#590 – Who has the Most Accurate Amazon Search Volume?

42 minute read

Published: August 24, 2024

Modified: September 12, 2024

Join Bradley Sutton in this episode of the Serious Sellers Podcast as we explore the vital importance of search volume metrics for Amazon sellers. We’ll reveal why accurate search volume data is crucial for making informed decisions on listing optimization, PPC campaigns, and more. We’ll discuss how to gauge demand in a niche and prioritize keywords effectively, while also addressing the limitations of Amazon’s own search volume metrics.

Listen in as Bradley addresses the misinformation circulating in the industry, particularly a misleading LinkedIn post comparing search volumes from Helium 10, Data Dive, and Jungle Scout. The episode highlights the flawed methodologies used in such comparisons and the significant differences between normalized and denormalized search volumes. Bradley clarifies the historical changes Amazon made to its search volume data and emphasizes the importance of fact-checking and accurate representation in tool comparisons.

Lastly, we’ll highlight the importance of maintaining civility in discussions about Amazon tools, particularly when it comes to the accuracy of search volume data. After conducting comparison tests, where we matched Helium 10’s data against Amazon’s only normalized search data, Brand Analytics, Helium 10 achieved an impressive 93.5% accuracy rate. In comparison, Jungle Scout scored 41.9% accuracy when evaluated against Search Query Performance, which uses a denormalized search metric. It’s crucial that we provide our audience with reliable information. We are committed to addressing misleading information in future episodes, ensuring that our listeners receive the most insightful and accurate information. Thank you for your support, and stay tuned for more in-depth analysis.

In episode 590 of the Serious Sellers Podcast, Bradley talks about:

01:52 – Accurate Amazon Search Volume Metric Importance
06:30 – Keyword Sales Is The Best Metric
07:11 – Addressing Misleading Information
12:19 – Debunking Jungle Scout’s Blog On Keyword Accuracy Analysis
17:30 – Search Frequency Rank And Why It’s Important
20:27 – Normalized vs. Denormalized Searches
20:58 – The History Of Search Volume In Amazon
21:22 – Understanding Normalized and Denormalized Searches
25:31 – Stop Comparing Apples to Oranges
26:20 – Let’s Do A Real Test
27:42 – How Accurate Is Helium 10’s Search Volume?
29:18 – Jungle Scout and Data Dive vs Search Query Performance Data
32:20 – Confusion Over Jungle Scout Search Volume History
35:45 – Bradley’s Final Message

Transcript

Bradley Sutton:

Search volume is one of the most important metrics for Amazon sellers to help make decisions like Listing, Optimization, PPC and more. Now, who has the most accurate search volume out there Jungle Scout and Data Dive or Helium 10? Well, spoiler alert in today’s case. Today I’m going to show you that Helium 10 wins with a 93.5% accuracy, with Jungle Scout coming in second at 41.9%. How cool is that? Pretty cool. I think. You want to know what keywords are driving the most sales for listings on Amazon. To do that, you need to know what highly searched for keywords the product is ranking for, maybe at the top of page one. You can actually find that out in seconds by using Helium 10’s keyword research tool, Cerebro. Now, that’s just one of the many, many functions that make this tool my favorite tool in the whole suite, and it’s the most powerful keyword research tool ever created for e-commerce sellers. For more information, go to h10.me/cerebro. Don’t forget to use the Serious Sellers Podcast discount coupon SSP10.

Bradley Sutton:

Hello everybody and welcome to another episode of the Serious Sellers Podcast by Helium 10. I am your host, Bradley Sutton, and this is the show. That’s a completely BS-free, unscripted and unrehearsed, organic conversation about serious strategies for serious sellers of any level in the e-commerce world. And today, guys, we are going to have a special episode where I’m going deep. I spent a couple of nights without sleep working on this because things got me real riled up on this. All right, this is an important topic to me, and there’s just so much misinformation out there that I was like I got to set the record straight.

Bradley Sutton:

Now the question is who has the most accurate search one? Well, of course, the first answer would be Amazon itself has the most accurate, because they’re the ones who are providing information. Now, sometimes, though, it’s not always the most useful though, like, for example hey, I’m trying to do research into a niche that I’m not selling in. Yet you’re a little bit limited with being able to see search volume in Amazon. Search Query Performance for an existing listing. Great, all right. Uh, that shows you denormalized numbers. We’re going to talk about what that means a little bit later. But if you’re looking at, hey, well, the keywords that I’m getting traction for already, what is my search volume? There’s nothing better out of a great apples to apples comparison as that. Now, the drawback there is you can only see what you’re already ranking for you can’t really like, put in your competitors and see their search volume. But again, obviously this is Amazon’s platform. They’ve got the most accurate search volume. I’m sure they have multiple search volume metrics, some of which Amazon sellers can get at.

