Double Profits, Half the Team? The Power of AI for Business Revealed

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Double Profits, Half the Team? The Power of AI for Business Revealed

Ben is one of the Co-Founders and CEO of Superfuel AI, he’s passionate about e-commerce  entrepreneurs and their aspirations. He is excited about bringing the advancements in AI to help ecommerce sellers scale in ways never thought possible.

 

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> Here’s a glimpse of what you would learn….

  • The role of AI agents in scaling e-commerce businesses.
  • Automation of routine tasks to reduce the need for additional staff.
  • Competitor analysis and its importance for e-commerce sellers.
  • Optimization of product listings, including images and keywords.
  • Enhancements in advertising strategies through AI insights.
  • The significance of quick decision-making in a competitive landscape.
  • Future developments in AI technology for inventory management and pricing strategies.
  • The balance between AI automation and human oversight in creative strategies.
  • The impact of AI on operational efficiency and business growth.
  • Encouragement for e-commerce professionals to adopt AI tools for improved decision-making.

In this episode of the Ecomm Breakthrough Podcast, host Josh Hadley interviews Ben Matthew, co-founder and CEO of Super Fuel. They discuss how e-commerce businesses can scale efficiently using AI agents, eliminating the need for additional staff. Ben shares insights on Super Fuel’s AI capabilities, including competitor analysis, image and keyword optimization, and ad spend management. The conversation highlights the importance of quick decision-making and smart leadership in leveraging AI tools. Ben also shares his admiration for industry leaders and invites listeners to connect for further insights. This episode offers valuable strategies for scaling e-commerce operations effectively.

Here are the 3 action items that Josh identified from this episode:

  1. Automate Pricing & Testing: Use AI to monitor competitors, adjust prices dynamically, and run scheduled price tests—freeing you up to focus on growth strategy.
  2. Cut Wasted Ad Spend: Let AI flag and remove non-converting keywords, and align your product listings with actual customer search terms for better ad performance.
  3. Streamline with AI Agents: Reduce manual tasks like competitor analysis and inventory planning by integrating AI tools, enabling faster decisions and leaner operations.

Resources mentioned in this episode:

Special Mention(s):

Related Episode(s):

 


Episode Sponsor

Sponsor for this episode…
This episode is brought to you by eComm Breakthrough Consulting where I help seven-figure e-commerce owners grow to eight figures.

I started Hadley Designs in 2015 and grew it to an eight-figure brand in seven years.

I made mistakes along the way that made the path to eight figures longer. At times I doubted whether our business could even survive and become a real brand. I wish I would have had a guide to help me grow faster and avoid the stumbling blocks.

If you’ve hit a plateau and want to know the next steps to take your business to the next level, then go to www.EcommBreakthrough.com (that’s Ecomm with two M’s) to learn more.

Transcript Area

Josh Hadley 00:00:00  Welcome to the Ecomm Breakthrough podcast. I’m your host, Josh Hadley, where I interview the top business leaders in e-commerce. Past guests include Kevin King, Michael E Gerber, author of The E-myth, and Brandon Young from Seller Systems. Today I am speaking with Ben Matthew, and we are going to be talking about how you can scale your e-commerce business using AI agents without needing to hire more staff. He’s got a super wicked smart AI software that he’s going to be sharing. How he’s able to do this, it maybe even can you run your business with one person and a whole bunch of AI agents to get to 100 million? That’s a topic we’ll say for another day, but that’s the vision behind this. This episode is brought to you by Ecomm Breakthrough, where I specialize in investing in and scaling seven figure ecommerce brands to eight figures and beyond. If you or someone you know is ready to scale, or looking for a coach or a consultant to really help them scale, reach out to me directly at Josh at Ecomm Breakthrough.

 

Josh Hadley 00:01:00  Com. That’s econ with two M’s. And let’s turn your dreams into reality. Today I am super excited to introduce you all to Ben Matthew. Ben is one of the co-founders and the CEO of Super Fuel. He is passionate about e-commerce entrepreneurs and their aspirations, and he is excited about bringing the advancements of AI to help e-commerce sellers scale in ways that they never thought possible. So with that introduction, welcome to the show, Ben.

 

Ben Matthew 00:01:29  Thank you so much. Josh, for having me. Super excited to be here. Like I was saying, I’ve been a student of your podcast. I’ve heard a lot of, people who’ve come here speak about different things, and that has helped us in our previous business selling on Amazon as well as for things that we do today. So super excited to be here. Thanks for having me.

 

Josh Hadley 00:01:49  Awesome. Well, Ben, it’s always it’s always awesome to have a listener on the show and somebody that kind of knows the the process and the flow that we go through.

 

Josh Hadley 00:01:57  And now you’re on the hot seat. You know that, in each of my interviews, I want actionable advice for seven figure, eight figure sellers and things that they can actually implement in their e-commerce brands to allow them to scale to the next level. So you’re on the hot seat. I’m going to be grilling you today, especially as we dive into your software super fuel AI, which, you know, you’ve showed me some brief glimpses of it. And so far I’ve been very, very impressed. So for the listeners that are going to be listening to this, I have I’m not currently using Super fuel. I’m going to be asking the same questions you would probably be asking Ben here, because I’m genuinely considering whether this may be the right tool to allow my team. As we continue to grow our catalog. We have 1600 SKUs now that’s only advancing every single month we release new products. And so the constraint is higher. Needing to hire more staff to be able to manage all of the new products that are being put out.

 

Josh Hadley 00:03:02  And so I’m interested to seeing, hey, does this save me from having to hire any additional staff? And I can have my senior leaders that are overseeing my Amazon sales channel utilize this tool to be able to do the work that was needing to be done by a lot of Vas or optimization team members, etc. so that’s the frame of mindset that we’re going to be using today. But Ben, why don’t you walk us through your background? Because I think it’s important to highlight that you’ve been an Amazon seller, and then you saw this opportunity that you’ve transitioned into super fuel. So why don’t you share that your experience there and background with the audience?

 

Ben Matthew 00:03:41  Yeah, definitely. Yeah. So, so yeah, I’m one of the co-founders at Super Fuel. and we are a team who, so we are a team of co-founders and engineers. We are software engineers and product managers. Manager. We started off about four years back, directly selling on Amazon. We were running an acceleration business, helping brands successful in one country launch from zero and scale, to a, to a large size or best sellers in their respective categories.

