The Art of Amazon PPC

The Art of Amazon PPC Speaker 1: Alexa, play That Amazon Ads Podcast. Unknown Speaker: Which one would you like to hear? Speaker 1: The best one. Unknown Speaker: Okay, now playing that Amazon ads podcast. These gentlemen are completely changing the game. Speaker 2: After listening to that Amazon ads podcast, my ads are finally profitable. Unknown Speaker: I also heard they're pretty cute. Speaker 1: Now, Andrew, the idea for this topic came about through many of the conversations that we've been having recently. With people in our Discord community, which by the way, if you haven't yet joined the Discord, make sure you do. Link in the description of the video or the podcast if you're doing audio and join there so you can ask questions, hang out with us on Discord and talk about Amazon PPC. But we're getting so many questions from people saying, what date range should I use? Or what should my max increase decrease be? Or all these types of things that they're expecting a cut and dry one right answer just Something arbitrary just like you should always be using 30 days when the fact of the matter is that there is a huge component of exercising human intuition. And all of these variables that we use in our optimizations are highly, highly dynamic. And I don't think I've said this on the podcast before, but if you were to look through my bid-change history for the accounts that I'm managing, You would see that on all of my change logs, there's not a single optimization that I do that is identical. It's not the same look back window. It's not the same number of campaigns. It's not the same target ACoS. All of these metrics are highly variable, dynamic, and part of the art that we're gonna be talking about today. But before we do that, Amazon PPC is also a science. So, Andrew, what are some of the things that are more on the science side of PPC management? Speaker 2: Definitely, and that's really well said. People try to deduce things down into simple black and white answers and we've been kind of conditioned to do so because there are so many components in Amazon PPC that are a science, that are mathematical, that are important for us to have clear-cut answers to and there's a lot of things that are and a lot of things that aren't but those key things that when we talk about Amazon PPC as a science are basically just the math and that's pretty much the way to put it. The things that are mathematical, those things are black and white. Those things can be deduced down to simple formulas that will output certain Outputs at certain things. And, you know, whenever we talk about how to calculate your placements, you know, that's pretty cut and dry. That's your, that's some simple math for you. How to do day parting, when you should be increasing, when you should be decreasing your bids, that's going to be relatively mathematical. And we can look at that as relatively black and white. And yeah, that's really, really kind of the core of what we talk about on this podcast is, is really getting to those things that are black and white and sharing our opinions on those. But there's so many other things that require that nuance. And like you said, every single change needs to take in that human context and be applied to very specific goals and objectives for every single change that you're making. Speaker 1: Yeah. And something else too is you'll hear a lot of people, you'll see it on YouTube, on LinkedIn, on blogs. You'll see a lot of people speak in absolutes saying, always do this, never do this. And what we're here to say is that that's not always the case, but we also don't want to commit the opposite side of mistaking in terms of educational content and just say it always depends, even though it often does. We're trying to find a middle ground here where we're going to say, Yes, it pretty much always depends, but we're going to provide some helpful kind of benchmarks, baseline ideas, tell you things to be considering so that you can know maybe in your case, there is something that should always or never be the case, but that would not be the same for every single brand because every single brand is different. Every single category is different. Every single product is different. They're in different stages of growth. All of these things to be considered. And like Andrew was saying, just on the science side of things, we're not going to talk too much about that on today's episode because we've covered a lot of it in depth. So if you want to learn more about how we calculate bids, which is very mathematical, formulaic, check out episode 34 of That Amazon Ads Podcast on the RPC bidding method. Talk about how to calculate your placement adjustments. This is something that is very mathematical that unfortunately too many people just drop the math when it comes to adjusting for placements. Watch episode 44 on that one. Day parting is also very mathematical and what those day parting adjustments should be. We have a new video that just dropped. It's not an episode number, but just search our channel for easy guide to day parting. You'll find it. And these are all the things that software can do. So, when you're looking at a tool like AdLabs, we consider AdLabs to just be a big fancy calculator with very sophisticated