How to Combine Organic, PPC & Ranking Data with AI to Optimize Every Amazon Keyword

How to Combine Organic, PPC & Ranking Data with AI to Optimize Every Amazon Keyword Speaker 1: What's going on friends? I'm here on summer vacation over here in Switzerland. Hope you're having a good one. And first, I need to take some time away from that vacation and say, what's going on Badger Nation? Welcome to the world's first and longest running show all about how to make your Amazon advertising life a little bit easier and a little bit more profitable. Today on the show, I'm going to be sharing a presentation I did for my dear friend, Elizabeth Greene's seminar. She asked me to prepare something about AI-based optimization for Amazon PPC. I wanted to talk about something that I thought was really terrific that AI does, which is of course, combining data so that you can know where to bid more and know where to bid less. Almost as if you had a Amazon PPC assistant who is sitting next to you and sort of giving you tips and feedback about what keywords to bid more on and which ones to bid less on and why. What you're going to get from this is basically An analysis using multiple data sources combined to give you some situations like, is your organic good? Is your organic bad? Is your impression share good? Is your impression share bad? Is your ranking good? Is your ranking bad? And sort of cross-sectioning all of those things. So ultimately, it will give you, essentially, Action items for every single search term in your account, which is really cool. You can do this by product or on a larger scale, which is also very neat. But essentially what you'll see here is that for each search term, it'll basically tell you how many orders you got for that search term. If you have strong organic ranking or weak organic ranking, if you have a lot of clicks, are you winning a lot of these clicks? Do you have a really strong impression share or not? Is the ACoS high or low to sort of clue you in and nudge you into what direction you should take Any of these search terms, should you bid more, should you cut it? What's also cool about this analysis as you sort of go through it, it's basically a lot of people are always curious like where can I reduce bids because I'm ranking organically really strong. What this does is this data will tell you where you're ranking well organically, if you're converting well using search query data, as well as do you have a really strong paid impression share. So you can see in this very first example, this was like a row for a search term that says I have strong organic, good clicks. Yes, I'm converting. I have a strong impression share. If the A cost is low, perhaps I am Can cut back bids there, eek some more profit out of it. The hardest part of Amazon Still today is goal setting, knowing where to lean into inertia, pull back for momentum, total late cost profitability. And the reason is because it's one big ball mashed together, right? On Google ads, on Shopify, if you're optimizing your Google ads campaign, you're often just looking at the Google ads campaign. Google ads isn't really influencing your email marketing revenue necessarily. It's not influencing your organic share necessarily. There's no real concept of like, if I get more sales velocity, I'll rank better. On Google ads, on Amazon PPC, there is, right? It's all one big ball matched together. If you're getting a hundred sales a month for a keyword, then you crank up your PPC and get 500 orders a month for that keyword. You should generally notice an organic ranking lift because you have more momentum, right? So I would say that still today in 2026, it's very difficult for anyone to set goals. Sometimes I see people with hyper vision, like hyper tunnel vision on any one metric. Maybe it's ACOPS, maybe it's profitability. Amount, and they're not thinking of percentage, or maybe they're thinking of profit percentage, but not profit amount. Maybe they're thinking of ranking too much, or total A cost too much. All of these things are very confusing, and when you mash them all together like you do on Amazon, it's very difficult. So what I wanted to use, whether it be Gemini, ChatGPT, or Claude, to be able to sort of parse this through, and I wanted to give you some guidelines here. So really, shout out to anyone that watches It's Always Sunny in Philadelphia. It's a top show for me. Anytime I'm sick, I'm turning on It's Always Sunny in Philadelphia for sure. So think of it this way. Imagine you're able to look at a keyword. And the hardest part about PPC optimization on Amazon is that when you're doing PPC optimization, You don't have total ACoS on your Amazon ad console. You don't have your organic ranking there. You don't have your total ACoS there. You don't have your dot, dot, dot, insert many metrics. You don't have your search query performance inside your PPC account, and so on and so forth. So really, when you're optimizing a keyword, yes, you have to optimize based off what is available in the PPC account, which is your revenue per click, your cost per click, and your target ACoS, which is, of course, the ratio of your revenue per click