The Exact "Revenue Impact Formula" to Prioritize Your Amazon SKUs [The PPC Den Podcast]

Most Amazon sellers are drowning in SKUs and using AI to go faster without knowing where to actually go. Mike Danford, Chief Strategy Officer at Adverio, has a fix for that.

In this episode of The PPC Den, Mike breaks down the Revenue Impact Formula, a scoring system Adverio uses to rank and prioritize product listings across catalogs with hundreds to thousands of SKUs. The framework separates the spray-and-pray work (getting every listing up to table stakes: images, title characters, pricing hygiene) from the surgical stuff (conversion funnel analysis, Rufus optimization, return badge fixes, parenting strategy). The goal is simple: attach a dollar amount to every optimization so you know what to do first, not just what to do.

If your team is busy but not moving the needle, this one is worth your time.

🦡 Highlights ​​ 

00:00 – Welcome 

02:40 – What is the Revenue Impact Formula?

05:47 – Why AI is Creating More “Busy Work”

09:20 – Optimizing for Amazon’s AI (How Rufus Thinks)

12:43 – Building Your Product Prioritization Spreadsheet

15:30 – The “Spray and Pray” Approach (Quick Wins)

20:35 – The Surgical Approach (Deep Listing Optimization)

24:54 – Case Study: Removing the “Frequently Returned” Badge

28:59 – Calculating Market Share & Potential Lift

33:13 – Outro

Host: Welcome back to the show. Mr. Mike Danford, chief strategy officer of Advaro. Born in 2014 is when Advaro was born. We’ve had some banger episodes, Mike, over the years. In case anyone’s unfamiliar with your work here on the show, I think one of the best episodes on placement testing and placement optimization we did together in January 2025. So, it’s been a while since you’ve been back on the show and got into deep placement testing. So, we got nitty-gritty stuff. We also looked at seven overlooked Amazon seller central tools. That was an amazing episode, too. Getting more out of your seller central account. And we had an amazing episode on branded spend. Today, we’re going to continue that trend. And you brought something very interesting along today, revenue impact formula. And I can’t wait to dig into it. But for now, welcome back to the Badger Den. How are you doing?

Mike: I am great. Excited. Thanks so much for having me.

Host: Tell me about some of these products behind you.

Mike: Yeah, so some of the brands we work with, um, we call it the profit perspective corner. Uh, each one has kind of a unique strategy and we kind of go through it. Um, kind of the things that we go where you can do, uh, skew replication, you can do unique packaging or all kinds of things and just kind of helping brands. We love creative brands, brands that have fun with their products and bring a little joy to the day. Um, so yeah, a lot of concepts here that I reference.

Host: I have to ask about this one. What is full of sheet?

Mike: Oh, so that’s from Shinasty. Um, and that is a dryer sheet or dry detergent sheets.

Host: Ah,

Mike: so instead of a bottle, it’s a little sheet you drop in. Um, and they they have a ton of, you know, play on words with their expressions and their apparel and whatnot. So, um, that’s f and that is a phenomenal product by the way.

Host: Amazing. Very cool. The Prophet Corner.

Mike: Prophet Perspective. Yes.

Host: Prophet Perspective.

Mike: Yes. Our newsletter of sorts.

Host: Ah, amazing. The Because the Prophet Corner seems like something that you go to each morning and light a candle and ask the the the heavens above for more profit.

Mike: Well, we have candles here if you want to do that.

Host: Yes, you could do it. Yes, that’s why that’s why I mentioned it. Fantastic. Um, so when people come on the show, I always like to ask them like what’s up for you? like what’s something that’s been really helpful for you? That way all the good listeners out there of Badger Nation listening out there and all the corners of the Badger Den world how to better navigate the ever expanding complexities of Amazon and pretty much right away you came up you’re like revenue impact formula. So there’s so many numbers and so many metrics and so many corners of Amazon that it’s helpful sometimes to develop these internal formulas to categorize, prioritize, get perspective, wrap your head around it the whole situation. So tell me a little bit more about why this came up for you. What is your revenue impact formula?