math and logic that can run these calculations However, the inputs to the calculator is art. Those inputs are date range selection. What should my max increase limits be? How aggressive do I want to be increasing or decreasing? Do I want to be more focused on increases or decreases? Or what should my target ACoS be is a huge variable as well that for us is constantly dynamic. So with that, Andrew, let's dive into these topics talking about Amazon PPC as an art. Speaker 2: First things first, campaign structure. This is something that people want to be a science and want it to be a fixed answer. Whenever people ask, what campaign structure should you have? They want it to be the same answer every time, but there's so much nuance in the accounts and even the accounts that I work on that sometimes it makes sense to do single product ad groups. Sometimes it's better to have single product campaigns, single keyword campaigns, And it all just really depends, but this is something that is an art and does require some nuance. So for discerning what your campaign structure should be, we have to consider a lot of things like how many products are in the catalog? How many different variations are you working with? And in a lot of cases, those accounts that I'm working on that have massive catalogs, 10,000 products, I'm thinking like car parts and apparel and things like that, It may not make sense to try to segment all of your products down into single product campaigns. You should probably opt for a slightly more aggregated structure using single product ad groups. But on the flip side, if you just have a couple of products or just a handful of products, it might make more sense to have further granularity within your campaign structure using single product campaigns. And giving yourself the controls to really dial in that performance on specific products. Now, single keyword campaigns is a whole other conversation. It's more of whether or not you need to use them, whether you don't, how many to actually have, do you need to have all of your keywords segmented out into single keyword campaigns, or can you kind of aggregate some of the stuff that's lower volume and just focus on things that are high volume, which is generally what we recommend for that piece of things, is just isolating and pulling out your top VIP, highest search volume, most competitive keywords, because that's really where you're gonna see the value. And a lot of times people try to over-segment, thinking that it's gonna add more control, but a lot of times just adds increased complication. Speaker 1: Yeah, absolutely. And that's the question that people ask all the time. They just say, hey, what campaign structure should I use? And that's the end of the question. It's like, well, again, it depends. If you wanted me to just pick a structure out of my hat, I would say single product campaigns. That's probably gonna be best for most people, but I wouldn't say always do single product campaigns or never do single product campaigns. So all of that requires nuance based on, and listen to our episode on campaign structure, that one will dive more into that. But it really just depends on the kind of volume you have for each keyword and the size of your catalog and how much volume each product in your catalog gets. Going on to the next. Speaker 2: Real quick. It doesn't have to be fixed either. Within one account, you can use multiple different structures for different groups of products and different objectives. Don't get into this mindset that I only use single product ad groups for this account. You can use a little flavor of all of them to accomplish your goals. That's really what we're trying to say. That's the art, is knowing what to use and when. Speaker 1: Yeah, I usually do single product campaigns as the default for non-brand keywords. For my brand defense campaign, I just consolidate it to one brand defense campaign and do single product ad groups. And then single keyword campaigns is reserved for like my top 10 or 20 keywords and only my top one or two ASINs for what it's worth. That would be good for an average brand that's spending $30,000 to $50,000 a month or up and has a catalog size of around 50, well, I'll say from 10, 20 products and up. Okay, how much to increase or decrease? This is another huge item. So when you are watching that episode on either the first like three, four episodes of our podcast where we talk about bidding or diving into that RPC episode number 34, There may be times where you calculate what the bid should be and it brings the bid from currently being $1 to $3 or it could be vice versa. Maybe the bid was currently $3 and the new bid calculation is $1. Does that mean that you should jump there immediately or should you step your way there in increments going 10%, 20% increments at a time, 25%, 50%? All of that is really going to be an art in terms of how quickly are you trying to grow sales or reduce ACoS. And as a general idea, the larger the changes that you're making, the higher the potential risk and volatility. And so depending on how, there's certainly desperate times, desperate measures where I've had accounts where like the last week something went crazy. And so we go in there and we find some bids that just for whatever reason, or