 

Ben Matthew 00:04:07  So we, we did that for about, about two and a half years. We built a lot of automation for ourselves internally because we were software engineers. And then early last year and slightly before that, we saw a lot of opportunity in AI based agents. so we saw this a lot in the software engineering space, and we saw that just like how junior software engineers are being built as AI agents. We saw a similar opportunity in doing that for e-commerce. Every e-commerce seller will have a bunch of AI agents that can do a lot of the tasks that we used to do. and we used to do a little inefficiently, not do it with as much of efficiency as we need to. We felt that we saw the opportunity where agents could do this for e-commerce sellers. So that’s how we started. so we are a company also backed by venture capital fund called Accel. They are based in Silicon Valley. They were one of the early investors in Facebook, Dropbox, Spotify. So we raised about $2.6 million in funding from them, along with them, in partnership with them, we are able to think very long term focus on, deep innovation that can really help sellers create more value for themselves using AI.

 

Ben Matthew 00:05:15  So our job and mission right now is to simplify AI for folks like you. For example, at Hadley Designs, being able to use AI on a day to day basis using AI agents and, take up a lot of the day to day tasks to be done by this AI. So, yeah, so that’s a quick background about ourselves. And, we work with brands of different sizes, mostly ranging from $300, those who sell between $300,000 a month to about $15 million a month. So those are the type of customers that we work with. So. So yeah. So that’s quick background about us.

 

Josh Hadley 00:05:47  Awesome I love it. So you’re hitting that those seven figure entrepreneurs and the eight figure entrepreneurs and those looking to scale, you know, past a 100 million. So Ben, this is awesome. So why don’t you share, a little bit of background about super fuel itself. So what is super fuel? Let’s talk about what these agents can actually do. I want to get into the real meat and potatoes and dive in and say like, all right, this could actually save my team, team time or allow them to do the work that they’re currently doing with the same amount of time right now.

 

Ben Matthew 00:06:22  Yeah. Sounds good. So let me just share my I’ll pull up my screen. Are you able to see my screen.

 

Josh Hadley 00:06:27  We’ve got it. So those that are just listening to this make sure that you come check this thing out on YouTube. Because this one’s going to be very visual today. Obviously, as we dive into this tool and it sifts through all the data and it’s sharing different insights. So we’ll try to speak about it as well as we can. If you’re listening via audio, but definitely come check us out and subscribe on YouTube.

 

Ben Matthew 00:06:50  Yes, definitely. Cool. So so what we’re building at Super Fuel, Josh, is we’re building an AI agent that does a lot of the day to day tasks for Amazon sellers. Now, this AI agent is trained with some domain knowledge on things such as how to, reduce wasteful ad spends, how to improve organic rank, how to scan and study a competitor listings. And based on this, it gives action recommendations that you can take. Now just like how you interact with an employee.

 

Ben Matthew 00:07:16  you can give it your own inputs and your own set of preferences based on which it will change the output that it is giving or recommendation that it is giving. And 8,090% of the output can be executed via super fuel itself by this agent. Right? So some of the tasks that it can do today. So these are some sample tasks. But in total there are about 15 to 16 tasks, some of which we’ll run through in this in this podcast. and you can also create your own set of tasks, by working with us. so some sample tasks are for any Ace in that we have. This agent will go and find top selling competitors. And for those competitors, it can analyze the images of these competitors and compare it with our images to find out what is missing in our images. Right. Second thing it can do is this agent has access to a keeper APIs, through which it can look at the past pricing trend, past BSR trend for these competitors, and from that recommend. What kind of discounts are helping your competitors get better? BSR improved BSR and recommend that for your brand.

 

Ben Matthew 00:08:20  It can identify keywords that are. It has access to Jungle Scout APIs, through which it can access keywords that are doing really well for competitors. In terms of ranking, it can look at the search volume data. It can look at where are we missing out on ranking for these keywords. And find these keywords and insert them into rewrite bullet points, titles with these keywords, and even launch campaigns in the format that you typically launch new campaigns whenever you discover keywords for which competitors are ranking, but you are not running any targeting, right? So these are some sample tasks. So now I’ll straightaway jump into the product itself to see what to show what it looks like. So this is, this is the homepage, of the agent, where you see where you will see a bunch of different tasks that this agent typically performs. There are about 15 to 16 tasks. As soon as any seller, central or seller account is connected, these tasks start, getting activated. And, within 24 to 48 hours, you would start seeing the agent give you recommendations for all of these actions.

 

Ben Matthew 00:09:19  Right? And none of these execute by themselves. So all of these just like how a new employee would join you, it will show you the work first and then you would, basically give feedback and then maybe, approve after that. Right. So I’ll run you through a few. We’ll run through, go through a few examples together. So this task, what it does is, like I said, it will look at competitors listing images and find out what is really missing in our images. Right.

 

Josh Hadley 00:09:43  So my my first question on this is how does it know who my competitors are? And is that something that my team has to upload and say, hey, here’s my product. Right. Well, you’re connected to my API, so you know my products, but do you then need to say like these, I believe are my true competitors? Because yes, there can be like 30 different listings on page number one. That doesn’t necessarily mean that all of them are my direct competitors. So how is it deciding who my competitors are? And guess what? Some of my competitors I don’t even want to pay attention to because I think they’re bad competitors, right? Like, I only care about the top one.

 

Josh Hadley 00:10:26  So how how does it take that into consideration?

 

Ben Matthew 00:10:28  Yeah, that’s that’s a great question. So the agent does that through two through two processes. First what it would do is it will look at your category node in which your Asin is existing today. It will go to that node. It will collect information of all the 100 best sellers that it sees there. So when I say collect information, it will collect the product title, description, pricing. And once it has collected this information, it will compare it with our product. It will compare our features with our price. And also look at the BSR range as well so that we can find relevant competitors. And from that it will shortlist ten competitors. That is for one process, one process that it follows. Second process is where it will identify keywords that are most relevant to your product from your PPC data, and for about 3 to 4 keywords, it will go to Amazon Search search go to Amazon Console, look at the search results. Look at what are what are the products showing up in the first 50 or 60 organic rank.

 

Ben Matthew 00:11:20  Right. And again it will fetch collect the information of those products. Product description pricing using LM. Again compare it with our product and then find the most relevant ten competitors from that. Right. But as a seller you could also you may also want to change the competitors that it is found. So once the agent puts together the list of competitors. You can also change that. Edit that list.

 

Josh Hadley 00:11:42  Okay, so I can come in here and if for whatever reason the AI is not picking up a specific competitor or they’re in a different browse node as an example, right, I can make sure that I, I list them in here.

 

Ben Matthew 00:11:56  Got it. Got it.

 

Josh Hadley 00:11:57  And how many? So how like Ben, as you talk about optimizing these images, is it only focusing on what it believes or like the top ten most relevant? Or is this going through hundreds of competitors?

 

Ben Matthew 00:12:11  Yeah. So right now what it does is what a what a human being would do or team member would do, which is go through ten.

 

Ben Matthew 00:12:17  I mean, you can define this to you. You can ask the agent to look at ten competitors or 30 competitors. That’s a number that you can decide. But whatever is the number that you decide is the task that it does.

