Choose the Weekly Operator Scoreboard

Outcome: Select the few metrics that deserve weekly review and define the owner, source, threshold, and action trigger for each one.

What to do in this lesson

Watch: start with the lesson video.
Learn: use the summary and key points to capture the operating principle.
Do: complete the action steps against one real product, SKU, campaign, supplier, or workflow.
Submit: write one action card with owner, evidence, next step, risk, status, and review date.

Watch

Hosted on Google Drive.

Lesson summary

This lesson teaches how to analyze Amazon seller data from the Daily Sales Tracker (DST) to identify trends and insights that can help improve product performance. The key is understanding the relationship between different metrics like sessions, unit session percentage, organic vs. PPC sales, and advertising cost of sales (ACOS) to determine what’s working well and what needs optimization.

The lesson covers analysis of both an established product and a newly launched product, highlighting differences in the data and how to interpret them accordingly.

Key points

Organize data by Monday-Sunday to identify weekly trends across the account
Look at sessions, unit session percentage, and revenue to identify conversion issues
Analyze organic vs. PPC sales percentages to see if ad campaigns are performing well
Review ACOS (advertising cost of sales) to ensure profitability, adjusting as needed
Take notes in the DST to provide context for data trends and actions taken

Lesson notes

In this lesson you will get an overview of the DST in Scaler-OS tools. You can access the Scaler-OS tools here.

Action checklist

Review keyword performance and consider adding new, highly relevant keywords to PPC campaigns
Optimize product listings (e.g. update bullets) based on unit session percentage changes
Monitor ACOS closely during a product launch and adjust ad spend as needed to maintain profitability