Mike: Yeah, so this came up. We work with very large uh skew count cataloges. I think the average is somewhere between 100 and 500 like main SKUs and then off of that you can have thousands of variations from size, color, scents, you know, bundling packages, all kinds of stuff. all the different attributes you can stack. And when a brand comes to us, they’re, you know, hey, this works on our DTOC or this works on Walmart or Target or Amazon or vice versa or, you know, how do we know which ones to keep in stock or which ones to keep, kill, optimize? How do we know what to work on first? How do we know what the current status of 6,000 products is? So, let’s level set first. Um, and then what do we do first? Because you can’t work on all 6,000 SKs at the same time. not for a reasonable cost. Um, nor can you, you know, keep full stock for 6,000 plus SKUs at all times, especially

Host: nor would it make sense to dedicate the same amount of time towards every skew.

Mike: That’s that’s the key part.

Host: Yeah.

Mike: How do you how do you prioritize and you obviously can’t dedicate everything and then AI has made it where you can do more. Um, so now really leaning to the puro. Okay, here’s your here’s your priority skewers, your group. Can we do some Can we sling some stuff at the wall over here at the same time for low value, low intent and see if more of those just kind of pop up with low effort. It’s a really cool way for us to kind of uh break that apart. You know, uh AI has been really tricky for people because you can do a lot more stuff. So like just in general, the world is very focused on productivity like how to do something faster, how to do uh something more, you know, efficiently. But it is much it’s easy to do that, right? Oh, you want to write an email faster? Just ask Chat GBT to do it. Boom, you have an email. But like to be effective, to actually enact change that actually has an ROI is a very different thing. And that’s where I think a lot of people get lost because like you can work at this rapid pace now. And if you’re not prioritized on like what is the actual lever that will actually change revenue, change profits, it’s very easy to get lost. So if nothing else, I I that’s a lesson that I keep relearning. I think everyone continues to like relearn that lesson, especially in this faster paced world where it’s just like, oh, I can do everything hyper fast, but what should I actually be doing to improve improve the bottom line? It’s a very different question.

Host: Yeah. If you are natively and historically doing busy work and you pull AI in, you just end up doing more busy work unless you have this this directionality and intentionality behind your prioritization on what to do and measure the impact.

Mike: Yeah.

Host: Did it actually work?

Mike: Yeah. Yeah. I may have used AI and it may have wrote a more beautiful email, but I spent the same amount of time, the same mental juice to it when I could have just wrote itself. So I’ve actually yeah for all for my certain sets of messages I post now I do it I don’t even pull AI I still want to be able to do it. It’s just it allows me to get more return on that and be connected and then obviously it’s more authentic as well and I make sure I can do that. So it’s like this balance that we go through because I realized I was just managing prompts instead of actually writing the actual right update. I I find that all the time where it’s just like, okay, a I could write this email and I could send it and like this is fine, but like I think I could like write something a little bit more like direct and like sound like it’s not even like sounds like me or doesn’t sound like me. Just like is this an effective email? And it’s like it’s very easy to be ineffective and just be doing a whole bunch of stuff. Um, so when it comes to Amazon, I see this all the time where, you know, there’s this sort of pressure to do everything all the time, right now, non-stop, every nook and cranny of everywhere. And it’s it’s actually like the most successful people I know are really good at prioritization. So, anything that any conversation we can have about how to prioritize is a conversation I think every Amazon marketer needs to hear. So, let’s walk through this.