 

Josh Hadley 00:12:29  Okay.

 

Ben Matthew 00:12:30  Okay. Yeah. So I’ll just show you what the output looks like. So for example this is a this is a sample product that we have, which is like a cloth napkin product. Now for this product, the the agent has gone and found top ten most relevant competitors analyze their images, not just their images, but also the customer reviews to find out what do customers really value in those products. Right. And for that, and after analyzing the images, I just found a couple of different, types of insights here. And I’ll run you through, 2 or 3 of them. So for example, here in the main image. So if you see this is the main image that we have and this is the main image some of the competitors have.

 

Ben Matthew 00:13:06  Right. So what after looking at the competitor images, what the agent is mentioning is that, we should basically, update the main image to show napkins in a style table setting, such as folded with a napkin ring or placed on a plate with cutlery similar to competitor images. This will help customers visualize the product size, color, and decorative potential. Right? If you see these images actually agent hallucinated and picked a not so great image here, but in other cases it still picks something that is much better, much better visually as a main image compared to, compared to what we have. Right? This is one type of example. Another type of example with this is that we don’t have many lifestyle images. So here it is basically it is found from customer reviews, is found that the customers basically use them for creative arrangements. They use them for different occasions like parties, weddings, banquets, and identify those in competitor images. And suggestions that the agent is giving here is to include a wider variety of real life usage scenarios.

 

Ben Matthew 00:14:09  show the napkins being used by people wiping the mouth, holding the napkin, as well as style for different events like weddings, weddings, parties, banquets, etc. incorporate decorative folding techniques and props to inspire customers and demonstrate versatility. Right, so that is what it is found from the top selling competitors their images, lifestyle images. What specifically are they’re showing? It’s highlighting that and asking us to consider these as images. Right. another type of example here it is found is infographic images. What to cover in infographic images. So it’s found from customer reviews that customers frequently mention issues with wrinkling after washing and the need for ironing, as well as concerns about color accuracy and stain resistance. So what the suggestion that it is giving after studying competitor images is update the infographic image to explicitly showcase key features such such as wrinkle resistance, stain resistance and color accuracy using clear icons and concise text text, right? Consider including a visual comparison of demonstration example before and after washing color swatches or a stain test. So if you look at, I think the text is too small to read here, but if you look at the text that is stain and wrinkle resistant is mentioned here.

 

Ben Matthew 00:15:23  Perfect finishing look is mentioned here. So these are competitors that have identified these customer needs and highlighted these in their images. Right.

 

Josh Hadley 00:15:31  And it’s so. It’s reading the reviews and the and the FAQ section of the listing. And it’s basically recommending, hey, people are having issues with this. Maybe talk about how you can resolve that in the images.

 

Ben Matthew 00:15:46  Correct? Correct. So right now the agent or at least the default setup process that we’ve given the agent is to look at the reviews and find out what are what is really important for customers. Right. And then try to look at our competitors doing that really well in their images. So try to find correlation between those and then tell us what we should do typically like how you or I if if you’re selling and we want to improve our conversion, we are doing certain things with images. And that’s something similar to what we would do. If you additionally want the agent to do look at Q&A, you can ask the agent to do that as well.

 

Josh Hadley 00:16:16  Okay. Love it.

 

Ben Matthew 00:16:17  Yeah. So this is one type of task. I’ll run you through a few other tasks as well on, what it can, what it does. Maybe I’ll just switch my tab to show you how it can write bullet points using, competitor ranking keywords.

 

Josh Hadley 00:16:32  So this is then I think, like before we transition over there to the keywords, I think that, you know, I’m already visualizing how vital that first task will really be for, like, the creative director on my team to be able to just like, get new ideas, right. Like, I see I as like, I don’t know that it’s going to replace people per se. It’s going to replace data entry people, people that were just gathering the facts and presenting things to you. I think it replaces those. Right. But it’s not going to replace the strategic thinkers. And what I envision here is like, my creative director is going to take that tool. It’s going to run that task and it’s going to look at all the suggestions.

 

Josh Hadley 00:17:20  It’s not going to follow it exactly, but it’s going to get those and it’s going to be like, ooh, that’s a really good idea. Ooh I haven’t considered that. Oh, I really like the way that that competitor is doing this. That gives me this idea. So I see it as like being able to, like a10x the idea generation and move a lot faster. In this process, you don’t have to have somebody go spend 24 hours or a full week scraping listings, finding this, compiling a report to then present it to the creative director for then the creative director to just, you know, provide additional feedback like this is like it’s just there it’s laid out perfectly there. So I think that’s super powerful. And the number one thing too, Ben, is like, I would make sure you feature this in your software is like the number one optimization strategy that people have shared when they come on this podcast. Time and time again, where the biggest leverage is, is in one place on Amazon and it’s the main image, main image optimization Is everything on Amazon.

 

Josh Hadley 00:18:27  And I want to share this analogy, which is this. For YouTubers like Mr. Beast or Diary of a CEO. Okay, all of those guys as I’ve learned about their businesses. Guess what? I’ve learned what their number one thing is. Their number one thing is not, hey, how do I think of like, the next greatest video to put out? Guess what their biggest thing that they are focused on. That is the thumbnail image. Period. They test hundreds, right? Let me repeat that. Hundreds of thumbnail images even before they launch the video. So likewise, I think for us as Amazon sellers, like we should be taking that away and saying, hey, like, how much am I testing my main images? Am I actually focused on that? Because that that is the end all be all on Amazon. You’ve got to stand out in the search results. And then it’s the rest of the listings job to convert people. But as Amazon focuses on AI, that visual aspect is going to become more and more and more important.

 

Ben Matthew 00:19:37  So right I completely agree with you. That’s a that’s a great point. That’s a great point. Yeah. So here what it is doing. Yeah. So here what the agent is doing is it is basically rewriting bullet points using competitor ranking keywords. So now similar to the same task before where it is looking at what is what are the competitors that are most relevant for us once the competitors are identified. it is agent is accessing.

 

Josh Hadley 00:20:03  Sorry, I’m going to interrupt you here. Is this something that, like I. I set up my competitors once in kind of like my here’s my ace and here’s my competitors, like feature on your tool. And then for all of these related tasks like it’s it’s now programmed to run these tasks? Or do I have to set up the competitors for each of these tasks individually?

 

Ben Matthew 00:20:28  No. So although so there is all these competitors are pre-configured for all of the actions and for any tasks that you do at an Asian level, which includes some amount of competitor research, maybe it is pricing, maybe what are the new variants launched by competitors, or what changes have they done to their images or a plus? So all of that, it will always go back to the competitors that are configured, and not just that competitor landscape keeps changing every few months, right? So the agent can, every month, go and check for new competitors and then tell you these are the new ones that I’ve found, and then you can decide to add some or reject some, and, you know, you can add that to your existing configured competitors for an Asian level.