Full transcript

Open transcript

Hello Titans, Justin Dyson here and in this video, we’re going to, we’re going to read some data. Okay, so it’s, it’s one thing to track the information in the daily sales tracker. It’s another thing to know what in the world is telling you. And that is really the point. The point is this should tell you a story of what your product is doing, what it’s not doing. And it should also be able to tell you how to improve it. So in order to do that, we need to understand what we’re looking at. We need to be able to see some patterns and trends and that will really help us paint a good picture. Now the other thing, which again, this is an account that’s being managed. So you, you see that there’s no notes in the DST. There was a note, you know, it would have, whoops, it would have a sole icon. And I expect all of you to have the sole icon in your DST because that means you’re taking notes and which is providing context for your product and it will help you tell that story without you having to dissect the data so, or in so much detail. But for this example, we’re just going to run through and I’m going to show you what I see, why I see it. And hopefully it will help you make the same conclusions with your own products. So first things to note, I’m on the parent view. And as you can see, there are five children or five child products here that we’re looking at. And all of this data is a collection of everything that these five products are producing with the exception of unit sold, which is why that’s, there’s one, two, three, four, five child distings here. And so there’s five columns for unit sold here, essentially. So as I’m just saying, you know, four units were sold here, eight here, one here, three here, one there. So that’s what we’re seeing. Now, just kind of a pro tip here. I have the date selected from a Sunday, I’m sorry, from a Monday to a Sunday. And I generally like to see the data in this way. If you’re always seeing it in this way, then you actually can start to see trends, not just for a single product, but for your whole account. Like, does your niche typically see spikes on Saturday, or is it on Wednesday, or what is it, right? So we can see that and we can figure out, okay, which days of the weeks should I be spending more money on PPC because I generally get more traffic and get more conversion and you can actually start to see that in the data. If you organize it that way. So I’m going from Monday to a Sunday and you’ll see that I’m not including the last three days. And that is because I have, I don’t have that data available, right? We know that the last two to three days, possibly of data isn’t complete because Amazon hasn’t given it to us yet. So I kind of remove it because I don’t want to see it in there because it’ll actually mess up my, my totals and my averages and things like that. So I typically remove it. So just kind of a pro tip. Now I’m just going to kind of dive in and show you what I see and what I believe that it means. So first things to note, you know, I like to just get a general feel for, are we trending in the right direction? So if you remove the daily data, you can basically see the oldest week to the most current. And you can start to see, you know, it’s the general trend of whether your sales are increasing or decreasing. And you can see this on an individual, you know, asin basis for the actual unit sold here. If we can look at that, we say, okay, you know, this one honestly is roughly the same. It’s like we had a pretty good week here, almost double that normal week. And that’s just what we see in the data. Do we see this across the board? No, actually, we don’t see it for this product. We do kind of see it for this one, but not really for any of these other ones. So this is just an anomaly and that’s okay. But it does tell you that perhaps your ads were hitting harder this week. We are actually going to dive into that. I think we can actually see that in the data later. So it’s worth noting, you know, you can see trends in this view. I like to do this with units sold. I like to do it with sessions because generally, you know, we want our sessions for a product like this that’s established. We want those sessions to be relatively the same or increasing if possible. But in this case, we should see under the rough of the same, maybe a slight downtrend, but we do see a go up and down between 2000 and 2500 sessions per week. So this to me is normal. One with unit session percentage, I want to kind of see the general movement here. And we see a small downtrend, you know, about a 1% decrease or so in unit session percentage. So what typically I would look for in this relationship is to say, okay, if my sessions are increasing, but my unit session percentage is decreasing, that means I’m driving the wrong traffic. Now, we just said that our session count is relatively consistent, but our unit session percentage is just slightly decreased. So really, that just means we’re not converting as well as we used to. And it’s just something to note at this point in time, we can’t make a decision or take an action on that just yet. Everything else that’s out of this, you know, I’m looking at revenue to, I do like to see if the revenue and mind you, if our sessions say the same, our unit session percentage drops, our revenue should actually decrease. That’s what that would tell you. And we see that here. It paints that story quite perfectly, actually. So we’re actually seeing because of our lack of unit session percentage or the drop in unit session percentage, we’re seeing a drop in revenue. That is the expected result. That means maybe we need to do something to, you know, increase that. Now if I was a good Amazon seller and I was taking notes, maybe what I would have found is that, you know, on March 30th or something, I updated the bullets for all my listing. If that were the case, if I had updated my bullets for all of my listings for this parent child product, and I saw my unit session percentage decreasing as a result of that, that means I messed up. I should put my old bullets back. Okay. So that would be an action. But again, there’d have to be a note there and you would have to have known that. Now if you were trying to memorize all this stuff in your head and be like, yeah, I’ll remember, you know, on March 30th of 2019, what I did, you won’t. So guys, please take notes. Now moving on outside of that, I don’t, I don’t really need to see the trend for a lot of these things, are a lot of these other data points. The main ones I’m looking at are the organic to PPC ratios, organic percentage. We see is relatively consistent within this range. That’s pretty good. It’s within about 10% difference over time, and we should see the same relationship with