some keywords that for whatever reason, you know, performance tanked and those bids need to drop by like 75, 80%. And we do it. Well, I wouldn't want to do that across all the keywords in the campaign. So also like how many keywords are you adjusting with those things? So like generally speaking, like, The more keywords that are being optimized, the tighter you want those limits to be. You don't want to be taking, let's just say you have a campaign, sorry, an account with 10,000 keywords. And if you're planning on optimizing all 10,000 keywords, you probably want some tighter restrictions on the max increase decrease limits so that you don't create too much volatility. Now, if you're just optimizing one or two problematic keywords, you can open those up. And rather than just limiting the max increase decrease to five, 10%, you could open that up to say minus 75% or up 50%, whatever. The other thing is sometimes rather than just saying max increase decrease 25%, if you're trying to be more growth oriented, you could say max increase 25%, max decrease 10%. And now you're tilted with a little bit more of like a growth bias, or if you're trying to be more conservative, you invert that. So max decrease 25%, max increase 10% to still push a little bit where there's opportunity, but more so focusing on pulling back spend where things are inefficient. So anything to add there, Andrew? Speaker 2: I think that's really well said. I don't really have a whole lot to add. I'll just echo what Stephen said. That was really well said. But another question that I often get is, What date range should I use? We'll be doing demos of AdLabs and this is a very common question. They see how dynamic our date range selection can be and that makes people ask which range should I use? And they want a solid answer that's just like, I always do 30 days or I always do 60 days or whatever. And a lot of softwares, that is what you do. It is setting those fixed date ranges and they don't change that much. And so people are looking for that solidity, but the whole art of this is having that flexibility. So we can discuss this a little bit. Generally speaking, when it comes to what date range to use, a lot of times whenever you're looking to make larger changes, put through a lot more optimizations, you're going to use longer timeframes because you want to have higher data confidence in all of the inputs that are going through the calculator that are determining what your bid changes and setting changes should be. You want to have A good amount of confidence in all the metrics, whereas on shorter timeframes, you might have a little bit of a skewed perspective of things and are usually set aside for smaller changes where you're just putting through a smaller number of keyword changes. And usually I will see those smaller changes like after I've already pushed through some other bid changes. So I'll put through some changes on Monday and then come back later in the week and I might see that you know certain keywords or campaigns are spiking. Their ACoS is going up unintentionally and in those cases I just kind of want to isolate those changes to where the performance really is not good or where it's really shifted and changed. So I might look at just like the last five days and put through some reductions on anything that was overpacing my goals for that smaller time frame. And you're going to really isolate and adjust the things that need changed in where things aren't really performing that well. Speaker 1: Just so people can know how I think through this, kind of going back to the it depends, On the date range thing, but generally speaking, I usually zoom out 90 days in my campaign manager or an ad labs, whatever view I'm looking at. Zoom out 90 days, go to a weekly view, look at the conversion rate trends. That's going to be my first indicator just to see are things over time trending up. I usually chart ACoS and conversion rate. I think we also did an episode on what should my date range be. A little bit of a recap of that, but also adding on new thoughts. From that episode, we say, zoom out, look for the trends. Things are staying pretty stable, then it's okay to use a longer timeframe. If you're seeing a big trend change in the last like 7, 14, 30 days, you want to shorten it down because all of the calculations that you're running on bids, whether you're doing it through a rule-based system or on a spreadsheet, whatever, all of your calculations are usually going to be based on the keywords performance for that look-back period. So it's imperative that you pick the right look-back period that's capitalizing. You want to pick the date range that most accurately reflects the performance for the next week or two weeks. So obviously, I would not want to pick a date range for the last four to eight weeks on January 1st, because the last four to eight weeks is including Black Friday, Cyber Monday, all of the holidays, shopping through the end of the year. That's just not accurate conversion rate performance for what we're anticipating. So there are times where you want those shorter date ranges, times where you want longer date ranges. And also, we did an episode on why rule-based automations don't work, so we kind of touched on this a little bit there. But