and your cost per click. Got it. But imagine you were able to make even more informed decisions. And there's lots of ways to make more informed decisions. Talked about it a lot on the show. One way is to view multi-date range analysis at every chance so you can see how these things are influencing each other. Maybe I'll save that for another episode. But really what you want to do is you want to be able to assess something, whether it be a keyword or a search term, and be able to view it from different perspectives. So maybe you have strong organic rank and low impression share. You might want to have a framework of what you want to do in situations like that. Maybe you have a high impression share and a strong organic rank. Maybe you might consider that double paying and you can play with maybe reducing bids ever so slightly on those expensive keywords that you're already ranking for very nicely. It's always a hot topic. So really what we would want to do when we're looking at PPC data is imagine if you were able to go in and grab organic data and search query data. And just mash it up together so that you had a good sense of like, does this keyword rank well organically or not? Are my ranking efforts working or not? So in this presentation, I just wanted to walk through a little bit of the process. In January, 2023, as you know, I'm part of a mastermind core community. We meet once a week. We talk about Amazon PPC, talk about Amazon marketing. Truth be told, shout out to everyone on these masterminds. I haven't been going the last two weeks because I'm here on my summer vacation, but Way back in January 2023, Gonza, one of the members there, super successful e-commerce seller. And I love learning from him because he's an e-commerce seller first, not an Amazon marketer first, which I think is a really interesting distinction. I always love to talk to him about that. He gave a presentation where he talked about how he was combining PPC data, ranking data, search query data. And you can see this on the AdVenture website, right? Like if you go to the adventure.com website right now, I have things like this. I've had a lot of joy and a lot of success building things like this and analyzing campaigns. I've shared many of these things. Over the last 10 years, there's been 35-ish thousand people that have got one of our spreadsheets in some way, shape, or form. Maybe you listening on this episode, you've seen these podcasts. You've seen these spreadsheets, where basically what you do is you take this report, you mash it into a Google Sheet, and then it will give you some output, which is cool, right? One of the most popular ones we've done was Ngram analysis. We have another thing coming, which is called Badger Sheets, which will basically be a place where you can just drop any spreadsheet and get this sort of kind of analysis. I'll have more details on that in the coming weeks. But basically, it was always like, go download this, put it into Google Sheet. And then get this analysis. So you can see here that this data comes from search query performance, brand analytics, sponsored product, search term, impression share, Helium 10 ranking in this case. And what you would do is you would just paste in everything, right? Paste over here, paste your search query data, paste your brand analytics data, paste your sponsored product data, paste your ranking data, right? You do all this stuff and you would get this cool spreadsheet. Cool, neat. But how this has evolved What I've learned is that spreadsheet work can now be done with your favorite AI chatbot. You can give it your spreadsheet and instead of you opening up Excel or Google Sheets or LibreOffice or whatever spreadsheet tool there is, you can have AI do that for you. It knows every formula for you. It knows everything for you. So when I was doing this report, I've done this report many times because I always found it so insightful to be able to look at your PPC data right next to everything else. The fastest was like 30 minutes, right? And this is me going at top speed, knowing exactly how to do it. I would talk to people who didn't have that, you know, 10 plus years of Excel training. That would take like two hours to prepare this report. And what AI has done is just sort of brought this learning curve to almost nothing, right? Where what you're going to get here on this episode is basically I'll give you the prompt and I'll tell you what report to download and then you can go produce this yourself, even if you've never opened up a spreadsheet in your life. So the mental framework is really give AI data, talk to the data and know what questions to ask. And I would say that when you're talking to AI, a framework that I love is like AI knows a lot about stuff. The PPC Den is a company that I don't know about. So I know nothing about heart surgery. If I ask AI about heart surgery, it will tell me stuff. But if I'm a 20-year veteran of heart surgery, I will look at that output and be like, it's missing so many things. Same thing when I look at Amazon PPC data. If I just go and ask AI about Amazon PPC data, it'll give me fairly good generic advice, but it's really unrefined