Host: Absolutely. Look forward to it. So at the at the top level again, how do we level set and have a rubric or an objective way to score each product, group of products, platforms, whatever data we’re pulling in. And then um break down here’s where you are, here’s where you could be from a scoring perspective. Um and then we take and we build in traffic, whether that’s existing or not. Um and then from there, it’s like what’s the potential lift from taking you from a 6.0 0 to a 9.0 and the score is on a relative of t. Um and then that’s how you know it. So you roll it up and you get a dollar amount attached to that and you’re like hey if you do this generally speaking this is your return um in terms of dollars or percentage lift if there’s no base to that and then this helps you prioritize it every single time because you the optimization cycle is okay I’ve got a top seller it’s already a 9.9. Do I do I just go full in try to get a perfect 10? Well, that’s a lot of effort. You got a lot of things you’re doing on there. Is that worth the juice? When I have 700 other SKUs that I can focus on and I can do a burrito analysis of that and say, “Man, I just need to put one extra image. This image works. Why don’t I put this infographic across all other 700 products? What happens then you roll that up?”

Mike: So, it’s just it’s just it’s amazing. It’s fun to see um you know, and it’s like what do I do next? When I when I come in, what do I do next? And our team even internally is like when they mentally the the fatigue and the pressure if you will on performance is when we have an effective way to tell them what to do next they can do more.

Host: Yeah.

Mike: And then they can do the part where it’s gray and a little obscure and you kind of like have to think on your feet where it’s not 100% always objective. There’s a little subjectivity into it.

Host: Yeah. And then they and that’s where they can shine and pull their value in as you as opposed to using their juices for something that’s like well it needs just be a rect an objective formula right out of the gate. Um you know what’s coming up for me and like tell me if I’m uh if I’m thinking about this uh in the right way like one thing that’s coming up for me is like there’s all these like analyze your Amazon product page and it’s like like Helium 10 has one. and it’ll score your product page based on like do you have enough images? Did you use enough characters in your description? Do you have this piece of thing? Do you have this? So like it it does a sort of like uh mechanical score of like do you have enough images? And then imagine if you had a list of every one of your products and it was like pass fail, do you have enough images? it’s like well where do I focus on? And then like so you have that element then you multiply it by like traffic potential or like market uh potential like so then you like start tacking on who’s going to have the best lift where’s the next best lift instead of optimizing a product page that doesn’t get any traffic like even if it improves 100% it’s still not going to move the needle that much.

Mike: Yeah. For us, that’s the listing quality score is the the main thing. And we have offer score, media score, content score, and there’s like two or three others that roll up into that. And that’s purely objective. Can be a binary yes, no. It could be character limit inside the the limit or whatever it may be. And then there’s a subjective layer on top of that, an intent layer on top of that as well. And then we have another set which is agent add to cart rating. And that is a readiness. And that is a whole another set of scores. And it’s like, hey, LQS is what the human is looking at. They can actually see and and and and know the flow and look at the images and the copy and does it speak to what they see on the screen. And agent add toart is what Rufus is looking at, which is a lot of the same things. quality images, make sure the copy is right, offers there. But it can also, the Rufus pulls in your inventory um history, your pricing history, your return rates, all these other things that a shopper is not going to be able to see on the front end. So now you you pull that backend information, you put it in because one of the biggest things that we understand for Rufus to Alexa, hey Alexa, order me a candle. Okay. Well, it’s going to do it based on your persona, your profile, your history, and what it thinks based on your historical things. And if it orders the candle that matches exactly, like, man, I have to tell it I wanted this pet house candle citrus. And you order it, and it’s like, boom, and it’s subscribe and save. Boom, boom, boom. Now, Alexa and the feedback circle with with with Rufus to the user is like, man, it gets me, so I want to order something again. Well, if it goes in and orders a candle that matches you, it’s it’s the scent and it’s good price point. It knows you if you want premium or or not, pricing products, etc., but the product is commonly out of order. So, you have to re say, “Purchase me a new candle.” That reliability, that consistency goes away and the user blames that on Roffus and Alexa. That’s the feedback loop that we’re seeing. So, we pull all that in as well.

Host: Yeah, absolutely. That’s a lot. Sorry, but No, no, no. That’s perfect. So uh and then how do you organize this generally? I just want to like visualize it for people. So uh I take it this is a spreadsheet of sorts with like each column being some kind of score for different categories.