when you're just using a fixed 30-day look-back window, if there's a problematic campaign or keyword that went crazy for whatever reason in the last seven days, On a 30-day timeframe, that bid might look okay. But the last week, you lost money. So your account that was doing well for the last seven days, you've been burning through cash. And there's a ton of stuff that you can see clearly went wrong in the last seven days. Maybe you had bids that were at $3 and you were only ever getting a $1 CPC just because no one was really bidding that high. But now within the last week, suddenly, Your CPCs are $3 and you can't afford that and we need to react to that. But any other rule-based system that's looking on a longer timeframe, it's going to be way too slow to react to emergency scenarios or abnormalities. What's the word I'm looking for? Speaker 2: Abnormalities. Speaker 1: Abnormal anomalies. Speaker 2: Anomalies. Speaker 1: Yeah, abnormalities. You need shorter timeframes to react to anomalies. So when you just have a bunch of rules and best practices and SOPs and automations and everything that's just fixed and you're trying to be as scientific as possible, and I applaud you for that, but you are completely missing the artistry involved in PPC, which is knowing when to react and adapt to real-time trends as you see them unfolding before your eyes. So if you see that yesterday, there was a campaign that spent $2,000 at a 200% ACoS, Something's wrong when the target ACoS was 30% and you can optimize that campaign based on the last two, three days of data. So there are times where you might just pick a date range that's tiny, tiny, tiny. But when you go with those shorter timeframes, you want to make sure because you have just in general fewer clicks, less data confidence, you want to be optimizing fewer campaigns and fewer keywords. So when I am using shorter timeframes, if I have an account with let's say 200, 300 active campaigns that are all spending, When I'm going seven days and less, I'm usually only optimizing five campaigns. I'm like, what are like the five campaigns that the ACoS was way too high, spend volume was high. I'll pick those campaigns and most of the time what you're going to find in any one of those campaigns is just one or two keywords in those campaigns that was problematic. So you have one or two problematic keywords in a campaign that it drove up like 80, 90% of the spend and you only need to adjust bids on like five to 10 keywords. So it's totally fine to use a very short date range. So people would say never use less than seven days. I would say I frequently use less than seven days to react to an anomaly. But for the most part, if I'm going to be doing And also in those anomalies, I'm increasing my max decrease limits to make sure that like maybe those bids need to drop by 50, 75% to really make sure we accomplish what we're trying to do. We'll just stop the bleeding until we have time to dig into the search terms and see what else might have gone wrong there. But then if I'm going to be doing a longer kind of more routine maintenance, optimizing all of my campaigns combined, I'm definitely going to want to use a longer date range to select all my campaigns and use tighter limits on how much the bids are increasing and decreasing. And the same applies also to our placement settings. If you're optimizing those placement settings, I'm never going to optimize placements on a very short date range, just because you really need to have a lot of data confidence for those placements. So 30 days minimum, I would say as a rule of thumb, again, it always depends, but for general, a normal account, I would say 30 days minimum is what you need to have really good calculations for your placement settings. And so you can do like once a month, every other month, And we're here to help you optimize everything on 30, 60 days, start dialing in those campaign placements, and then to react to smaller things, you would maybe only want to adjust the bids on a few keywords. You're not going to be touching the placement settings in those scenarios. You're just trying to get those bids either increase or decrease to hit those goals. Speaker 2: Yeah, that's a good point on the placements too, like having a lot more data confidence. The performance on placements, we typically don't see that as being a really volatile change in performance across placements. So in those cases, the adjustments can be a lot less frequent and you can start using those longer timeframes to really inform what those should be because a lot of times the performance stays relatively consistent. So that's a great, great point. Speaker 1: Another question I love getting, Andrew, is, what should my target ACoS be? With zero context. Leave a message, hey Stephen, what should my target ACoS be? Speaker 2: Yeah, no idea what you even sell. But yeah, this is a good starting point. I usually say that your target ACoS should be break-even if you need to. So that's kind of like the blanket statement general rule that I abide by for what the target ACoS should be. But there's a lot of nuance beneath the surface of that. How new is this product? Is it a brand new product or has it been relatively established with a lot of reviews? In the case of having a lot