Bradley Sutton:

But let’s just talk about this. Take a step back. Why is search volume important? Why do Amazon sellers rely on this metric so much? Well, there’s a lot of different reasons. Maybe you’re just looking for demand in a certain niche, for example. Hey, I’m looking into selling in this category. I don’t see many products here with sales, so I can’t really estimate demand because there’s not enough sales. Maybe it’s something newer, but there’s a lot of search volume, right, because you could have a lot of search volume for something, but no sales yet because there’s no competitors yet. All right, so that’s something exciting. That’s where search volume could be important. What about you’ve already decided to make a product right? The number one reason that we need search volume is prioritization. What do I mean by that? Let’s say I’ve identified 200 equally relevant keywords. Obviously, all keywords aren’t equally relevant. Let’s just play devil’s advocate and say we’ve got 200 keywords. That we’ve done in all of our keyword research and I need to put them in my listing.

Bradley Sutton:

Now, can you put 200 unique phrases in phrase form in your listing to send those relevancy signals to Amazon, to let Amazon know hey, this is my product. You know, you always want to put your most important keywords in phrase form in your listing. No, you don’t have room for 200 separate phrases. You maybe have room for 15, 20, 25. Well, how do you prioritize? Which ones you’re going to put in phrase form, which ones you’re going to concentrate on? Right, if all things were equal, the one thing that is different is search volume, right? Hey, my most search ones of these equally relevant keywords. That’s what I’m putting in phrase form. The most search ones of the most relevant. That’s what’s going in my title, right? Similar with you. Know, when you’re deciding what you’re going to do for PPC, hey, am I going to try to equally target all 200 words? No, I might try and like target 20 words at first, 30 words at first. Again, relevancy is the most important. But then the next metric is search volume. All right, you know, I’m not going to try and put a whole bunch of 1 million search volume keywords in one campaign and then another campaign with an equal number of keywords that have 100 search volume. That just wouldn’t make sense, right? So, I’m sure all of you would agree with me that a search volume is something that is important. Helps us in many different ways as Amazon sellers.

Bradley Sutton:

Now here’s the interesting thing. It’s not always the number itself as the most important. When you think about search volume for prioritization, it’s really the order in which they’re in, right? That’s one of the factors, not just the number itself, like, for example, um, you look at google trends, uh, google trends is not search volume, right? People have been using google trends for years and it’s a scale of one to 100. Helps you prioritize, right? Brand Analytics, which you guys know I love. You know there’s no search volume number in Brand Analytics. That’s the data point that amazon gives and has been giving for like what, four or five years now. There’s no search volume in there. It’s just giving you an order. It gives you search frequency rank.

Bradley Sutton:

You’re totally able to prioritize keywords not based on a search volume number. Like, if all you had was Brand Analytics and zero search volume number, guess what You’d be able to do almost everything you do right now, right? Even if there was no Helium 10, no Jungle Scout, no, anything. You just had Brand Analytics, no search volume numbers at all. That’s enough information to prioritize. Now you might have to make your own little formulas or something like that to try and see hey, I only want the search frequency rank from, from, you know, 500,000 and up, or 500,000 below, I should say, you know. Or a hundred thousand and below, you know. Of course, you know you might have to do something, but still, you could get around, uh, get along without the actual search volume number. So, it’s not necessarily the search volume number that’s the most important. Again, it is which ones are searched more in comparison with whatever other keywords you have, right?

Bradley Sutton:

Now, of course, the best way to prioritize even more than just search volume itself or search order, is keyword sales, right? Not all keywords are created equal, right? You could have a 500,000-search volume keyword that generates, you know, the products on the page generate a hundred sales only because there’s low, low buyer intent. You could have another keyword that’s 500,000-search volume and it could generate a thousand sales because there’s a lot more buyer intent. So actually, the best metric, of course, to prioritize if you’re talking about, hey, what’s going to potentially bring me the most sales is keyword sales.

Bradley Sutton:

Now, are you able to see estimated keyword sales by keyword? Yeah, Helium 10 can help you with that. Jungle Scout doesn’t have that. I would assume that Data Dive doesn’t. I have access to a Jungle Scout account. I don’t have access to a Jungle Scout account. I don’t have access to data. I can only monitor the biggest competitors out there. So, Jungle Scout, the last time I checked, no keyword sales. I would assume data doesn’t. But if I’m mistaken, I apologize.

Bradley Sutton:

Now, why am I even doing this episode? How did this drama all get started and why am I so worked up? Now, before I even get into this, let me just give a kind of disclaimer here. I’m pretty passionate about this subject. I might get a little worked up in this episode. I hope nobody takes anything personal. I’m even going to blur names over here. People can probably figure out by looking at posts and stuff where the party’s involved. But again, I’m not trying to call somebody in particular out. So, I hope this doesn’t come off as oh, I’m trying to like fight somebody in the backyard or something like that. All right, I just really get worked up about this kind of topic and when people are throwing Helium 10 under the bus, or when people are misleading others, intentionally or not, who are you know? Known figures like it just bothers me, all right. So again, I’m not going to try and throw any name, drop here personal names. I apologize if anybody ahead of time, if anybody gets offended. I’m just stating the facts. All right, just the facts, ma’am. All right.