Mike: Yeah. So we get someone to build this. Yeah. When you pull it in, we’ve got a scoring system that goes through 180 some checkpoints in the actual listing. Uh like if you were to literally look at it in some of the backend stuff. Yeah. Um, and then there’s a subjective layer on top of that where it’s scanning your images for intent, looking at your personas, making sure you’re addressing that, and then it’s pulling all of your history through buy box percentage, pricing, deltas, coupons, historical return rates, and it’s also doing it against your competitors, your cluster of competitors as well. And then eventually, so if I were to sit down and build this myself, that that’s sort of how I’m visualizing. I would get started. I would have a spreadsheet and then I would think of the different columns that I would put there. Things like uh you know do I have enough images or like you all you mentioned like the human readable stuff like does the image have a lifestyle picture? Does it have a you know high-res like does it have all the different characteristics of what a good image should be an action shot? you know, product and use, uh, lifestyle, like all these different kinds of things like, and then it would eventually earn points and earn for each element. And then I love that you mentioned all of those not so apparent stuff like shipping time and, you know, buy box percentage and um, all of that kind of stuff I find really useful, too, like return rate, like there’s a million in one data points. So you populate that and then ultimately you get some kind of you know score rolled up and tell what about like you have all that and then also I figured you’d want to also enact like ease like how which which thing will be most easy to implement versus time like how long is each thing going to take because you mentioned something interesting which is like what if we add an infographic to 700 products you know that’s relevant for 700 products Um, like that’s pretty cool. So, like when you have so much data, even still, how do you get to the point where you’re able to like zoom in on the biggest priority? Is it always the one that just like already has the most clicks, like already has the most profit? Because it’s easier to, you know, take something from a six to an eight to a 10 as opposed to like zero to one. Yeah, it’s a great question. And uh you know going from an eight to a 10 is a lot harder than a six to an eight.

Mike: It’s a great part. So we do have that in the back end as well as what our our lift is from our our efforts. Um our time cost quality speed as well. Um can we, you know, do it at scale? Can we do a spray and prey first? We know this generally works. Let’s just it’s one image blasted on seven. It’s going to hurt some listings. It’s going to probably not change some listings and it’s going to crush other listings. and that surfaces those up.

Host: Can I pause you right there? So, I actually wanted to get some specific examples and you sort of mentioned one. So, I’ve seen like big cataloges before and I like that you called it Spray and Prey because it like one example, a specific example would be every product title that is low on characters. It’s like wasted opportunity. It’s like why aren’t we utilizing all the characters that we have available?

Mike: Mhm.

Host: So that’s like, okay, somebody go through and like make sure every product title has the right amount of characters or like amount of images or add an extra infographic. Those are like three examples of just like let’s get everything like I would call that like low cerebral work.

Mike: Yeah.

Host: Because it’s like you either have enough characters in your title or you don’t. You either have all the images or you don’t. So that kind of work is I like that as like a you know first takeaway here where it’s like when you organize this you’re able to see all this and it’s like spray and pray like get everything up to this watermark. Get everything table stakes.

Mike: Yep. Yep.

Host: Start there.

Mike: You got you have a 100 listings that have two images. Well, okay. That’s very clear. Let’s put some brand images in there. Let’s put cross-selling images. Let’s put just fill it up with something that’s of value. And then you go through and iterate from there. and we have, you know, a catalog that has 70,000 SKUs in in one one marketplace and we come up with formulas specifically for a title. So, we can scrape all of your listings uh your one listing per like one design or whatever per parent, if you will. Got it. We have all your Cosmo and Roffus. So, you got your 15 things in the back end, the Cosmo, and then whatever up to three to seven or so Cosmo questions that we can scrape um and pull in. And it’s literally take these answers and put them in these bullets, this title, and just just answer it. Boom. Do it. And you’ll see your visibility take off instantly on those products without even putting advertising dollars on it. Let’s just see if you can get organic visibility. And as those come up, hey, here’s a whole another cohort that’s, you know, moved from your D tier to your C tier. Let’s put 20, 30 bucks a day behind, you know, whatever. And boom, they go from Ctier to Btier. And you’re like, oh man. So now you know which ones work. And that didn’t cost you anything. It’s a formula in a spreadsheet. You run on the back end through your PIM or whatever software you’re using and it’s done.