longer history, this product probably converts a lot better. Whereas if you have a brand new product, you're likely going to need to push those margins a little bit more than you typically would because It's not established, you're not ranking well, there's not a lot of sales history and reviews and a lot of history behind that product. And so there's cases where you need to have a higher target ACoS than your breakeven like in launches. And then there are times to be a little more conservative or try to optimize. And I say target your breakeven ACoS if you need to, because a lot of times you'll find that you can still get visibility and you can still perform quite well below that breakeven, but it's a good starting point for just getting new campaigns going. You can target your breakeven because we're basically saying, if we hit this, we're going to be profitable because we're relying on not just a PPC sale, but for every one PPC sale, we're hopefully getting one or two organic sales as well. And so it balances out to a solid profit margin for you. That's generally what I look at. Now, there's also situations where not every single keyword has the same target ACoS. There's going to be keywords that are a lot higher volume, have a lot more competition, CPCs are higher, and in order for you to actually gain visibility and see growth on those terms, you're going to need to target a higher ACoS. You're going to need to have higher bids and go after higher CPCs. There are certain keywords where you can get by with a break-even target ACoS or even lower, but there's a lot of keywords where they're a lot more competitive and you have to be able to tailor those adjustments and set the target ACoS according to that level of aggression that's really needed in your bid settings and all of that. Speaker 1: All right. Sorry, guys. Having some weird camera Wi-Fi issues. So my camera changed, but we did not. We are still here. Speaker 2: You look good from this angle too. Speaker 1: Is it better? Okay. It's just my laptop. It's just my laptop. So on that topic, though, for Target ACoS, just one quick example. I was just speaking with a large supplement brand last week, and this brand was spending over $50,000, maybe even I think around $50,000 a month on ads. They were getting about a 50% ACoS. And a 15% tacos with about a 30% ad sales to total sales ratio, which is actually very strong for a supplement brand. When you see an ad sales percentage that low, only 30%, to me that's an indicator that you could definitely push a lot higher on average on Amazon, around 50% of sales are coming from ads. But for this guy spending already 50K a month on ads and seeing that like over two thirds of his ads are coming from organic, Indicates a super high return rate in terms of repeat purchasers. So that's monumental, which means long LTV, which means he was telling me that his breakeven ACoS is 40% and he was trying to reduce his ACoS from 50, it was like 50%, sometimes 60%. He was trying to reduce it down to 40%. And trying to lower his ACoS and I told him you should be doing the opposite because you're not trying to this is a supplement. We can clearly see from the data just from within like, I mean, obviously you could do more analysis on it, but within my 30 second overview of looking at his data, I was like you have high repeat purchasers. And that means one new customer acquisition could result in three to four additional sales down the road, which means your target ACoS should really be two to three X above break even, because let's just say your ACoS is seven days sales attribution if it's a sponsored product ad on Seller Central. 14 days for vendors and sponsored brands, stuff like that. If someone's buying a second product on the third week or the fourth week after buying the first one, you will never see that data in the ads. It's only going to come through on the organic side. So you absolutely want to be capitalizing on that, factor that in. So you have to move your break even higher. So that's just one example of how to think through a target ACoS or as Andrew was saying, Maybe you can't run that breakeven like that high of a target ACoS across all your products, but there might be a few keywords that are very competitive because what you'll end up finding is if you're always trying to breakeven or always trying to be profitable on your target ACoS, When you run the numbers and run the math of what does that equate to on a CPC level for what you can afford to get that target ACoS, you're going to end up realizing that you're not competitive enough to keep up with your peers, the other competitors who are bidding in this auction. It's an auction. You've got to be competitive. You've got to increase your bids. The question is, how much should you increase your bids by? The answer to that is, well, how much can you afford as it relates to your ACoS and your margins and all these things? And so hopefully that proves the point that the target ACoS should be dynamic. The other thing for me is usually with advertising, your target ACoS is going to be within a range. So if you're normally trying to hit like a 30% target ACoS, there may be times where you have to come, maybe you have a 30% target ACoS goal and a 15% target tacos goal. Well, depending