 

Josh Hadley 00:21:08  Love it. Love it. All right. Very cool. All right. So this this tool is now looking at the competitor keywords. All right. So what’s what is it found here.

 

Ben Matthew 00:21:16  Yeah. So what it has done is for the competitor that is found it is went and gone ahead. It has looked at Jungle Scout APIs to find all the keywords for which competitors are indexing on, ranking well on, but we are not ranking well on. And for that it is. This is the current bullet points. It is rewritten. These bullet points with these keywords included new keywords and stick for safety. 613 search volume. Stick for walking support 3399 search volume or old age stick for women 1206 search volume. So it has included all these keywords rewritten this. You can also edit this if you want. You can accept some changes, reject some changes. and once you click on Approve Changes here, it will directly make this new listing live on Amazon.

 

Josh Hadley 00:21:57  So I can edit this like in real time right here on this side.

 

Josh Hadley 00:22:02  Like if I’m like, actually I don’t like that word better stick or hand stick for safety, right? Like I could take that out and add a different keyword if I wanted to or something like that.

 

Ben Matthew 00:22:13  Right. Got it. Exactly.

 

Josh Hadley 00:22:14  And then it updates everything in the back end of Amazon for me. I don’t even need to have a VA that goes in and adjust that.

 

Ben Matthew 00:22:21  Yeah, you don’t need to. So it is this will update it. One more thing that we need to add though is right now it’s not live is go to the front end and then monitor. Is the listing live or not. Right. so that is something that we’re just adding now, where it will go to the front end after 24 hours and check whether it is live or not, because sometimes it takes up to 24 hours. Sometimes to update the listing, it will go to the front end check, and again it will retrigger the process. And if it is not getting, uploaded then it will basically show you a status update.

 

Josh Hadley 00:22:51  Fascinating. Love it, love it.

 

Ben Matthew 00:22:54  Yeah. So this is this is one time. Maybe I’ll just run you through one more thing that it does to rewrite the content by looking at your PPC data. So let me just pull out this task. So what this task does is it looks at all the keywords that are doing really well in your PPC. And again, it goes back to Jungle Scout to see whether these are high volume keywords or not. So here it is found for example Easter napkins. I mean, this is a seasonal keyword. So it’s it’s come up in the last, let’s say 2 to 3 weeks. Right. So it’s come up and it’s identified those keywords, which is doing well in our PPC and recommending including them spring napkins, reusable napkins as example. Right. So it will again, you want you can edit this or you can approve them directly here. And it will it will make this live right. maybe I’ll just pull out one more example. So yeah. Here what you can see is our product is actually a, blue light blue colored product.

 

Ben Matthew 00:23:43  So it’s picked up specific keywords that are color specific that are doing well in our PPC. and then it is including those as well in the title.

 

Josh Hadley 00:23:50  And how does it handle variations.

 

Ben Matthew 00:23:56  Yeah. So each Asin is considered by this agent as a, independent product. so for each agent it will do the job, the right quality and amount of job required to research and find out what is really right for this Asin, and then it will fetch those insights around keywords to be included, things like that. but there are also some of our customers who don’t want to make changes in the color or size variations. They just want to replicate the parent. So in that case, the task to be created, the agent task to be created is create my parent, listing first. After that, replicate that for my child child.

 

Josh Hadley 00:24:33  Okay. But if you have different like color variations or things like that, you would obviously have different keywords, right. Black napkins, gray napkins etc..

 

Ben Matthew 00:24:45  Correct. So as long as you want to do that the agent can do that.

 

Ben Matthew 00:24:48  but if you don’t want the agent to do that and, for example, we have a clothing brand, which has about 5000 agents, and they are very particular about, colors and size changes to be mentioned only at the end of the title and only in the first bullet point. So they can give those custom instructions to the agent.

 

Josh Hadley 00:25:09  that I love that. So how could I set that up? Like, do you have to manually edit that in the the title. Right. Is that is that typically what.

 

Ben Matthew 00:25:20  Happens for you? Yeah, I’ll just show you how that works. Maybe I’ll just run you through one more example and then I’ll show you how, how you can give the agent those specific instructions. Maybe one more task that I’ll just run you through is how the agent basically creates new campaigns using competitor ranking keywords. Right? So again, it is fetching the data from Jungle Scout APIs. And then it is looking at our ads data to see, are we already running any targeting for this, for this keyword or not.

 

Ben Matthew 00:25:49  If it is not, if we are not running it, then it is recommending launching campaigns, right? So for example, if you see these keywords, these are five keywords that are identified with a certain a reasonable amount of search volume, which competitors are ranking really well on, but we are not indexing or we are not ranking well and we don’t have any ads running with this targeting. Right. And it has pulled out what the Amazon suggested bid is. Once you click on approve here, it will directly launch this campaign in this format.

 

Josh Hadley 00:26:18  Interesting. All right. We’ll go ahead and create the campaign for you. Like do you get it? So you get to choose like it’s an exact match campaign. You get to choose the bid. How do you get to choose, like up and down bid negating keywords, things like that.

 

Ben Matthew 00:26:36  So that’s where I’ll come to where you can interact with the agent and change any process it uses. So as of now, this open workflow is where you see the exact brain and steps the agent uses.

 

Ben Matthew 00:26:46  It’s opened up on a new tab and I’ll show this now. So these are the step by step process that this agent is following to run this task. And you can given your custom instructions or customization here and submit this here. And it will change the setup process. So I’ll show you what this what are the steps that it is using here. So like I mentioned it is looking at bestseller list finding top ten and competitors similar in product and similar in pricing, then it is using Jungle Scout API to fetch the keywords for which these competitors are ranking. Ranking on. Then it is filtering for those keywords where competitors have less than 50 organic rank. Then it is filtering for three lessons. At least three competitors are ranking for those specific keywords. Then it is finally applying a minimum search volume filter of 500, right? Once this is done, then the agent is going into our ads data. It is looking at our targeting report for the last 60 days. It is specifically looking at what keywords what are these search terms where we are not running targeting ads.

 

Ben Matthew 00:27:42  Right. So and then it is finally doing a relevance check, taking that keyword, using LM to compare it with our listing to see whether this keyword is actually relevant for me or not. Competitor may be ranking, but is it still relevant for my product or not? Right. Once this is done, it is just shortlisting ten top keywords based on search volume and then launching an exact match campaign. Right? So this is where you can interact with it and give it your inputs. Let’s say Let’s say you want to go after even a long tail keywords, right. So you can mention also include long tail keywords that have more than 100 search volume. Right. Something like that. Or instead of exact launch broad campaigns, with down only strategy, write down only strategy. And once you submit this here, it will change this process. Right. It will change this process though. This has domain knowledge. This has domain knowledge. This agent has domain knowledge and all. Okay. There is an exact match.