Bradley Sutton:

Now, how did this all get started? It all got started with this LinkedIn post. Uh, that’s somebody. I have no idea who this person is, I’m not connected to them, but somebody I think they tagged me. Uh, people tag me all the time on LinkedIn. I’m not that great on LinkedIn. I don’t do the whole, you know, interaction with other people’s posts, like I’m supposed to. But anyway, somehow this post did get on my radar and I have nothing against this guy who made this post. He, he’s not an influencer in this space where I could say, oh, he should definitely know better, whatever. But anyways, here is how this post looks like on LinkedIn.

Bradley Sutton:

He was like hey, Helium 10 versus Jungle Scout versus Search Query Performance, comparison of search form. So, when I saw it, I barely skimmed it, because I get so many of these tags every day. I don’t interact with hardly any of them, but he was like hey, why does helium 10 display three to four times lower search volume compare to Jungle Scout and Search Query Performance? Bradley, what are your thoughts? Blah, blah, blah. I use 80 keywords to compile the data, et cetera, et cetera, et cetera. Now, at the time I didn’t really even look very closely at this, because I think I saw this graph that he gave and it didn’t even show the keywords or anything. I’m like okay, it is what it is. This is just one of those things that I get tagged like on a million times.

Bradley Sutton:

But then what happened later is at the top of my feed, somebody who I am connected to and again is at the top of my feed. Somebody who I am connected to and again who I think is a very, one of the most respectable, uh, respected, people in the space, put out this message where he reposted it and was like hey, this, this dude did an analysis where he did 80 keywords that analyze with Data Dive and Jungle Scout compared to Helium 10. And he was questioning which one is most accurate and I told him to check Search Query Performance. All right, so there’s strike one. I’m like why would you do that? What does Helium 10 have to do with Search Query Performance? All right, we’re going to talk about that. Why? Why, this is such like a no brainer. Like why in the world is this person doing that? But let me keep going here. He says oh, after doing this, he found that Data Dive was within 5% accuracy for this keyword and Helium 10 had a deviation of 70. All right, this data is crucial.

Bradley Sutton:

So now, all of a sudden, I’m starting to get pissed. I’m like this this is ridiculous. Helium 10 has nothing to do with Search Query Performance. Uh, you know whether Data Dive or Jungle Scout is. You know, we’ll talk about that in a little bit. But like, why are you even bringing Helium 10 into this conversation? It’s ridiculous that this other guy had mistakenly compared the two, thinking it was the same. But again, he doesn’t work for a SaaS company. He doesn’t know. You know the ins and outs of he’s not monitoring. You know other companies and knows what they base their search volume. But I wouldn’t expect this individual to have no. And I even, when this like, I think you probably want to delete this post, you know, couple of times. I said, I was like, I don’t think this is a good look you know for you to like put out misinformation like trying to say that, oh Data Dive, Jungle Scout is 5% off of this amazon data point, but Helium 10 somehow has that 70% off. But they never took down the post. I’m like alright, that’s when I started not sleeping, like two nights in a row of just like data crunching and preparing for this episode. I’m like all right, you asked for it. Now, again, I told you guys, I wouldn’t make it personal, but I get worked up about this.

Bradley Sutton:

Anyways, it wasn’t just this, things were escalating even more. Like a high-level executive from Jungle Scout hops on this thread and says, oh, we consistently see similar results in our own validation and hear similar feedback from customers, you know, basically talking about, oh, that Jungle Scout is so close to this Search Query Performance, but then Helium 10 is so far off. Supposedly they validate this all the time. And this is what and they hear this from customers all the time. Like what is going on? More misinformation from somebody who’s respected in the industry. Like why are you saying this nonsense? This is happening now.

Bradley Sutton:

But then a couple of months ago, uh, somebody forwarded me a blog, uh, on March 21st, that Jungle Scout put out Jungle Scout versus Helium 10, a comprehensive review. Uh, march 21st, 2024. You see it right here, dun, dun, dun. Like you see the big logos you know, versus each other. Now this blog, anyways, was just, oh, my goodness, there were so many inaccurate things in there, it just boggled my mind, really got me upset, but like I never did anything at that time, it was just all of this now together, kind of like put me over the edge.

