How Relaunching the Same Product Made Me $3,000,000+ Dropshipping

Yo, what's good YouTube? Welcome back to another video. Now, in today's one, I'm going to be breaking down my exact product launching framework that I'm running. It's a two-step framework. The hit rate for it right now is absolutely insane. Uh, and just some results from the other brands. So, you guys know I'm not, you know, bullshitting. I actually do this. I'm going to be showing you a lot more results as well in a second. But yeah, you guys can see two 10k order plaques there. There's my father right there. Sorry. But anyways, jumping straight into it. I'm going to be showing you guys a textbook Galad winner. Now, if you guys are drop shipping, this is pretty much going to be the ideal situation for most of you guys. You know, you find a product that solves a problem, has a wow factor or whatever, and you're launching it, and this is pretty much the results you're looking for. Like, this is a product launch from last year. It was one of our uh kind of little pump and dump stores. You can see here, day one of launch, we had 15 orders, and then we had uh I don't know, it was like a 3.5 rorowaz on $150 spent. The next day, 6.94 rorowaz. Absolutely insane. And you guys can see literally within 2 days of launch, we're already at 1K days. Now, the only issue with this method is it's not the product, it's the creatives. And what I mean by this, it's a little bit confusing cuz our testing structure was different last year, but assume all of these are the same ads. They just launched in interest campaigns or interest adsets, should I say. What you can notice here is one of the ads is just carrying. And the point that I'm trying to make here is when you rip off Caladata and you find a winning product off the bat, it's not the product, it's the creatives. And you'll see this time and time again. You're essentially relying on luck if you are doing this Kalad method where you're just ripping one to one and editing blind. And this is what usually happens is you'll find a winner. Uh you'll think drop shipping is easy. You know, you've cracked the code. You'll be able to scale this product for about a month or two depending on how good your ability to brand products are. Uh if you can't, you know, performance is going to tank. You're not going to be able to replicate it. You're going to say drop shipping's luck and maybe you'll use your [ __ ] results to sell a course. And with the newest Andromeda update by Facebook, it is only going to punish the Caladata method even more. And what this Andromeda method essentially did is it's rewarding larger swings in your testing. And what I mean by this is if you are selling just say like an anti-aging supplement. The core desire of this or like a wellness supplement to older people. Just say one of the core desires is anti-aging and the persona is moms after pregnancy. If you're only launching UGC content, the introduction of this update is going to essentially have a negative performance on your ad account because what it's doing now is it's it's grouping them based on which ads they are resonating most with. So just say for an example here, Sarah, 42-year-old mom who's noticing early signs of aging. Now cortis anti-aging persona might be moms after pregnancy. This is just an example I'm using here. And her ad behavior is she engages more with UGC content, relatable videos, hooks, and the authenticity matters. As compared to Emily, who's a 39year-old mom, she's experiencing the same core desire and under the same This should be the same persona. That should be the same persona. I just changed that. She might be more interested in your static images with your long form primary text or a different ad format. Now, the point I'm trying to get out here is if you're only ripping and launching UGC content, you're missing out on a significant portion of the people that could be potential buyers for your product. So you can see that you know and that's why I wrote this down here just to further emphasize the point. If you're only ripping off Calad data, you're getting one format of ads. So therefore, you know, your performance is just going to get [ __ ] Moving on to what I like to call bad product scaling. Now this is essentially just again changing the way you speak and the way you operate as an like a brand founder essentially. Instead of being my product sucks, switching that mentality to my ads and my offer sucks. And I'm going to give you a clear-cut example on exactly what this looks like. You guys can see here this was two weeks of an initial product launch for me. 21st of May, 4th of June. This is this is when I really started doubling down on this strategy. All the initial ads that I was launching sucked. You can see there 1.21 rows. Absolutely trash. As soon as we located a winning ad, you can see here from the 5th to the 12th. Now this is just iterations around that specific ad. So that's why it's performing significantly better. You can see the rorowaz jump. Like we went from 1.2 one week to 2.63 63. And the point I'm trying to make here is you can see that most of you guys would have killed this product. Most of you would have said guys would have said it's a bad product, whatever. But truthfully, it was just we hadn't found a way to communicate that product to someone and make them impulse buy. And you can see with this method as well, scaling is so much more effective. Like we were able to jump from this to this. You can see maintaining healthy rorowaz. And then the 22nd of June was when this store had its first 10k day. Like and you can see it's still printing to this day. So, it's like a million times more sustainable. Now, before I show you my launch system, I'm going to break down the two-step launch system because this is still using Caladata. And this is exactly if I do see a product I like on Calata, the way that I launch it. This is