and incomplete. Your favorite chatbot. Spreadsheets and a structured prompt is basically you're standing almost like on the shoulder of giants, right? Like I've done this a lot manually, thought about this process, and I helped craft a prompt for you. So if you go and give it these spreadsheets and a prompt, you'll get some pretty good output, right? So the first piece of data we're going to grab is search query performance. I've talked about search query performance a lot on this show. It's basically your search, click, buy behavior. How people interact with your terms, how they interact with the overall market, and it gives you your percentage of clicks, your percentage of orders. It's fantastic data that combines PPC and organic performance. One thing we built inside AdBadger is a way to analyze this data In a way that is double date range comparison, right? One bummer about this is that you can only pick one date range at a time. You can only view one product at a time. Inside AdBadger, which I think gives AI analysis an even better leg up, is it has every product and multiple time frames in one sheet. So when I export, you know, 3,000 rows and I have Gemini parse through it, It gives me some really rich data, which is really cool. Because again, the thing that we're after is combining. Even if you don't have that and you're just going directly from Amazon, you're still going to be way ahead of everyone else who's not doing this analysis. The next thing you'll do is you go to your sponsored ads reports and you will download a search term impression share. Basically tells you what your share of paid impressions is, right? So you can be number one search term impression rank. That means nobody got more impressions than you did. It's also worth keeping in mind that, you know, Amazon's constantly shuffling the SERP so that Even though I'm impression rank one, I don't have 100% impressions, right? So that's some good information to know. The next thing that you'll want to know is, of course, your ranking data. There's lots of different ways to get ranking data. Helium 10 is a popular way. AdBadger, not to pat myself on the back too much, we also have rank tracking inside of our tools too. So you can get it in multiple different ways. But you want to know your organic rank, your search and impression share, and We're going to talk about your search query data. And you can also go and get your brand analytics top-clicked terms as well. You can punch in your ASIN and then you can go and take a look at what you're getting clicks for, what your conversion share of those terms is as well. So again, we're looking at something very similar, right? We're looking at search performance, combining PPC data and organic data, and overall search behavior, which is really cool. So it's search query data, top search terms from brand analytics, Sponsor product search or impression share and organic ranking data. And then my friends simply put, you run the prompt, right? You run the prompt, you look at it and you can just copy and paste this, drop it right in. I would also invite you to read through this and you can tweak it, right? So here I talk about a target ACoS. You might have a different target ACoS. I define a strong organic You might have a different one. So read through this. If this all looks like a foreign language, just rock with it the way that it is and begin to just ask questions as you work through it. But essentially what you'll be able to do here is basically categorize your terms. And it's really cool once you do. It will tell you for each term, if you're ranking strong organically, are you winning clicks through paid? What's your impression share? All these different things. So if you have a keyword that isn't ranking, has a weak impression share, and the A-cost is low, bid up on that bad boy. If you have something where the A-cost is high, maybe lower the bid, right? It's just a really simple way to give you insight into your campaigns. So my friends, The good people out there in Badger Nation, I always try to end each episode by ensuring that you have something to go and do. And these are the four things to go do. Go download your search query data. Go look at your top search terms inside Brain Analytics. Go look at your sponsored products, search term, impression share, and grab some organic ranking data. And in fact, you actually don't even need to look at these files. You don't even need to open them. Give all four of them To your favorite AI, whether it be Gemini, Claude, or ChatGPT, crank up the thinking all the way to the max and give it that prompt and see your keywords in a new light. See your keywords next to your organic data, your market penetration data, and get some new insight into how your search terms and your keywords are behaving. Go forth, optimize, and I'll see you next time here on The PPC Den Podcast. Unknown Speaker: And pick keywords. I've got my bids. Some placements too. Now bad music. I've made a few. I've had my share of problems. Oh yeah. You are the creepy shit in my frame. We are the PPC Den. We're talking about Amazon. No time for medicons, cause we'll fix the game, baby.