Bradley Sutton:

But the one part, that of that blog that has to do with this, was a big section they had on Keyword Accuracy Analysis. Who is more accurate Jungle Scout or Helium 10 for search volume? Keyword search volume information? And look at what they said in this blog. They’re like hey, amazon provides Search Query Performance and we found that Jungle Scout was way more accurate than Helium 10’s keyword tool. On average, keyword Scout showed a positive 10.93% difference from the search volume provided by Amazon and Helium 10 showed a negative 58% difference. See the info below. And we chose keywords from Search Query Performance. And again, so like hey, if Jungle Scout wants to compare themselves to Search Query Performance, fine, if that’s what they’re basing their search volume on, go ahead. But why are you bringing Helium 10 into this conversation? Helium 10, uh search volume has nothing to do with Search Query Performance search volume.

Bradley Sutton:

But then I’m looking at this, this, this case study that they supposedly did, and it just didn’t make sense. It was like potty pads Helium 10, 11, three, 93 search volume. All right, this is, this is like their big expose to show how Helium 10 is different. Now, first of all, the number is just super weird here. Even according to them, uh, Amazon had 10,000, Helium 10 had 11,000, but somehow the difference was negative, 8%, like we were under. Like that, that’s not right, like we’re over according to this, but anyways, that’s not important.

Bradley Sutton:

I was trying to find out okay, in in Helium 10, we, we have history that goes back five years for a search volume. Okay, I think Jungle Scouts got only has two years, but anyways, Helium 10, 393. I was like, let me try to find where that is. And I kept having to go back and back in time to try and find out when in the heck they were pulling this data. And, lo and behold, I found this 11,393 number on 9/24, wait for it, guys 2022. So, this is a new blog. The date is 2024. And they’re pulling some data point from September, like two years ago, two years, literally two years ago. So, I was like, well, that’s weird, it did really Jungle Scouts numbers uh, you know, look like this way.

Bradley Sutton:

Back then. Now that’s where things started getting weird. I was like this whole article just doesn’t make sense because, uh, again, you know, they were saying that, hey, Jungle Scout said 10,800. And so, if they were taking Helium 10 in September of 2022, I was like, well, what really Jungle Scout said, such a close number to search, create performance. So, I look back in Jungle Scout to that same date of September of 2022 and started adding the numbers up. I was like no, look, these are weekly search volume that Jungle Scout is giving and it’s like 6,000, 6,000, 5,000. I mean, we’re talking like 20, 30,000. Where in the world is Jungle Scout saying that they were 10,800.

Bradley Sutton:

Now I think maybe what happened was, later Jungle Scout changed, you know, after 2022 changed our whole search volume a model, because they made announced that they were trying to follow the search, create performance. So, I’m assuming they did go to like the denormalized number. I didn’t realize at the time that they actually backdated and went back in time and maybe changed all their search volume numbers from before Helium 10 numbers don’t change once we have the search one. That’s there permanently. But anyways, I’m not sure that’s the reason, but I could not find where Jungle Scout was 10,800. Because if I went back in time right now using Jungle Scout, it’s way more than that.

Bradley Sutton:

But anyways, these things were just like oh, really making me mad. Like LinkedIn, a bunch of people saying these crazy things, and then here’s Jungle Scout blogs again. That’s what kind of upsets me when people with authority you know who people trust is putting out misinformation to try and pump themselves up. Like, no, if you want to pump yourself up, pump yourself up with facts. Like why are you pulling in wrong information? So now that’s when I was like, ok, fine, let me go and do a deep dive no pun intended, on this original guy’s post. Well, again, I don’t know who he is, I have nothing against him personally, but I’m looking here and, like I said, there was no even keywords mentioned here. So, I was like, well, I can’t even double check this information and then just weird things were happening. First of all, you know, remember the other individual who I respect was trying to say, oh yeah, Helium 10 is off by 70%. That’s not even what this guy was saying in his post. He was saying Helium 10 was off by 70% from Jungle Scout. I’m like why are we even doing it? Why are you comparing Jungle Scout with Amazon? But then you’re just comparing Helium 10 with Jungle Scout.

Bradley Sutton:

And then take a look at this, the way they were calculating the numbers for some of these. He’s saying Search Query Performance says zero and Helium 10 and Jungle Scout are saying a certain number, but then somehow that means a Jungle Scout is a hundred percent off. So, if Search Query Performance is saying zero and Jungle Scout says a certain number, that’s infinity percent off. You know, like you shouldn’t even have counted that, bro, like I don’t even know what. That’s not the way you do. I’m not a data scientist, I’m not a mathematician at all, but I’m pretty sure you can’t just say it’s 100% off when you’re comparing something with the number zero. But anyway, so his numbers of 5% off for Jungle Scout and 70% off of Helium 10, the whole thing is bogus, right. Like it wasn’t an accurate test and he shouldn’t have even done it anyways, as I’m going to show in a little bit, because Helium 10, again has nothing to do with Search Query Performance. Now Jungle Scout has said multiple times, even in this thread hey, you know, we’re close at Search Query Performance, so go ahead and compare Jungle Scout to Search Query Performance. Guess what I’m about to do that you know in a few minutes here. Uh, so that part was fine. But again, why are you all trying to bring Helium 10 into this conversation? Now you might be wondering well, what is Helium 10 search? I’m going to get to that in a little bit.