just a funny photo I saw on Twitter, pretty much summarize a lot of the ecom space. Uh the difference between focusing on [ __ ] that matters and not. I don't know why I [ __ ] decided to include that, but anyways. Uh yes. So the biggest difference again is literally just changing your mindset. Product didn't work to my ads aren't good enough. It's the that's the point I'm trying to drive home with you guys here. So the first launch from Kaladata is literally just going to be a data launch. I'm not looking for sales. I'm not looking for anything. I'm literally I'm just buying data essentially. Uh so I'm going to launch and I'm going to launch with a pretty general offer and landing page. I'm going to launch ripped ads, statics. Like I'm not just going to go all in on that UGC content because like I was explaining before with the new Andromeda update, you have to be pretty broad with your testing, which is why I said test wide. And then you're going to let these ads cook for 5 days. Now again, and again, I really emphasize the point here. You're buying data. And what I mean by this is when it comes to day three and you guys aren't profitable yet, don't don't go run around [ __ ] throwing your hands up in the air and turning off all your ads and moving on to another product because truthfully, that's just part of the process. Now, the second launch, this is when we're going to be doubling down on intent. And this is when stuff starts to pick up. So, we're going to use the data that we just bought and launch follow-up tests around this. And what I mean by this is you guys can see, so you got avatar one here, avatar 2, avatar 3, avatar 4. You can see I'm separating them and I'm also using different ad concepts in each to really see what's resonating, see what's not. And if you do notice a specific avatar that is crushing in your Caladata launch, or if you have a product that doesn't have several different avatars around it, maybe it's only tailored to one, um, just change this around and just try launching several ad concepts around that specific avatar. Now, when you launch, study which ad spent the most and then I want you to determine whether this ad is hitting the KPIs or not. I'm going to assume 99% of the cases it's not hitting the KPIs. So, what to do now is to really troubleshoot and really get an understanding of what's going on. Because if the ad that's taking all the spend in the campaign is a very top ofunnel ad and your landing page or your product page or whatever you're sending your traffic to, if it's not essentially aligned with that ad in the sense that if you're running to like a bottom of funnel or middlefunnel LP, people are going to get confused and they're going to click off. So, you need to make sure that kind of everything's aligned and there's no funnel misalignment. Um because if there is if because if you're sending people who have no idea what your product is to a page that already assumes they know what it is, uh it's going to create a lot of friction. Now, another one another good one to study is the CTR just to see how well your ad is actually resonating with that audience. Now, something that's very very important here is just because an ad takes spend within your CBO does not mean it's a winning ad. And what I mean by this is if you're launching terrible ad, terrible ad, terrible ad, and a bad ad, and the bad ad's the one that gets all the spend, you know, your results are going to be reflective of that and they're they're going to be pretty [ __ ] We still want to open our testing to other avatars and, you know, other ad concepts. We don't just want to be like, all right, this ad spent everything. Let's double down on this ad concept and this avatar that it's targeting or masses are, whatever. So, if you dedicate like 40% of your time to making iterations around that specific winning avatar and you spend the rest of the time trying new variations of different avatars and different concepts, that's a pretty good testing ratio that I found and it's how I'm able to locate winners pretty quickly. Now, if the follow-up test you do launch is hitting your KPIs, really get an understanding of why was it the hook, primary text, whatever, and then you're going to want to launch iterations around that same persona using different concepts. What I mean by this, if you launched a AI voiceover ad at moms who want to lose weight, you could then go and launch statics. You go and launch, you know, more AI voiceover ads in a different format like testimonial or problem solution, whatever. You can do a long primary text static ad. There's so many different like variations. And then you can also just work your way down the market awareness stages. You're essentially able to milk a lot of ads around a specific concept, like way more than a lot of you guys think. Now, moving on to the actual like my launch system that I'm using at the moment. this is crushing it. And when I mean that, I don't say that lightly, but it is very dependent on how well you are able to market stuff. So maybe if it's your first product launch or whatever, or maybe if you're very new to drop shipping, this isn't going to be the ideal system for you, but I thought I'd just include it so you guys know exactly what I'm doing at the moment. Now, we're going to I think this is like Mark Builds Brand Strat as well. I'm not coming saying I'm the original founder. It's just the one I'm using. Uh so literally, I'm just going to choose a problem that actually solves a problem. Uh, I'm going to make sure that problem also has a big enough TAM, which means I can scale it to 100K days. And an easy way to validate that is by looking at the competitors and making sure they are doing 100k plus monthly visitors. Use similar web to determine that. And we're going to be able to come into this proven market now that we know works. And the only thing that's lacking is our ads and our