 

Ben Matthew 00:28:40  There’s a broad match. There’s a phrase match. There is up and down bidding strategy. there is an Amazon recommended bid if you ask it to basically, bid, set your bid as 20% less than Amazon search. So all of that it can understand. Right. So it can understand and you can change the logic that it uses. And next time when it is basically giving you recommendations here, it is basically giving. It will give you recommendations for keywords that have more than 100 search volume as well. The campaign type will change to phrase or phrase as a or whatever is the type that you select.

 

Josh Hadley 00:29:12  Yeah.

 

Ben Matthew 00:29:12  Like this. Every agent’s brain or steps that it uses for any task you can look at here. And then you can edit and modify to exactly how you today operate or, you know, works best for your brand.

 

Josh Hadley 00:29:23  That’s pretty cool. because you could basically for any big brands that are using this, especially for ourselves, like we have lots of SOPs already created. And so what we could do is basically, you know, layer on top of your existing SOPs and say like, oh, actually, this is a good idea.

 

Josh Hadley 00:29:43  We weren’t doing this, so I’m going to keep that. But these are a few enhancements that we feel like we could actually make. So I think that’s an important aspect to call out. And I think that for let’s say younger seven figure brands, right, that maybe don’t have a full SOP playbook. I think that maybe Super Fuel gets you started off on the right foot of hey, here are some best basic SOPs that have basically been crowdsourced. So maybe that leads me to another question. Ben is like as AI and software development is no joke because like after you release something, one a week goes by and it’s probably outdated already, right? So like the pace of innovation is crazy fast. So how does the what is the what is the future look like for these SOPs as you learn and grow like right. Is this SOP for launching new campaigns using competitor ranking keywords like Will this be the same SOP for the next year, or do you make modifications? As you see how people are changing the the workflow structure in the back end and then you’re like, oh yeah, like this is the new Baseline for everybody.

 

Josh Hadley 00:31:01  Like, how does that work?

 

Ben Matthew 00:31:02  Yeah. So I will split this into two parts. One is that, the SOP that we follow here, let’s say to create title and bullet points. It is defined by what works on Amazon and what, let’s say experts like yourself know would work on Amazon. So the AI would not be, let’s say if you are an expert or if you know what is what really works for organic ranking, I may not be ahead of you. Right? So the SOPs are pretty much what, let’s say in the world of Amazon is defined. So what the agent needs to do is it needs to be aware or trained with the latest SOP so that that can be executed. Right. now coming to how the agents operate, which is a more, what is possible with tech kind of question, today what the agents can do or as and when the agents are created, especially in the software world, what we’ve seen is agents start with extremely basic tasks to begin with. Right.

 

Ben Matthew 00:31:53  catching errors in my code. Right. That is the basic thing. That is start with or autocomplete my code if I’ve written 20% of my code complete the rest 70% of my line in the code. That’s how it starts with. But what happens is, with every six months, these agents have been becoming smarter and sharper in the capabilities that they have. So what that would mean here is the agent that we today is basically doing some tasks based on what you’re asking it to do tomorrow. It can actually do something more complicated. For example, to predict how much if you have a business plan of, let’s say $50 million for this year. So what all other things that I can do to get to $50 million in the next 12 months, which variance shall I launch? What improvements do I need to make on my product? What is the kind of ad strategy that I need to make? Now this is how much inventory I should plan. and things like that. What are the levers? There are 14 cost items in my PNL.

 

Ben Matthew 00:32:47  Which levers should I move by? How much and what should? So those are extremely advanced thinking. problem solving. Right? So that is where agents will over a period time get to, and that is defined by how much of reasoning capability is there with these LM models that are out in the market? How much of tools around these models are we able to build? so yeah, there are entire ecosystem has to develop. And we are seeing that pace only increase, with the most advanced AI agent that we see in the market are are doing revenue of $150 million. And they what they do today is very different from what they used to do before. Right now they are a lot more advanced than what they are. But but the SOPs for Amazon would be defined by what you would, you know, as of today, and that is exactly what you have to ask the agent to do and execute if you want the agent to follow your process. Does that does that answer?

 

Josh Hadley 00:33:42  Yeah, yeah. And I think ultimately, Ben, I think like the way people need to think about this is like you still need to whether this be yourself.

 

Josh Hadley 00:33:52  Right? You as the Amazon expert, or if you’re a bigger company and you actually have an Amazon brand manager or something like that, you need to have the creative strategist that oversees this tool. You, as the creative strategist, need to know, like, what are the best optimization strategies? And then I think, like the use of these AI agents is like, you know, consider these as like the work that you would use to give to a VA no longer needs to go to a VA. And instead of waiting like the turnaround time with like a VA might have been a week to go create this report to showcase to go scrape the data, fill the data. Make it presentable. Right? Right. That has now shortened that window into hours of time to where you’re able to make decisions more quickly. And I think that the brands that are succeeding five years from now, they’re able to adopt these things and they’re able to move at light speed. They are going to be going ten x faster than their competitors.

 

Josh Hadley 00:35:01  And I think that’s that’s the magic that sits behind this.

 

Ben Matthew 00:35:05  So I’ll I’ll add one more thought to this, which is that today when we look at, let’s say, what our creative director must be doing. it’s broken into three types of work. One is what shall I do? How shall I do it? And actually doing it right. Actually doing it. And, how shall I do it is pretty much 60% to 80% of their of their work. Right. So this doing it and some part of how to do it is what agents will help it. the creative director would spend more and more time on what I should do and how I should do, giving instructions to the agent. So that’s the future that we are heading to.

 

Josh Hadley 00:35:40  Yeah. I love that. All right, Ben. What are some other cool use cases that we haven’t yet talked about that we should.

 

Ben Matthew 00:35:48  Yeah. I’ll run through one example where it can look at the pricing analysis of top competitors or price price action of top competitors and give a recommendation.

 

Ben Matthew 00:35:57  Although you may or may not like this output because every seller looks at price very differently depending on the category, depending on the goals, depending depending on the product lifecycle. But what it is doing here is for a nation that we have, it is basically looking at what price changes or discounts with competitors run that help them improve the BSR, and what duration did they run those discounts for, right? Based on that, this AI agent is giving us a recommendation on what we should do with our price, right? So what it is mentioned here is our current price is 21 or 99. we should do, we should have a price of 18.69 for a period of time. and it is also identified that this SKU or this Asin has a lot of inventory. So this is good to do, a price driven sales boost. And it is recommended to duration duration to run this discount based on typically when competitors which time of the month competitors are running their price discount. Right. So, so this is what it is.