Bradley Sutton:

Now, another funny thing about this one you know graph that this guy came up with is the numbers. Instead of showing that, you know, Jungle Scout is so close If you can take this numbers for granted it actually shows that Jungle Scout is way off. Remember I told you, what’s more important than the actual number is the order in which, uh, the number of searches is presented. Right, the order, the search frequency, rank. That’s the important thing. Take a look at this guy’s own graph, like, for example again, I don’t know the keywords here because he didn’t put it but look at this keyword a, let’s just call this keyword a. He’s saying Search Query Performance was 6,000. Okay, and this keyword B was 5,000 something. Okay.

Bradley Sutton:

So, you know, if you were going to prioritize one keyword over the other, which one would be the priority. With the actual Amazon data, it would be keyword A right Because it says it has 6,000 search volume. But then look at in his own chart, the Jungle Scout numbers. Or for those same keywords, keyword A only 3,000 search volume. So, the number is far, way, far off. But again, nothing wrong with a number being off. That’s not what’s important. The importance is the order. But his keyword B Jungle Scouts, keyword B was 4,000 search volume. So, it actually not only was way off in the search form. It was prioritizing the wrong order. So, if you were going by Jungle Scouts, you would have prioritized keyword B, because keyword B has 4,000 search volume and keyword A only had 3000, but guess what? Search Query Performance was completely opposite. So, he thought he was like maybe trying to hype up Jungle Scouts supposedly 5% accuracy but actually he was exposing something where it’s off.

Bradley Sutton:

Now, as I started reading this more and I found you know what this entire thing was off because he was taking Jungle Scouts search volume from right now, or you know the last time Jungle Scout checked, which was August 10th. Okay, he was comparing it to Search Query performance all the way from July 1st through the end of July. So, we’re not even talking about an apples versus apples comparison here. So, like again this whole original post, kind of like a waste of time here. But what happened was is people started jumping on this and that was what. That was what made me mad and nobody, nobody checked this.

Bradley Sutton:

It’s like all these people jumping on this post and say, yeah, this is exactly what we see and we find the same numbers ourselves, and another person said, you know is reposting this and saying look at you know, uh, how accurate Jungle Scout and Data Dive are. But this whole thing was just a ridiculous post in the first place and none of these respected people should have been posting this information. I’m sure maybe I’ll do that sometimes, maybe I’ll just get so happy that somebody is hyping up Helium 10 and maybe I don’t fact check, fact check, uh. But if it has to do with, like throwing a competitor under the bus, you’re never going to find me throwing a competitor under the bus If I haven’t, like, fact checked everything, like I literally spent the last 48 hours fact checking all of this before I make this podcast here to make sure I’m doing my due diligence and I’m not putting out misinformation, and that’s what I would expect others to do as well. But again, you know, regardless of all these numbers being wrong, the whole premise of this was wrong, even if he picked the perfect numbers, because he’s trying to compare things to Helium 10, which is based on normalized searches, and Search Query Performance is based on denormalized, and Jungle Scout is denormalized too in day to day because they’ve been open to say, hey, we’re comparing ourselves to Search Query Performance, so they actually said that they were changing to denormalized a couple of like about a year and a half ago. Now let’s get a little bit more into the history of search volume on Amazon so you can kind of understand how we got to this normalized versus denormalized. Now Amazon years ago like 2018 around there actually made a search volume that is normalized the actual number that Helium 10 designed its algorithm after it was available in the API to like software tools, and Helium 10 was the very first one to get access to it, and so we’ve got the most historic search volume data out there Now.

Bradley Sutton:

Normalized means how many times pretty much somebody typed in a search term. So, if I search coffin shelf right now, that’s one search. But then if I search that same keyword 10 hours from now, you know within 24 hours the search volume that Amazon counts as normal. Normalized means it still only counts as one. If I click to page two, it only counts for one. If I click back on my browser after I was on page two, it still only counts as one. There’s only one search that somebody did in 24 hours.

Bradley Sutton:

Now, denormalized means hey, I search coffin shelf right now, there’s one search. I click on a product on that page, I click back on my browser. Guess what that’s? Another search. I click another product and I click back. There’s another search. There’re three searches. Now I click to page two of the search results. Guess what that’s counted as a search. Now we’re up to four. Five hours later I come back to my computer and I search again that same exact keyword. Guess what that’s five? I hit refresh on my browser for whatever reason. Guess what that’s six? So, D? Uh, norm, denormalized means it’s counting six searches, six search volume for that one individual, whereas normalized, which is what the original Amazon search volume is based off of, it’s only counting one.