PPC. So if this goes up or down, this one should have the opposite effect, right? That’s the expectation, unless I’m running external promotions, which I’m not. So in this particular case, the last thing I’d be looking at is tacos. So 1914, 18, 23, 19, relatively consistent. Now you might be thinking, well, this is high. Now super important. This actually isn’t high. For this product, the profit margin is 52%. A third of that is 17%. So in this particular case, I’m actually sitting pretty close to my tacos target for this particular skew. Again, this is something that it has to be specific towards your product, all right? This is a very mature product. We order a lot of inventory, and there’s just generally, we have very good supplier. You know, we’ve gone to China. We’ve done our supplier negotiation. So we have very good margins as a result. And so we can tolerate a tacos that’s as high, and you should be perfectly fine with it. Now, could we optimize it better? Sure. That’s the case with just about every product, but I’m not unhappy about this. I’m not going to take any action as a result because I’m profiting quite a bit on this product, despite having seemingly high tacos. Now, B2B, I don’t really care about this. There’s not generally too many orders we get like this, so I’m going to ignore that. And outside of that, I can pretty much just ignore most of this. Now, the only other thing that I would check on, but again, I wouldn’t be for a trend. It was just to make sure that this number doesn’t change. My FBA fulfillment fees should never change. If they do, I need to run a report and submit that to Amazon. Now, that’s kind of it for that summary view. Let’s dive in a little deeper. Let’s say you want to go look at a specific variation and just to see what it says. Now, we noted on this one that we had a spike in sales on one of these weeks, what was it? This week here, let’s see if we can figure out what happened there and let’s see if we can duplicate it. Wrong one. All right. So, as we’re now in that specific variation, and if we come down here to the week where we actually sold more units, which was this one here, let’s see if we can find out what happened. Because what we want to be able to do is say, okay, well, we saw a spike in sales this week. How can we duplicate that? And if we look at our session count, honestly, there’s not a significant difference from any other week. If anything, it actually is lower that week than it is most of these other weeks. So it wasn’t because we were driving more traffic. So that’s kind of tip number one, right? If your session count doesn’t see a spike here, but your overall sales increase, that means your unit session percentage should be higher. And we see that it is. It’s 12% compared to 4, 4, and 6, right? And, you know, 5 in this case. So we converted better this week. That’s what it means. All right. Now, why? I don’t know yet. Maybe we won’t ever know because sometimes that’s just how it is. But as we go through here, we can see, okay, our organic percentage looks like 81%. It actually looks like our organic percentage is lower this particular week, which means our ads must have been performing better that week than they normally do. And if we look at this again, if we just kind of make this a little simpler look at the summary of weeks here, we look at our PBC revenue and we see that boom, this is the anomaly. This means the reason we saw a spike in sales for this week is because our ad spend, I’m sorry, our PBC sales were higher than they normally are. They’re normally like 20, 40 bucks, right? That’s what we see here. But in this case, they were 113. Our PBC percentage was almost 20% compared to, you know, 6 to 14 normally. And what we also see is our tacos went down as a result. We started getting more sales. So our tacos goes down as a result. So that’s a great thing to see. And we see her tacos as a dollar amount was only 86 cents that week. That’s fantastic, right? So what I would take action on here is maybe I go into my PBC, I look at the data for this week and see what particular the keywords where we actually converting on, do we need to spend more on those keywords and is there something I can do to make that happen again? And that would essentially be the action that I’m here. Now you don’t have to take that action. I’m not saying you should take that action for every single time you see this. But if there is an anomaly like this, you want to be able to go through the breadcrumbs, look at every data point to find out, hey, what’s going on with this product? And is there something I can do or should do about it? And in this case, again, it would just depend on your scenario. If you wanted to try to duplicate that, that would be the method for figuring out what happened and to go see if you could actually duplicate it. So that’s really it. I think for this example, let’s look at another one. Okay, so in this example, we’re looking at a completely different set of products and we’re looking at something that was actually launching. So I think it’s important to see the difference in the data. You know, when we’re looking at a more established product and we’re, let’s go back to this tab that we’re looking at earlier, when we’re looking at a more established product, you know, looking at this, you know, apparent view here. What we see is, you know, the sessions don’t really fluctuate too much. We’re not seeing a lot of changes. And that’s normal. That’s what you expect to see in an established product. But if we go into something like this, we’re like, it’s in launch mode, right? Like this thing launched on April 5th, according to this data. What we want to see is a trend upwards in certain metrics and really what the reason we’re looking at this is to find out, do we need to take any action? And a lot of times, if you’ve picked a good product and you’ve set things up properly and you’re running ads the way we’re teaching, you don’t really need to make a lot of changes. And that’s really what this example illustrates here. So basically what we see again, we have three variations here. You can say they all kind of, or two of them sell pretty similarly. One sells a little bit less. So okay, maybe that variation just isn’t, you know, hitting it with the customers. That’s okay. We’re looking at this thing as a whole. But the first thing you want to see is, you know, are we trending in the right direction? And quite frankly, like this product launches pretty much crushing it. So we go from like three to five a day on the initial launch or on the day of launch and then like on the 10 that was almost 20 a day on average, about 19 or 18 a day on average. So like that’s fantastic. We look at our sessions, we go from 355. So we’re basically seeing a nice