Host: So yeah. So if I were to encourage some action uh from the listeners, I would say you don’t need to start with 180 data points, right? Like even if you were to do like a simple one like do we have enough images on every product? Boom. Knock that out, right? Like some of those things are like pass fail. And I love your idea too of just like what’s worse having only two images on a product or like adding a gener like like an infographic that could apply to many many products in my catalog. I would say like you know like populate your stuff right like get it going like fill in your product images like use all the characters. So that’s like a cool way to also visualize this to get started where it’s like you don’t need every metric right now, but like you’ll start to scaffold this over time. Yeah.

Mike: And that’s a that’s a really cool uh like mechanism there.

Host: Yeah. Yeah. Really cool. And it and it goes the same way with pricing. You I just talked to a brand yesterday, $15 million brand. They haven’t touched their pricing on 50 a little over 250 total products, 50 parents if you will, since 2023.

Mike: Interesting. The economy is the exact same. So there’s probably no detriment and I’m like, “Okay, we got to work on this.”

Host: Yeah. Um anyway, so it’s just, you know, again, throw a coupon on there, put take 10 cent off, add 10 cent. Just do something. Show Amazon that you’re in that. When’s the last time updated images? Well, it’s been six, seven months. Okay, just go in and put a new image in. You’re telling Amazon that you care about this product and you’re trying and it’s going to reindex. Now, sometimes that causes issues on the back end and whatnot, but again, that’s like that’s how you you revise it, you refresh it, and you show Amazon that, hey, this is not a stale skew. This is something they care about. They’ll redo it again. Oh, yeah. Absolutely. So, I love that we have a couple like easy examples of that sort of spray and prey approach. Um, just the sort of like get everything up to table stakes. I like that as like a a mental model here, but we’re still and I, you know, we’ve sort of teased at it a little bit. So, after you know, the spray and prey approach. Um, if I were to put it sequentially, so it’s like getting things up to a waterline. I would say almost like the other part of the equation, too, is like thinking of, well, where do I get a little bit more precise and where do I get a little bit more surgical and like where do I dedicate more cerebral like thinking? Where do I spend the mental glucose? Um what are some factors that jump out at you to indicate where to like really think like really double down where to use my ultra think

Mike: that is going to be on the qualitative side that is going to be okay we’ve checked all the boxes we have all the things now let’s understand what the quality is okay then you go down you look at your your conversion funnel traffic everything do I run ads yes no when was the last time I ran ads yes no um have I updated my pricing yes no u coupons deal, whatever. So, you just go through these simple things that you can put on and if you haven’t done these things in a reasonable amount of time, then do at least one of those and see what happens. Um, sometimes it’s that simple. We have brands that will come to us and we’re like, hey, when’s the last time you updated um this main image or a main image or a set of images and it’s like, well, it’s been 12 months. Okay, just go in and and do whether it’s your primary image or a secondary image or something like that, do it across scale. Uh, when’s the last time you updated your title? Well, we don’t. Why should we? It’s the character limit. Okay, we’ll just try something different. Move a like what people were shopping for 12 months ago is different from it is right now. Um, and we have that Cosmo and Rufus data that tells us that as well. When you can go right in the list on what people are asking, they’re telling you what they’re looking for. Do you do you And that’s another thing is like, do you answer these questions? Yes. No. These are literally the questions that people are asking when they come to your listing. If you don’t answer the question, Amazon is either going to say no or what they like to do is make an estimation and guess based on the information that they have. And you don’t want that. You want to control the narrative. So, I mean, it’s maybe not as technical and and and direct of the an answer you’re looking for, but that’s that’s kind of the flow when you go through it. Um, and then on your top products, it’s, you know, are you a nine out of a 10? Okay. What do you need to do to get you to a 10? Can you even do it? Okay. Um, is it the is it the video? How old is the video? Is have do you have can you do more than one video? Uh, have you tried UGC versus your own branded video? Um, does it answer the questions that you’re now putting in the listing so that your copy, your images, and your video all say the same message so that anybody looks any asset, any robot or human that looks at it knows exactly what the intent is, how to use it and u, you know, go from there. What are your competitors doing? What are the opportunities the the the advantages in your SWAT analysis that you have? Um have you parented before? Have you reparented? Can you can you add a new variation? Can like we do parenting analysis is so huge for us. Um you stacking it based on these two or three attributes. Well, in your category, it’s actually better if you stack on these attributes. You have your single packs separate from your three packs. Why would you do that? No, let’s put all your single. let’s put the right colors, patterns or whatever it is and let’s stack the quantities there and make allow them the comparison shop so you can make push them to the one that gives you more margin.