on how the organic is doing, that tacos is gonna raise and lower a little bit. And your target ACoS on the advertising side needs to be a little bit dynamic. So you can look at like the ACoS to tacos ratio to kind of figure out based on what tacos is doing, what should my target ACoS be doing? And you're not always going for 38% or 30%. Sometimes you're going down to 28%. Other times you're going up to 32, 33%. All of that is kind of, you gotta ride the waves. As they come and go. Speaker 2: Yeah, that's a good point too. And sometimes whenever you're just running some bid optimizations, bid calculations, sometimes you want to give yourself like a little buffer between your target and what types of changes you're trying to make. So maybe if your target is 30% and you're looking to make some reductions, you don't want to necessarily change things that are between 30 and 40%. Maybe you're just trying to pull the stuff down that's over 40%. So setting a 40% target ACoS would just kind of clean up those things that are way over your target. And then on the inverse of that is when you're running bid increases, sometimes you can set a lower target ACoS, which is basically just going to increase bids on everything that's well below your target. So if you've got a 30% target ACoS, You know, targeting a 20% and running bid increases on those things that are below 20%. You know, you've got quite a bit of wiggle room between where those targets are currently at and where your actual target is. So that way you can with confidence push through adjustments that are actually pushing spend on things that have that additional room to spend more. And yes, they'll be within your overall target. Speaker 1: All right, last. Topic. Interpreting data. This is very much an art. Interpreting data and really critically thinking through data and troubleshooting and performance issues. This is worth a whole separate episode on its own. We actually do have a whole lesson on this in the masterclass on critically thinking through data, interpreting metrics, storytelling through metrics. So if you're interested in that, check the description below where we also have a link to the masterclass. And that is just basically a very condensed version of Amazon PPC education. But Andrew, what Give me a bad example of someone's reporting or what they're doing with the data and then we'll talk about a good example. Speaker 2: Yeah, bad example I see all the time with ad managers is just They'll have a dashboard built and they'll be like, well, last week we spent this much and that was 10% more than the previous week. And our ACoS was 20% and that was a little bit less than it was the previous week. And they just read off the data. They just read the data and they're not explaining the reasoning behind it. So it's just like they're missing a critical component where You're actually saying, okay, our spend increased because X, Y, Z. We did this, this, and that. We adjusted bids here. We're trying to be more aggressive on X, Y, Z keyword and really kind of going a layer or two deeper into interpreting what the change in the performance and the change in the metric actually means and what types of adjustments were actually made to elicit that change. Speaker 1: A hundred percent. Yeah. I was just quickly Googling like interpretive dance to see if there was anything I could pull in here, but nothing's relevant. Reading the metrics is not okay. Either because someone's paying you to manage their ads and you need to be doing a lot better job of telling them, why the metrics are changing as they're changing, or you are a brand owner and you need to be doing a much better job of understanding your business. So when you see that sales are down, Where did that come from? There's a whole list of troubleshooting steps, which again, is in the masterclass. We can't explain it all right now because that topic alone is like 30, 40 minutes and this episode's already on 30, 40 minutes. If you would like us to drop some of those lessons, we can maybe put some of them for free on YouTube. Just comment masterclass and if we get enough people commenting, we can put up a few of those videos. It's like four or five different lessons around these types of topics. But sales drop, for example. The question is, where did that sales drop come from? There's a whole list of troubleshooting steps you got to go through. Was it because you reduced bids and therefore you lost some visibility? Was it because you lost ranking? Was it because your products, sometimes you just have products that went out of stock or the prices changed? Was it because did the conversion rates change? Did the conversion rates decrease and that's why sales are down? Or was it the traffic that decreased? It's usually gonna be one of those two things, either traffic dropped or conversion rate dropped. If traffic dropped, why did the traffic drop? Is it because campaigns ran out of budget? Is it because you reduced bids, like I said? Or is it just the search volumes dropped? You can check out the Search Query Performance Report episode to find out how to track those search volume trends. How do conversion rates trend? If conversion rates trended down, why did they trend down? Was it an issue with the listing? Was it a switch