 

Ben Matthew 00:36:55  So this is this agent has access to a APIs through which it can get price data. BSR changes along with that price data discount that they’re running. Now you can decide how you want this agent to use that data and give you a recommendation at an Asian level, right. So like how we went through the steps that it follows, you can give it your, set of recommendations.

 

Josh Hadley 00:37:16  Love that. Are you able to like, schedule different like like let’s say I want to test my price Ben. Like is that a feature that I could like plug in here and be like look during this week I want to be at 1999 during next week I want to be at 2199 or 2099. And I want to see what the difference is in my conversion rate and things like that. Is that something that this could like schedule, fulfill? And, you know, even at some point be able to, like, analyze those results and be like, hey, your price was better at 2099.

 

Ben Matthew 00:37:54  Yeah. So what it cannot do yet is, give you after you’ve run your experiments or done your changes, show you what happened after that.

 

Ben Matthew 00:38:02  That’s not a feature that we’ve built to analyze. So that’s something that we have to add, to, to this AI agent. What it can certainly do is if you have a certain logic to decide what pricing to set for next week, what pricing to set the following week, maybe you will include some seasonal factors. Maybe you would ask the agent to look at five closest competitors and see how much sales do they have and how much sales do I have? If if we have only 5% of market share and other sellers are selling other sellers with similar features and pricing, or maybe slightly lower pricing or selling, you know, techniques or quantity or sales, then you can ask you to refer to that and give you price recommend. So those kind of steps you can ask the agent to do, and it can follow those and make the price changes once you approve them here. So one thing that you would notice here is we don’t take any action, or the agent does not take any action on its own.

 

Ben Matthew 00:38:49  You have to basically look at this and give an approval, right? Over time you can move a lot of these to auto approval, but it can do that analysis and give you a recommendation. You can decide to approve it or not approve it. But but that feature we get to build where you can look at post action results okay.

 

Josh Hadley 00:39:06  So like data analytics and drawing conclusions from the data and running the tests is to be built in the future. But what you’re saying is like surely like these are and to be honest, like we have a we have an assistant that their entire job is to just, just go make price changes for us. Right. We have our schedule. What you’re telling me, though, is like that could be fully automated. We don’t like.

 

Ben Matthew 00:39:31  Absolutely.

 

Josh Hadley 00:39:32  We’re already setting the strategy. We already know what we want to test the price at. Right. We’re just having team members go. All right. Go change the price. okay.

 

Ben Matthew 00:39:41  Ready?

 

Josh Hadley 00:39:42  Okay.

 

Ben Matthew 00:39:43  Great. Yeah, that’s exactly that can be done.

 

Ben Matthew 00:39:46  I think soon that that aspect of being able to get the feedback back for, for any changes that we’ve done, whether it’s worked or not worked, use that as a feedback to improve my next set of actions. So that’s something that’s that is something that is part of a roadmap, but it is more complicated to do but that it doesn’t do that yet. Today. As of now.

 

Josh Hadley 00:40:05  Okay.

 

Ben Matthew 00:40:05  Right. So I’ll run you through maybe one more, task where it can basically, look at, we were talking about this where it can look at, keywords where you’re spending money. but it is not converting. And, like, how a team member will find out why we’re not converting. It will, it will basically find that, it will find that reason for us. Right. So let me just open this here. Yeah. So here we have basically, so if we have a bunch of different keywords for which we spent a certain amount of money, we’ve gotten clicks, but it is not converting, right.

 

Ben Matthew 00:40:38  So like a team member would do, it is trying to find out why are we not converting? So let’s just see what the agent has responded here. Yeah. So what it is found is that the product that we are selling or advertising here is a white colored product and not a light blue product, but the customer search firm is light blue napkins cloth. Right. So customer is looking for something different. We are not going to convert for this keyword, right? This is another keyword cloth napkin set of six. Right. so here the thing problem is that the product that we are selling is a set of 12, but the customer is looking for a set of six, right? So this is again not relevant as a keyword for us. We spent $20 for this. So once you click on approve here it will directly negate this keyword in the campaign in the in the ad group where this is a underperforming because we have another product that is light blue. Right. So the keyword should be triggered from there and not here.

 

Ben Matthew 00:41:33  Right. and this is another set of analysis where the agent checks whether my product is competitive or not. For example cloth napkin set of six. Spend $2,822 but not converting 20 clicks so it will try to find out why are we not converting? So in this case, I found that the product that we are selling is a $20 product, which is priced much higher than the other search results that are between $9 to $14 in pricing. Right? So for this keyword, our product is more expensive a keyword search term Easter tablecloth. So here we spent $20. our product lacks explicit Easter motives and is priced higher than most other products in the search results, making it uncompetitive for this keyword. Right? So it is basically for any wherever you are spending money, it will go and check whether this these keywords are worthy to be spent or not. And then I mean, you can individually approve them or approve all of them, after reviewing them. And again, if you have, let’s say certain, you you want to look at at least ten minimum clicks before you evaluate these keywords, right? Then you can customize that in the steps that the agent uses.

 

Josh Hadley 00:42:46  That’s awesome. Is it something that you could automate as well? Like once you get accustomed to like the recommendations. Right. I think at the beginning you’re like, hold on, is the AI doing the right thing? Right? What if I’m like, yeah, Ben, every time all I’m doing is like, click, click, click, approve, approve, approve. Is there an option down the road to where it’s like, all right. No, I agree, my rule is anything with more than ten clicks. If you see it with zero sales over this time period just automatically negate it. I don’t even want to have to think about this anymore.

 

Ben Matthew 00:43:21  Okay, so we’ve, Yeah. So auto approve is something that is also currently there. So if there are certain tasks you want to move it to auto approve. it can auto approve these tasks.

 

Josh Hadley 00:43:31  Very cool.

 

Ben Matthew 00:43:31  Right. So typically typically brands do I mean run this review it and approve it for a period of time. And once they get comfortable, once they’ve adjusted the agent to do exactly what they want to do, then they move certain things to auto approve.

 

Josh Hadley 00:43:45  Yeah, right. That’s incredible. So I think what the idea is going on in my mind is like, we have a dedicated PPC software to do just exactly what you’re describing here, but that PPC software doesn’t help me with my pricing updates. It doesn’t help me with main image, optimizations. So like, you’re you’re building like an all in one tool to help an e-commerce seller, really be able to scale out everything on Amazon, which is pretty incredible. Like I’m excited so far.

 

Ben Matthew 00:44:19  Yeah. So what how are we looking at this right now is we’re looking at specifically those tasks that in spite of all the sass and automation that is there, which are there are great tools in the market and extremely valuable. We absolutely love what they do. But in spite of that, if team members are spending time applying the brain, doing certain manual tasks, collecting information from different places so that those are the tasks that we are looking to automate with. Because that is what I can actually do. I can do, beyond mathematical things.