Host: I love that like it’s very easy to forget all these things, right? Like in the in the flurry of the flurry pace of like being on Amazon and selling on Amazon and all the million things you need to do, it’s very easy to forget a lot of those things that you mentioned, right? And I think the as we sort of like get a little bit deeper into this concept, it’s like half spreadsheet, half project management board because I also imagine if I was a team and we were to start using this, they would it would actually like we would like be leaving notes to each other like, oh, the last time we changed the image was blank. Yep. And then like days ago. So like go into our product manager sheet and like write down the date that we did it and then like that becomes another formula of like days since and like that impacts scores too. So it’s actually like I like it because generally when I do product optim product page optimization it’s almost like um something went wrong where it’s like oh this product is suffering let me go do a deep dive on it. And what I like about visualizing it in the way that you’ve brought it, it’s like much more proactive. It’s much more like we know where everything is. We know like what the status of everything is. We know when it comes time for our product optimization, we know like where to make our focus and we don’t have to like guess or like find out. It’s like sitting waiting for us.

Mike: Yeah. Yeah. I’ll give you a an edge case that kind of rolled up into another way for us to look brand um started getting a frequently returned badge because obviously Amazon started putting that on there and it’s for only for certain colors and ironically it’s not all sizes across all colors. You’re trying to figure this out what happened and we talked to the brand and they’re like have you changed anything? Have you trained suppliers? Have you changed this? Like no it’s like we’ve been doing this for three years healthy product consistent or whatever. Like well what happened? And it’s it’s what was a what was a medium three, four, five, six, seven years ago is not the same medium now.

Host: Oh wow.

Mike: They’re expecting they’re expecting different sizes, right? So if and then now Amazon doesn’t even allow us to put um size guides in the images. You have it’s it’s like they control it. Like come on. So you have to start have that feedback loop. You’re getting this badge. Why are you getting this badge? Is it anything that you have done? anything on the, you know, upstream or sorry, downstream upstream side where your your inventory, your supply, your measurements have changed, your cut, your cloth, whatever it may be. If none of that’s changed, you’re going to have to go and change the way you classify your your sizes or you’re going to have to be very specific. Loose fit, tight fit, long fit, short fit, or you’re going to have to like regroup this. that this is commonly because it’s too short. Well, now you call this a short and let’s go get another medium that’s a little longer and call it the long just like you do in a tux for, you know, for men, right? Short, regular, long, whatever. So, we it’s like that’s a way to be creative and in how like, man, nothing has changed on our end. It’s just the way that people identify and size and what the expectation, the fit that they expect a medium to be for them or a large to be for them.

Host: Go ahead. So I think that’s a perfect example, right, of like you need to take action and address this issue. Just to make it really clear for people, how did like this sort of process of like ranking, prioritization, like looking at these attributes, how did that surface that uh pretty specific, you know, not everyday issue.