Bradley Sutton:

Now, before, when Amazon first started product opportunity explore and Search Query Performance, amazon still was basing their search volume on normalized searches. But then they made this big announcement all over the place in about April May of 2023, that says, hey, we are changing our model. This was plastered all over the place in Search Query Performance we’re changing our model to be denormalized, and they explained exactly what denormalized meant, and that was like what I was talking about. And so, what was the difference in the search volume number Once Amazon moved it? I actually have some screenshots. Take a look at this. This is from a post I made because I used to talk about denormalized and normalized all the time. So, here’s a post I made in one of our Facebook groups If you look at the coffin shelf niche, all of the keywords put together for 360 days was 85,000 searches. That’s the normalized search volume. But then Amazon changed Search Query Performance and opportunity explorer to denormalized and now what was a 360-day search volume? Take a look at this screenshot here 406,000. It was like a five to one difference. Almost you see how big of a difference that made it. When they went to the Dean uh, normalized. And so again, this is why I was thinking that hey, like, hey, every all these respected, you know executives in the industry, they know this stuff. I mean that was all over Amazon. Um, I’m sure they’ve got to know these things and we weren’t keeping, we were not hiding this.

Bradley Sutton:

I would just talk about this nonstop Episode 433 of this podcast. You’ll see I talked about the normalized versus denormalized Episode 435 of the podcast, episode 485. I actually had the Search Query Performance team from Amazon come on the podcast and they did a complete breakdown of what normalized versus denormalized meant. Even up to like a month ago I had Mansoor on the podcast he was talking about normalize versus denormalized in episode 584. So, this is not like some industry secret. All right, everybody should know what normalize versus denormalized means and that Helium 10 has always been based on the normalized.

Bradley Sutton:

Now you might ask me like which one is better? Now, that’s a subjective thing. Everybody can like their own kind of search volume. But for me I like the normalized searches better because to me that’s more of an indication of what I’m trying to get at. I want to, I’m trying to find out how many customers are searching for this product and the normalized will count that one, that search volume, as one, but the denormalized counts it as five or six, just because they’re clicking around on the browser. So, to me the more accurate number is the normalized search because you know it tells me hey, in this one instance there’s one customer who is looking for it, or there was 100 customers who are looking for it, whereas on the other one I’m not sure how many times somebody was clicking around. That number just is kind of inflated. So that’s why I personally like normalized. But hey, if somebody might have a use case for denormalized, I’m not sure what it would be, but let me know why you think that one might be better. Either way, you’re still going to be able to prioritize it’s. It shouldn’t be that far off. But yes, Search Query Performance is going to be different than Brand Analytics, Amazon versus Amazon data, even though it’s both from Amazon, because it’s normalized versus denormalized. That’s why the order is actually different, even when you’re comparing those two.

Bradley Sutton:

So again, that’s one of the reasons why I was getting so upset that they were all posting about this is because it’s not. We’re not even talking about comparing apples to apples. It’s kind of like in this post, everybody was jumping on the bandwagon and saying, hey, look at, Jungle Scout is a tangerine orange, very close to a blood orange, right, ooh, that’s very nice that they’re close. Great, you’re comparing an orange to an orange, good on you. But then they’re coming in and saying, oh, but look, Helium 10 is an apple or a Granny Smith apple. Look how far off it is from this blood navel orange. Like, why are we even comparing this Granny Smith apple? We’re not even trying to be an orange, or if there were Jungle Scout orange.

Bradley Sutton:

Anyways, where not even trying to be an orange, were just trying to be an apple that’s all were tying to do. So, why are you trying to bring us into this conversation about oranges, right. So, that was when I became so upset. But now, looks like, you know what, let’s go and let’s do a real test. You know like here, ah, I think we all agree that how bogus is this test that was done was and how useless it is. But like, all right, let’s go ahead and take Brand Analytics. Let’s compare that to Helium 10. Let’s take Search Query Performance, let’s compare it to Jungle Scout. And who has the most accurate search volume. Who has the most actionable search order.

Bradley Sutton:

So, what I did was I spent like much of the last 48 hours just like diving deep into their information. All right, I pulled in the Brand Analytics search frequency rank for 31 keywords that have to do with like coffin shelves and stuff. All right, I took the Search Query Performance from each week though the exact week that matched the Brand Analytics, and then, four weeks, I pulled out all of these keywords one by one, because I’m an idiot who doesn’t know how to use pivot tables and V lookups and stuff. So, I took these one by one, the search ones, because remember that one guy’s test was based on a number from July. I’m like, no, let’s make it apples to apples. Here’s Jungle Scouts number as of eight, 10, which is a full month number. Let’s take the eight, three to eight, 10 search rate performance. Let’s take the seven, 28 to eight, three. Let’s add up those four weeks and make it a month and let’s compare it. All right. So, I took all of that, I went in and I took all of the Jungle Scout numbers.