 

Ben Matthew 00:44:47  It can do thinking like a, like a team member. So those are the tasks that we are working on, adding to this product.

 

Josh Hadley 00:44:56  Love it. Okay.

 

Ben Matthew 00:44:57  So just like how you saw this, keyword negation. Right? I’ll show you something. Where. I mean, you must be running, targeted ads on competitors, which are, these are competitor races on which you’re running ads, but not converting. Right? For example, we have this one Asian. We spend $160, but not converting 36 clicks. Right. So the agent will, in a similar fashion, go and check the competitor’s listing to see what is the problem. Why are we not converting? So the product that we are advertising is a four inch D ring binder. whereas the competitor that we are targeting is a sheet protector, which serves a very different purpose. Right? Yeah. Which is why even if we run targeted ads on this competitor, we may not convert. Right. So that is one type of insight that it is found here.

 

Ben Matthew 00:45:42  here again what it is found here. The product that we are advertising is a different size compared to the ad. compared to what the product that we are targeting. The customer is looking for a tabloid size, product, whereas what we have is a letter size kind of product. Right. Or the size is basically different. So, 80, 90% of the time we typically see the product does accurate results, but there are still 10% of the time, maybe 10 to 15% of the time, maybe we see some hallucination. Yeah. So here is found the product that we are selling is what the one that we are targeting is a 0.8in touring binder. Whereas what we are selling is a 2.5in, three ring, letter size binder. So that’s why we are not converting for this keyword. Okay. So apart from this, there are a few more things that are, you know, organic rank, basically related, optimization, for example, it will look at keywords that are important for us organic rank wise.

 

Ben Matthew 00:46:43  it will monitor whether our rank is improving or not. If our ACOs is good, really low, then it will recommend a 10% increase. Right. So, here our our rank is improving or can improve our ACOs is low then as compared to, our campaign. So it is recommending increasing the bid. similarly if there are rank is improving no orders low clicks. It is recommending bid bid increase by a certain percentage. So all of these again by going to the instruction you can ask this agent to customize or do differently.

 

Josh Hadley 00:47:15  Yeah. Okay.

 

Ben Matthew 00:47:18  So those are all the major actions that that I had to run you through. So, so the data again, like I was saying earlier, this agent has access to data that is available via Seller central APIs. Data that is available from the shopper facing customer website. It could be your listings, competitor listings, search results of a search term or best seller node, and it can collect this data over a period of time. Let’s say last three months data analyze month over month for you, and then Jungle Scout data to find keywords that competitors are indexing on, a data to find price and BSR for competitors and you using this, you can set set up most kind of tasks.

 

Ben Matthew 00:47:58  So right now what you see here is tasks that are pre-built that you can run but you can customize. we work with, customers to understand what tasks they want to automate, and we add those, tasks to the product. and after understanding what, what do they spend a lot of time annually on? And that’s something that we would like to do with, designs as well. And, after 3 to 4 months, what you would see on the product is a ChatGPT type interface where you can interact with the agent and ask it to do whatever you want it to do. Today you are still telling us what tasks you want us to automate, but you won’t have to do that. You can directly do that on the product. You can ask the agent to analyze something until you find something, until you call or ask it to do some task and do it for you. So that is something that is expected over the next 3 to 4 months. Right now, a few other tasks that we are adding here are.

 

Ben Matthew 00:48:48  One is inventory planning. Looking at how much is your sales for the last seven days, 30 days, 90 days? How much inventory do you have in FBA right now? How much is inbound? And this agent can refer to a Google sheet that you have where you can put in level lead time. And including all of this data, it can tell you how much inventory you need to dispatch to Amazon, for example. Another task that we are launching is week week week to week comparison of your listings. So last week versus this week has anything in your listing change title, bullets, images, ratings, price or something else? And if your sales is dropped or conversion is dropped and some changes happen, it will. You’ll be you’ll be able to see that as information. Another task that is going live is. Back end keyword creation. If there are keywords that are different languages but we can’t put up in put, put the ranking really well for competitors, but we can put them in a title or bullet point.

 

Ben Matthew 00:49:38  So we will collect them for back end keywords. So like that get back end keywords from a few different sources and create those back end keywords as well. So these are there are a couple of tasks in the pipeline. So these are some that are coming out in the next 3 to 4 weeks.

 

Josh Hadley 00:49:51  Man Ben I’m I’m genuinely excited because like especially as you talk about the inventory planner, like you were hitting on all of the things that, you know, we have to hire like Vas or specialists to be able to, like, gather the data for us, present the data for us so that our leaders can make the decisions and the calls for these. And if what you’re saying is true, these things can actually be automated and presented in an easy to read fashion, and then utilizing the use of AI, it’s going to be able to draw faster results for me like I. You’re on to something very, very big here, Ben. That like if what you if if what you say can actually be true in the real world here in e-commerce, I think you have a game changing tool that, you know to our audience, like, I’m not Ben’s not paying me to say this.

 

Josh Hadley 00:50:50  He’s not a sponsor of the show. I’m not even a subscriber of his software right now. I’m genuinely looking at this being like, Holy cow, as a business owner, this changes the game of who I need to hire. And to be honest with you, like people will sometimes wear it as a badge of honor. Like, oh, I’ve got 50 team members and everybody’s like, oh, that’s cool. Like, I think it’s the exact opposite. I want to see how much revenue you’re doing, how much profit you’re doing. Like revenues, vanity, profit is sanity and how little team members you can get to do that level of profit. That’s where the magic sits. And I think if this tool is all it’s cracked up to be, can be that game changer to where, like, I think there is a point in time where like there is a one person solo, wicked smart Amazon business operator that utilizing a tool like this. Exactly. And a bunch of AI agents, it’s a solo shop.

 

Josh Hadley 00:51:52  One person doing it all, $100 million brand, right?

 

Ben Matthew 00:51:56  Absolutely. I see I feel that that will be that will happen very soon. soon in the sense maybe 3 to 5 years, you’ll certainly see that, but that transition will be gradual. Like you said, instead of 50 people, we’ll start soon. Start seeing people running $50 million brands with five people for people, where a lot of the routine grunt tasks, grunt analysis is done by AI agents and their team members are spending a lot more time creatively thinking about how to do things, instead of having to operationally manage all the tasks and the people, they would be spending more time creatively thinking about where do we generate the maximum alpha to grow the business?

 

Josh Hadley 00:52:33  Yes, 100%. My experience has been more people, more problems in the business, right? Because humans have lots of variableness to them, right? You’ve somebody passes away or there’s vacations or somebody’s kid is sick. They’re sick. You have to manage that. It is true management.