of the keyword mix? Sometimes just like the types of keywords or search terms that were coming through, you just happen to get more traffic on keywords or search terms with lower purchase intent. They're either higher up the funnel, not quite as relevant, more just like broad categorical terms and not bottom of funnel, long tail keywords that are typically driving the volume. And then what do you do about that? How are you going to get those sales back? Is it something that you can do? Is it as simple as just some bid optimizations? Do you need more keyword harvesting? Do you need to now build out single keyword campaigns? Because these keywords that were driving most of the volume are now having problems getting visibility because they're in a campaign together with 20 other keywords that are all sharing the placement settings and it would be better to just have more accurate placement settings for this one keyword or maybe you need to switch out your products and put your best foot forward. All of this is art. There's so many things to think through and that's probably actually where most of, I think, Andrew and I spend our time as PPC managers is really on that step. Like bid optimizations, all that kind of stuff, we can fly through that in a couple of minutes and be done with it. But when it comes to actually analyzing your data, thinking through it, troubleshooting it, and then figuring out as a result of just spending 30 minutes digging through the weeds and finding out what went wrong, you're spending another 20, 30 minutes creating a strategy around that and implementing that strategy. Lots of things, lots of things there. Did I miss anything, Andrew? Speaker 2: No, I mean, I think that's pretty well said. Just really paying attention to all the different factors that can play into the changing of your metrics and the changing of your data. There's a lot that we could talk about there and just understanding, you know, that there's outside factors that can influence what you're seeing in console and within your data, you know, macro changes. There's a lot of talk on tariffs right now, like that's going to have a big impact on A lot of sellers and understanding and factoring that into your decision-making tree and your analysis is going to be important. Understanding the dynamics within individual niches like you talked about having search volume changes, things like that. Knowing the depth of your niche and what's changing as well as what competitors are doing because that can have a really big impact on performance that you're getting as well. Competitors are decreasing their prices or increasing their prices or running deals, things like that. That can all affect how your products do and it's got to be considered in the analysis so that way you can kind of craft a strategy around What to do about it. Once you know what's going on, why it's going on, the next step is really figuring out what do we do now and putting together that formula for attacking those problems and adjusting and adapting to what the market's telling you. Speaker 1: Absolutely. So I hope you guys made it to the end of this episode. I think that the last section that we said here, we should have said at the beginning, but Because I think that was very important. If you made it to the end, congratulations, because you heard some of the most valuable stuff about the artistry in Amazon PPC management. Too many people are trying to turn all of PPC into only a pure science. And they're leaving a lot of money on the table if they're doing that. You can't automate everything. You can't automate thinking. Because the PPC data itself is siloed. It's not taking the big picture, the full picture into account. And you, the PPC manager, are. You are the one who at the end of the day is sitting in on these meetings with your team and with clients and with your boss, whoever, and understanding a lot more information about the business and what the business needs. And these other tools aren't doing that. So that's why you really need something that, you really need a tool that can only handle the science, the truly scientific things, just like calculating what bid should be. But you're always tweaking those inputs, changing those date ranges, changing that target ACoS, understanding when it's time to push, when it's time to pull back on spend a little bit. All of those things are dynamic. I hope this episode was shedding a little bit more light on how to think through those topics so that you can really take full control of your PPC and get the performance that you want. So if we missed anything on this episode, please drop comments below. Let us know what we didn't cover, what you still have questions on, or jump into our Discord. And let us know there. Andrew, final thoughts? Speaker 2: Leave us some suggestions on what kind of content you want to hear too. Those are super helpful for us in picking topics and stuff. We've covered a lot. We've been doing this for almost two years every single week. So we've hit a lot of the core topics. But if there's anything that we're missing, definitely let us know in the comments and make sure you like and subscribe. We love and appreciate that support. And we'll see you next week on That Amazon Ads Podcast. Speaker 1: Peace.