Mike: Yeah. So you have, okay, advertising is kind of the same, you know, general spend, CPCs, everything. Uh then you start seeing conversion kind of drop and nothing’s happening. Your pricing is right and you’re looking in. and you go and you you find the date. Okay, it happened on April whatever. Okay, what what happened? Well, the the badge hit. A good badge or a bad badge can impact your sales equally as much, right? Okay, what’s the badge? Um okay, what happens? How do we get rid of the badge? That’s another thing as well. Well, it’s your return rate over 30 days, 90 days historical. Can we redo it? Can we do this? But also, it’s like this is not going to go away unless you change something. You have to change something. And then it goes back to what’s the lift? Man, I really can’t do it. Okay. Well, come to find out, you’ve used a a chart for your your uh your sizes, you know, small, medium, large. Measurement across the chest, shoulders, waist, whatever it is, Mike. I mean, when’s the last time I mean, I just got fitted for a tux last week. I got I got different measurements. I’m the same body weight for the last like 10, 12 years, but my measurements are different. I have a digital scale. I don’t know that. But when you go and you put the same shirt or you know you got this is a six foot male 185 pounds this is what it looks like on them how it hangs on them. People can identify with that and it’s just you change that and all of a sudden you stop getting returns. Yeah. It’s wild man. Um but that just surfaces of what can we control and first is what’s changed? Has anything changed? Yeah. Then it’s like what can we control and then what’s the lift for that control? Right. And then you have to prioritize it across hundreds of products.

Host: And the I think the last piece of this is now that we’ve surfaced information, we’ve sort of got the spray and prey. What are the um elements to determine where the lift will be the greatest or like where the le where the biggest leverage is? Meaning, let’s say you took that exact situation. You had two products, same kind of thing going on. Uh you know, conversion rates dropping a bit. Which one do you pick first?

Mike: So we have a model. We have a little over 350,000 SKs on Amazon US and we take all these numbers. So we can look at what a score of a six is or a seven or a nine or a 10 and we can understand what the delta is. Okay, here’s where they were at a six. We get these changes. They’re at an eight. What was that lift uh percentage wise and you can kind of you take them roll that out to the anticipated lift for that product. If you do this thing, that’s how you get the dollar amount to that to understand what to prioritize even at an individual skew. there’s like three things you can fix on the skew. Okay. Um that’s how we do it. That’s the model that we have in it’s dynamic thanks to the AI and the large models where it’s conly constantly iterative and it rechecks and make sure that we’re not just using like old you know analysis and old modeling and weights like no it does shift over time. Uh it’s not as impactful to okay clickthrough rate. Everybody’s always about main image optimization clickthrough rate. Well there was a huge lift you know 18 months ago maybe a year ago six months ago because nobody was really doing that. Now everybody’s doing it. So the lift that you get from optimizing your main image and improving your click-through rate is less because everybody’s doing it. Then it’s like, well, just just optimizing for click-through rate, does that actually increase your conversion? Yes, it gets more people to your page. Yes, you’re probably going to spend more on ads, but is it relevant traffic? Is it quality traffic? Did you convert? Yes. No. Sometimes you can improve your click-through rate, but your your conversion doesn’t doesn’t change. your actual units sold don’t change because the the quality of traffic’s not there. So all that has to be pulled in. Do you factor anything like um like total search volume of keywords per product or like market share percentage per product? You know, because like one thing that my head is doing, it’s like, well, if you have a product that has like, you know, 0.1% of market share for a niche and it’s got, you know, bad scores on stuff, if I fix those scores, maybe I can like potentially like double the revenue or something like that because there’s so much more market share. Do you do you ever factor in like percentage of market share in into this?

Mike: Yeah. So internally we have the query IQ and it’s basically your search query intelligence companion that we have. Got it. And we can pull TAM and we can pull relative market share search market share out relative to the individual search. Then we have clickiness and scrolliness. That’s another factor for us is people click and buy and go back and forth from this product a lot before they they buy or no man they click like three times and they buy. There’s high intent. Boom. Okay. that’s where we want to go. Or um and then clicking this and scrolling this and it’s like how far will they go down the page. Okay, you don’t have to be number one. Being number 10 is okay because you’re getting a a pretty good equal share at this point. So don’t keep pushing and pushing and burning budget. It’s too cost uh prohibitive or whatever. Yeah, share is a big point of it. Um and then we get to compare your share versus the market share as well over or like the the rest of the share if you will over time. And have you taken that? Have you lost it? has the total market shrunk as well and it’s in real time or like I guess a weekly basis on a search great performance every roll up.