offer. And if you can find a better product as well, that's also a bonus. So, how does week one look for testing? I'm going very hard in on market research in the beginning. Now, I'm not talking just going to chat GBT because another big thing I see a lot of you guys think market research is going to chat GBT, clicking on deep research, and then just it's spitting out a bunch of stuff about different personas, desires, whatever. And then you're like, that's [ __ ] sweet. I'm going to go ahead and copy and paste that into my market desire or market research doc, and then I'm never going to look at it again. That's not market research. like you guys need to be getting an understanding of what people want to see, what they don't want to see, so you're essentially able to communicate that to them because the better you understand the customer, the better you're going to be able to talk to them, and you know, the higher ad hit rate you're going to have in return. So studying what angles are the competitors running, identifying the main avatars, what ads are competitors running, are they going all in on AI, voiceover ads, statics, whatever, are they running preanders? This is all stuff you guys should be yourself. Now, the the point I'm getting at here with angles is you're able to use something called the purple ocean strap, which is taking a product that's already working, going doing your own research, and finding an angle that is unsaturated, and then using your creatives to target that angle. It's a very, very effective method, but it is pretty [ __ ] hard. Like you guys saw from that original creative, like that ad account setup I showed you, we were unprofitable for like 2 weeks. And that doesn't sound like that long of a time, but a lot of you guys won't even go 3 days on the same product. Uh, and if you're not profitable, you're just going to drop it. So, yeah, I'm really trying to change your perspective here. Now, what does my testing structure look like? I'm going to launch three to four high intent 322s around the top avatar. Now, what are 322s? You take one concept. So, one avatar here as an example. You're going to make one AI voiceover ad, like a very high quality one, and then you're going to give that AI voiceover ad three hook variations. You're not going to change the body. You're not going to change the primary text, whatever. You're just going to change the hook. We're going to replicate this with each one of the concepts. Uh you can see I just whacked together a bunch of different ads there. And you're going to leave this for I should put 5 days. 3 days is too short. Now, because we were testing very wide, we can then look at which avatar is taking the spend. So just say for an example, we have a $100 budget and you know, these avatars didn't really spend and this avatar here, it spent $80. Now I really want to break down why this avatar/ ad spent, if it's hitting the KPIs, and how I can iterate on it. Now, what I mean by iterating, this is exactly what I mean. So, video one, just say it's a product focused ad that is highlighting the features um like it's just an AI voiceover ad essentially. It's not like a testimonial style. It's just an AI voiceover ad that's highlighting what your product does and how it can help people. You then want to be launching your iterations around a hypothesis and aim. And what I mean by this is again, all this is is about completing positive feedback loops in the sense you're becoming smarter with each one of your tests. you're understanding what the customer wants to see, what they don't want to see. So this is exactly how I structure it. So if I include X, then Y should happen. And this is a pretty good example of this. So if I run a testimonial style ad, this is comparing it to the product ad. CTR and conversions will go up because people are going to be more willing to trust the relatable story and the story that's resonating with them just more than the general product showcase video. So we launch this and then if it overtakes the current top spender, uh we have to determine why. If it didn't, we're going to do the exact same thing. All of this is about asking questions on why it's not working. Like, was it the hook? Was it the visuals? We can then create a new hypothesis, which we can test on the next video until we find something that works. And that's why I said positive feedback loop created. We've got the data. And now we can utilize this data in the next ad. And that's how we're going to be able to just keep pushing and pushing and pushing and locate a winner very fast. Cuz you can see here, this might be our week one results. Week one, 0.5 rorowaz. But now we have the information that avatar one, the top spending avatar, prefers seeing visual A, B, and C over visual D, E, and F. Now, the best part about this, it's a win-win situation because not only are you going to be getting smarter, Facebook is going to be getting smarter as well as it starts to allocate spend to creatives and see how they performed, it's going to be getting data into the pixel as people are buying. Even if you're running at a negative rorowaz, Facebook is just going to becoming smarter. And if you're able to just replicate this and stay consistent with it and really get the [ __ ] mindset that the product isn't the issue, it's your ads or your offer or your landing page, then you're just going to be able to 10x your results when it comes to drop shipping. This is literally like my entire testing method at the moment. Pretty complicated, but I'm I'm confident if you implement it, you can get similar results that I'm getting at the moment. I'm about to have a crazy Q4. Uh, a lot of hard work to be done, but I really want you guys to win as well. If you do want to join the free Discord, you can in the description. If you have any other questions as well, message me on Instagram. But apart from that, boys, that's it.