 

Josh Hadley 00:52:51  And so A.I. doesn’t need to be babysat that way. So I’m a big fan.

 

Ben Matthew 00:52:55  Exactly. Yeah.

 

Josh Hadley 00:52:56  Ben, as we wrap this up, I love to leave the audience with three actionable takeaways. So here are the three actionable takeaways that I’ve noted. You let me know if I’m missing something. Action item number one I’m going to say this. Anybody that is not adopting the use of AI into their business, this. You’re going to be far behind. And so that leads to kind of the second action item. So number one is learn AI and follow the people that are talking about AI stuff. Ritu Java has a great newsletter that she puts out that’s about AI tools for e-commerce. So that’s a highly recommended one. And like begin actually taking action to implement those AI tactics into your business. Because action item number two is that the speed of your growth as a brand owner is directly correlated to the number and the speed of decisions that you are making on a day to day basis. A lot of people just get hung up in.

 

Josh Hadley 00:53:59  I’ve got a I’ve got to think this over. I’ve got a I’ve got to sleep on it. I need more data. I need to see more. I don’t feel comfortable yet. Like every time you postpone a decision. Now, sometimes there’s there’s two different types of decisions. There are irreversible decisions where if you make. If you step through the wrong door, you fall off a cliff and die. Right? There’s no coming back from that. But most 90% of business decisions I believe that are made is if you open up this door and you go down the wrong path, okay, you’re able to reverse course. Hey, I thought it was this one, actually. Let’s go to the next door. Right. And you keep going until you find the right next door. I think those are the two different types of business or decisions. So the more quickly you can identify those, those decisions that are like, they’re reversible, you’re like, let’s go this direction. Because even if we’re wrong, it doesn’t blow the business up.

 

Josh Hadley 00:55:02  But I got to make decisions quickly. And I think I allows you to make those decisions quickly. Third and final action item here is to hire smart leaders? Absolutely. Everything that we talked about in this episode today, you could hear, like, I need to have my supply chain manager utilize the inventory planning feature, and it makes her job, his or her job ten times more efficient, right? I need my creative director to utilize this tool to get all the ideas and all the information in one place, make decisions ten times faster. I need my Amazon Brand Manager to be able to execute these strategies ten times faster. My PPC manager ten times faster. So guess what my organization looks like? All right, maybe it’s not just one person, but maybe it is 5 to 10 people that are just wicked smart leaders in very specific roles PPC, brand management, inventory management, supply chain. you’ve also got creative director. and those are your people. That’s your core team that you go to battle with, and you’ve got AI agents that actually execute on those things for you.

 

Josh Hadley 00:56:22  So that’s the future I see, Ben. Is there anything else that we didn’t address, or any other action items that you think we need to call out here?

 

Ben Matthew 00:56:31  Well, I think, yeah. I would just add to the first point that you mentioned, as specifically on e-commerce. We are in a, in the, in a in, in the world, which is a marketplace where the best ideas are winning and the best ideas are in terms of efficiency to reduce price efficiency, of creating the best products, best creatives. So in the marketplace, it’s even more important to be ahead in all these areas. if we were a different business where we are a monopoly, let’s say in a different category, let’s say building software for salon businesses. Then there are very less players to compete with. But in our case, as we sell consumer products, we are in a competitive landscape. So the ones who win are the ones that you mentioned. Do those three things well, and that first thing you are doing, I really well is going to be very important to win.

 

Josh Hadley 00:57:25  Love it. Ben. Great summary here. Lightning round time final three questions. What’s been the most influential book that you’ve read and why?

 

Ben Matthew 00:57:33  Yeah. So it’s been the Everything Store story about Amazon. This is something I read when I was working earlier. It had been really eye opening, in the sense of, in the sense focusing on innovation, how to think about long term innovative bets, focusing on execution, how you can execute a lot more than what you think. So that has been a big eye opening book for me. I’ve read it a few times too. I keep going back to it to learn from it.

 

Josh Hadley 00:58:03  Love it. Great recommendation. All right. Question number two. And you can’t say super fuel. What’s your favorite AI tool that you’ve been using or ChatGPT prompt and why?

 

Ben Matthew 00:58:14  Yeah, so I a couple of them, the most commonly that I’m using these days is I’ve been a non coder. although my all my, the rest of the team members are software engineers. So, but it’s very important for me to catch up on, understanding code and how code works.

 

Ben Matthew 00:58:31  so I built a, GPT, which, basically any code that I’m trying to, like, my team members exchange with each other, I post it in my post, it in that GPT and the GPT tells me what each of those items in that in the code, code is. So what is what do they mean? What does the code do? So I’ve been using that to learn, what what what these lines of code mean?

 

Josh Hadley 00:58:57  Always super powerful to have some custom GPT.

 

Ben Matthew 00:59:00  Yeah.

 

Josh Hadley 00:59:01  All right. Final question. Who is somebody that you admire or respect the most in the e-commerce space that other people should be following and why?

 

Ben Matthew 00:59:08  Yeah. So, in the e-commerce space, I mean, a lot of people I learned from, so one is Sean, the founder at, Dude Vibes, who’s been focusing on building, innovative product and focusing on creatively marketing it, and bringing that bringing the product to the, to the masses, and focusing on building just that one product, as a ten, as a decade year old business so that that’s someone I really admire.

 

Ben Matthew 00:59:40  and, apart from that, in the Amazon world, there is another brand called California Design. Then they do about $100 million a year, being in touch with, the founder of that company called Deepak Mehrotra for the last three years now, learned a lot from this gentleman how he thinks about, selling on Amazon, winning on Amazon. it’s been pretty, inspirational And the eye opening.

 

Josh Hadley 01:00:05  Was that California designed in.

 

Ben Matthew 01:00:07  California designed. And so you would see them among the top 3 or 4 organic rank on Amazon.

 

Josh Hadley 01:00:12  Awesome. I love it. Well, Ben, this has been a great episode. If people want to learn more about Super Fuel or learn more about you, follow your journey. Where can people follow you at?

 

Ben Matthew 01:00:24  Yeah. I love catching up with the folks in the ecosystem helping where I can. I’m here because other people help me. I’m available to help people who want to learn about, how to use AI or other areas where I can be helpful. I’m reachable at Ben at super fuel.

 

Ben Matthew 01:00:41  Oh, that’s my email address. I’m also active on LinkedIn. You can find me on LinkedIn and message me. I’ll be more than happy to do that.

 

Josh Hadley 01:00:50  Awesome. Ben, thank you so much for your time today. It’s been a pleasure having you on the show.

 

Ben Matthew 01:00:55  Yeah. Thank you so much, Josh. It was a pleasure being here. Thank you so much for hosting me and putting this together for more people to see.