Bradley Sutton:

I went into Helium 10 and I took all of the magnet numbers for the search volume and I was like, all right, let’s go ahead, put this stuff to the test and then so let’s take a look, all right. So, first of all, why do I say, where did I get that 93.5 accuracy for Helium 10? Well, remember, there is no public search volume that you can compare one V one, the number of Helium 10, but what kind of normalized search do we have in Amazon that we can compare with Helium 10 Brand Analytics? So here, the first test I did was I took the Brand Analytics 31 keywords that have to do with coffin shelves and then I took Helium 10 and I got all the search volume of those same exact keywords. And then I sorted Brand Analytics keywords in the search frequency rank order, because that means you know the higher or the lower the number of search frequency rank, the more that it’s searched Right. And then I ordered the Helium 10 one in the order of descending search volume order and guess what? It was almost identical. The first 29 keywords was 100% the exact same order. Only on the 20 or the 30th keyword here did things, uh, get out of whack and two of them were flipped coffin pet bed and glass coffin. Helium 10 had in the wrong order compared to Amazon Brand Analytics. So that is a 93.5% accuracy. How cool is that? All right, only two off. So, can you trust Helium 10 search volume? Is Helium 10 accurate a hundred percent? Well, maybe not a hundred percent 93.5%, all right. So there that part of the story is done. Helium 10, 93.5% accuracy. If you’re comparing it to the only normalized data point we have, which is Brand Analytics.

Bradley Sutton:

Now what about Jungle Scout? With Jungle Scout, what I did was I took the all of the Search Query Performance for four weeks. Right, I took four exact weeks and added it all up, so we have a full 30 day or one month search volume number uh goth, uh 121,000. Uh, gothic decor a hundred thousand, so on and so forth. And then I took the Jungle Scout search volume from the tool, their 30-day search volume. So here in Jungle Scout you can see where I got that information of 83,903. This is the exact search volume 30 day for the keyword goth. And if I actually click on their details, I can see when that date was from, because the very last date that they have in the system is August 10th. Okay, so we are like on a apples to apples comparison here, because search group performance was also based on the week, the month ending October or August 10th.

Bradley Sutton:

And so, the first thing, remember Jungle Scout data dive. Everybody loves to compare. Jungle Scout is so accurate compared to a Search Query Performance. Let’s look at the raw number. Remember, spoiler, like I said before, like I don’t think the number is the most important thing, but if you guys are going to flaunt your uh accuracy, is that really true? Let’s take a look. If you compare the month search volume of Search Query Performance versus Jungle Scout, on average, look at this it’s 44% off, 46% off, 44% off, 71% off, 84% off. As a matter of fact, on average, it’s a total of 34.5% off. Okay, 34.5% off is the number, but what? What if you say, okay, forget about the search volume number? You know search volume, you know? Actually, I don’t think that 34.5% is that bad. If something has 10,000 searches and then it really has 7,000, is that the end of the day? You know, probably not right, but again, I’m just calling this out because they’re trying to say, oh, our numbers and our data shows that we’re 5% off. You know always. No, all right.

Bradley Sutton:

Now the other thing is remembered I said that search position, the order of search, is actually arguably more important than the search volume. So how off was Jungle Scout compared to Search Query Performance? The very first 11 keywords, Jungle Scout was 100% on, but then things got off the rail, and almost every other keyword was out of order. For example, coffin box was the 17th most searched term for Jungle Scout, but it was the 12th most searched term for Search Query Performance. And that is where I got the number of 41.9% accurate, because only 13 out of 31 had the right order of keywords 41.9%. How many did Helium 10 have when compared to Brand Analytics? 29 out of 31, which is the 93.5%. So again, whose search volume is more accurate between Data Dive and Jungle Scout and Helium 10? Helium 10 wins with 93.5% and Jungle Scout with 41.9%.

Bradley Sutton:

But then something was bothering me. Let me show you exactly what I mean. So, what was bothering me was when I looked at the Jungle Scout search volume history, I noticed that week by week, they actually had a weekly search volume, which I thought was actually pretty cool. I was like, oh, that’s nice, they give the exact search volume for 30 days, but then weekly. But then it didn’t add up. Like if you add up these last four weeks it does not add up on Gothic Decor to 68 000. Like wait a minute, this doesn’t make any sense. How can the week uh be different? I was thinking, oh, maybe, maybe you know it’s 28 days and so they need to. You know there’s two days extra and I couldn’t get it to like Jive.