Host: Amazing. Well, one watermark that I have for this show every show is did we hopefully inspire people to take some action and I think we hit the nail on the head. I think if someone’s listening and isn’t like very excited to have a list of their products and begin to sort of quantify, characterize, describe like all these different attributes down their product skew list uh and then begin to rank where you should be prioritized. I would worry if they didn’t do that, they might be stuck in like a productivity loop where they’re like, “Oh, I can do this now. I can do that. Now I can do this. I can do that.” without with missing like where the really low hanging fruit is and where the really big leverage activities are. So, I think we’ve done it, Mike.

Mike: Yeah, love it.

Host: Um, we have links to Advario in the description here. Uh, thanks so much for coming back on the show. It’s always nice to have your uh perspectives here every couple months. So, uh hopefully you come back soon. Um, what’s when you’re not optimizing, what’s something personally that you’re excited about lately?

Mike: Well, I just returned from a Euro trip. We spent like a week in Greece and then a few days in London on the way back. And uh a few things. When I travel like that, I like to go analog. I like to because I don’t want I’m a cheap ass. I don’t want to pay for the travel pass or whatever across three phones for 12 days and all that other stuff. I’m like, no, I want to learn and get immersed. We always pick a local spot, get close to the tube, go the same way. Like I know my three or four intersections. I know direction where to go and I just walk and do that. Um, and that’s so fun for me because you get to really experience the culture. You’re using your senses. It’s an overwhelm for it. And being analog, um, I didn’t I didn’t do any work for the the 12 or 13 days. I was totally out. You know, it also stress tests my my business for me and like my flow and did I give them enough work while I was gone through a sprint? How did it go? You you learn so much through that. And, you know, this is where kind of the other topic that we talked about at the beginning came from. It’s like this is this is where we’re going. Um, so it’s a nice reset. I don’t do those as much as I should, but in this highly digital world that we are in and this this AI ubiquity that we’re going through, man, get out in nature. Do it. I mean, you know, hopefully you don’t trip and break your wrist, but get out there anyways.

Host: Do it. Um, what was the best thing that you’ve eaten on that trip?

Mike: I had I ate my body weight in gelato. I It was everywhere. Um, honestly, I mean, the Greek food was absolutely amazing. The alfresco every every night, um, was was amazing. Um, you know, I’m I’m a big sucker for this for grape leaves. Um, they call them the vine leaves there. But, uh, I mean, I again probably equally body weight and taziki, right? Everything. Um, and then something new. So we I’ve done some buil before. We have a bottle at downstairs, you know, licorice type anise. And uh they have I think um is it is it Uzo? I think it’s what uzo. Yeah. So now we have that now it’s Christian at the house now. I brought the bottle back out and we do it after dinner as a digestive. Um Yes. And I’ll tell you the biggest thing is I love to eat. I I train I’m a hybrid athlete. I train intensely. Um I eat a lot and I did not train there. I only ran a couple times while I was there. I gave my body a full break, but we did 20,000 steps on a daily average, which is like 10 miles and I I didn’t gain any weight. Amazing. It was And I ate way more than I do usually. That was pretty a big epiphany for me.

Host: I love it. Yes. I’m thinking of my Greek trip uh like sitting down and just like eating taziki and and pa. It’s like that’s a that’s like a one of my favorite meals. It’s like so so good. Well, Mike, thank you so much for coming on the show. Uh there’s links to Advaro in the description of this video. Uh everyone else, you know, go build your ASIN prioritization list and uh we’ll have you back on the show in a couple months.

Mike: Awesome. Thanks so much.