steady increase for the most part over this week long period. This is fantastic. That’s exactly what we want to see during a product launch, unit session percentage. The cool part about this is typically what can happen during a launch is you start getting a bunch of sessions, but your, you know, conversion rate of unit session percentage actually drops because you’re driving a bunch of traffic to a listing that doesn’t have a lot of listing credibility. Well, in this particular case, again, this is why this product launches actually doing so well is you’re seeing a consistent increase in the unit session percentage despite the session count increasing. That means we’re running ads on keywords that are freaking crushing it. We have picked our keywords exceptionally well and we have, we’re running ads at a great cost per click to basically convert at whatever placement that is getting us. So like this is good. That tells me I shouldn’t touch a thing, right? If anything, this means I should add more keywords and see if I can squeeze more juice out of this thing because the conversion is actually pretty decent. And if I come over here and look at reviews, I don’t even know if there are any reviews. There’s not any reviews yet. It’s kind of unheard of. It is what it is. Again, we always recommend you try to get some reviews here pretty quickly. But let’s be honest, you can only get reviews if you get sales. This product’s not even a week old or this data or at this point in time anyways. It’s like barely a week old. So we shouldn’t actually have any reviews. Despite having sold, you know, as many units as they have on this particular product launch, there are no reviews. So maybe I wait before I add some more keywords to my campaigns. But right now the indicator is once I get more reviews, once I actually get any reviews, as long as there are five stars, I should actually see this unit session percentage increase. So that’s kind of the key takeaway or one of the key takeaways here. Review counts still at zero. Once I get those reviews and assuming there are going to be five stars, we should see our unit session percentage continue to increase. If we continue to see that, then we are going to keep adding more keywords to our campaigns that are hyper relevant. Now, if I keep looking further into this listing, again, we know that units are increasing. So that means our revenue should be increasing. We see our BSR in the category keeps going down. We do happen to have the Amazon’s choice badge for this product or at an Amazon’s choice. It was number one new release badge for this product, which like no kidding. Like this is a fantastic approach for an initial product launch for this type of product, especially in a very competitive niche that this is in organic percentage. Now, this is super important. I want to call this out. So percentage of organic sales, we see is not great. It’s the opposite of what it should be. Or is it? It actually, no, this is exactly what it should be. It should be low. We’re launching. We don’t rank organically for like any keywords, right? So in this first week, the expectation is absolutely, most of our sales should be coming through PPC. And that’s essentially what we see. Organic percentages on average is 27%, right? We want it to be the opposite. We want it to be like 60, 70, 80%. But that’s okay. We are launching. I’m 100% okay with this. I’m not going to make any changes based on this data point. Off Amazon adspan, we’re not running any promotions. It’s strictly PPC in this particular case. And then again, you look at your PPC sales here. We can see those are in pretty solid. We’re getting sales every day. Our ad spend, I’m sorry, the revenue associated associated associated with that is really good. We’re looking at our percentage of PPC sales, again, if the organic percentage is low, then this PPC percentage should be high. And it is. So that’s what we’re seeing here. This is just a weird spike in the data, just or normally you can’t have more than 100%. It just happens to be that way because this didn’t take, or this was in fact during this particular day, just a little blip in the data, something we can have fixed. Spend pretty consistently high. So one thing to note. As you can see, yes, I am making good sales here and making a lot of headway. However, that is at the cost of very high ad spend. This is $538 a day, $460 a day, $388 a day. So I am very aggressively spending money on this product. Now, when we look at the tacos as a percentage, it’s quite high, right? And that’s okay. Again, guys, we are launching a product, so I’m totally cool with this for now. But look at what we see. We see it go from 80, again, blip in the data for that day. So 82%, 77, 59, 62, 41. Even though this is a small data set, this is trending down. That is fantastic. That’s exactly what we want to see. And that’s the relationship we see. When you see these higher PPC percentage and then you start to see it go down a little bit here, we should start to see tacos percentage go down as well. So again, this is a brand new launch. We’re not going to make any huge changes based on this data. In fact, this data is telling me that don’t touch a thing. It’s a working. Okay, that’s what this data is telling me. Do I like this tacos? No. But I’m launching. So I’m totally cool with it. And I will roll with it for now. Again, when I’m in reviews, we can see our Amazon fees are as long as these are good and these are what they should be, then we have nothing, no action items to take here. So I just wanted to quickly go through these couple examples. You know, one of an established product and then one on a product that is launching, just to show you like what the data says, why in just giving you some context as to like what it means and should you take action and why or why not? Again, there should be notes in here talking about what we’re doing. If we launched on whatever this was, the fifth and on the eighth, we added a keyword and removed the keyword, maybe we put a note in here, right? Especially if it’s a root keyword or something that we didn’t mean to put in there originally and it was just blown through ad spend and maybe we put a note saying, you know, removed keyword, whatever, because it was just overspending. So we do want to see notes in here that would make this so much easier to manage and understand if there is context in that regard. But hopefully this is helpful and you can see, you know, the relationship between the data points and what they lead you to believe based on whatever they say. So thanks guys, I’ll see you in the next video.

Resources

Source lesson: Where and What is the Daily Sales Tracker
Resources: none attached yet.

Track: 01 — Seller Operating Baseline
Module: Control Tower Setup