forward. to find in the program that can, you know, just do it all for me and make more money. But, uh, but no, it's really fascinating. Uh, Valen, thank you for coming on the show. Before we go, right, we do this.

Uh, I mentioned to you this question for Matt, where you ask me a question and I answer it on my social media channels. Uh, so what's [00:46:00] your question for me?

Valon Xhafa: Very good question, Matt. Um, What do you think, what do you think about the, uh, what do you think, uh, are going to be some, or what do you think is going to be an interesting trend in eCommerce in the future?

Matt Edmundson: Okay, an interesting trend. Or,

Valon Xhafa: maybe, maybe, maybe, maybe, let's rephrase it. How is the online shopping, um, experience going to look like in the future?

Matt Edmundson: Okay.

Valon Xhafa: Because it hasn't changed that much in the last 20 years.

Matt Edmundson: Okay. So what's it going to change? No, that's a very good question. So what does the online shopping look like into the future? If you want to know how I'm going to answer that question, check out social media, just follow me on social media, and you'll find at some point, I will put up a little real or short form video answering that question.[00:47:00]

But I have some really interesting answers to that, especially after a recent visit to the States. But I'll go more into that on social media. Val and listen, thank you for coming on to the show, man. Really appreciate you. Coming on and just sharing your whole insight into AI. It's always good to talk to knowledgeable people and you are very knowledgeable, sir, uh, in this whole area.

So thanks for coming on. Uh, we will of course link to Valon and everything, uh, his, uh, LinkedIn and his company bahamix. com in the show notes. Uh, but Valon, that's it from, from me. Thank you, man. I really appreciate you being on.

Valon Xhafa: Hey, Matt. Thanks. Thanks for having me. It's always a pleasure.

Matt Edmundson: Always a pleasure, indeed.

No doubt he'll be on the show again soon in about 18 months. So make sure you follow the eCommerce Podcasts wherever you get your podcasts from, because you're going to want to hear that episode as well as all the other ones we've got lined up. And in case no one has told you yet today, dear listener, you are awesome.

Yes, you are. Created awesome. It's [00:48:00] just a burden. You've got to bear it, Valon's got to bear it, I've got to bear it, you've got to bear it as well. Now, the eCommerce Podcast is produced by PodJunction. You can find our entire archive of episodes on your favourite podcast app. The team that makes this show possible is the wonderful Sadaf Beynon and the latest one, Jonah Prisk.

Oh yes, our theme song is written by Josh Edmundson. And as I mentioned, if you'd like to read the transcript, the show notes, uh, all that sort of good stuff, just head over to the website, eCommercePodcast. net. But that's it from me. That's it from Valon. Thank you so much for joining us. Have a fantastic week wherever you are in the world.

I'll see you next time.

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