Bradley Sutton:

But then I figured out what Jungle Scouts doing and they’re actually doing something similar to Helium 10. They’re actually basing their monthly search volume on a weekly velocity of the last day, the seven days, which is actually, actually, like I said, that’s what Helium 10 is doing and that’s good on Jungle Scout for figuring that out. That’s the best way to present it. But you know you might be confused if you might think that Jungle Scout was doing something weird in the numbers, because the monthly doesn’t add up to what the weekly is. But watch this. This is what I figured out. Look at, the very last week of this Gothic Decor keyword had 15,982. If we take 15,982 divided by seven days, and then we multiply that by 30 days seven days, right. And then we multiply that by 30 days, that is the number 68,494. And that’s what their exact search volume for the full month is.

Bradley Sutton:

So, then I thought, wait a minute, maybe I was shortchanging Jungle Scout on this. I was just taking their, their number at raw data, their exact 30-day number, and comparing it to 30-day Search Query Performance. But if the real number is the week search volume because that’s what it seems like they’re basing their whole month off, I should just be comparing apples to apples and compare their latest week to Search Query Performance, latest week, right, again, if they’re trying to be Search Query Performance, that would be a better comparison. So, I was like, oh, who knows, maybe the numbers are going to look better, did it? Let’s take a look.

Bradley Sutton:

The first thing that I tested was just the percentage off on the week. So again, I’m comparing the Jungle Scout super specific week number with the Search Query Performance week number and it was off 48%. It was 48% lower than Search Query Performance. I’m like, nope, no help there, this is actually worse. This actually made it worse Now that I got the real number because, remember, their month data, for whatever reason, was only off by 34%. This is off by 48%. So, then the next thing, I was like, okay, well, let me go and maybe the order is a little bit better. You know how? For from the, if I’m comparing the one week to the other week, is the order of the search volume at least better than before? Nope, 35.4% accuracy.

Bradley Sutton:

Jungle Scout and Data Dive versus Search Query Performance, even when you’re just comparing the week. So, no matter what way you spin this around, well, no matter what way you look at it, Jungle Scout and data diver just way off from Search Query Performance. Now, I don’t mean to sound like I’m exaggerating. I’ve said this a few times before. I don’t think numbers being far off is that big of a deal. Like, if you’re 30% off, you’re within the realm of possibility. But again, I’m bringing this out because, oh my God, do you know how many, how many blogs Jungle Scout has come out with saying oh, we are 5% more accurate than Helium 10, 11%. This is a big deal. And they’re making a big deal out of 11% or something which I don’t agree with those numbers in the first place. But even so, how can they be saying that when all their search volume numbers are literally 30% off and Helium 10 is 93% accurate? So anyways, guys, hope you guys stuck with me to the end.

Bradley Sutton:

I usually don’t get so worked up like this, but I used to argue on the internet all the time. That was how I got discovered at Helium 10 was. I would always go on Facebook groups and start arguing with people who had misinformation, and I I’ve kept to myself for a while, but I just this, this just latest uh episode just kind of upset me and I was just like I just want to set the record straight again. I don’t have anything personal against anybody involved in this this. You know people writing the blogs or the, or the people you know posting on LinkedIn and stuff. But it’s my advice to every you know people out there who are respecting you know like there are people you know I guess I’m one of them Like is it still kind of strange for me to think like that?

Bradley Sutton:

But if you’re a public figure in the Amazon world or any world, be careful what you post. You know, like be proud of your company. Nothing wrong with that. I mean you, you you’ve worked really hard to build up your company in the Amazon ecosystem. By all means, be proud of it. You know, um, I’m proud of my company.

Bradley Sutton:

Otherwise, why would I put a Helium 10 logo on my basketball court and do all the other crazy stuff? I do nothing wrong with being proud of your company, but don’t put out misinformation just to. You know, kind of like elevate your company, or I would hope that nobody even here is doing that purposely, but then the alternative if it wasn’t on purpose. It means that you’re just like not even fact-checking and not even making sure that you’re putting out the correct information, because you just want to, you know, hype yourselves up and try and throw Helium 10 to the bus. It doesn’t even have to be Helium 10.

Bradley Sutton:

I don’t care who we’re talking about. It could be Jungle Scout versus Data Dive or whatever comparison you’re going to do. Guys, just let’s keep it civilized. Talk about facts if you want to talk about facts, but don’t try and sensationalize certain things and paint the wrong picture, because people listen to those of us who have these kinds of platforms on the internet and they take our word at face value, and so that’s a heavy responsibility.

Bradley Sutton:

And I’m not saying to totally misrepresent the entire way that a company does things or misrepresent my own accuracy, you know, and just hope that nobody calls me out on it. But anyways, um hope you guys found this interesting because, like I said before, search volume is important and you got to know who you can trust, and I think it’s hands down. This has proven that. Hey, you are going to be able to trust Helium 10 with your search form, because we’ve got the most accurate out there at 93.5%. So, um, thank you guys for tuning in, and I’m going to do some other exposés now because I’m still riled up about some of these crazy blogs. It’s time to set the record straight. But hope you guys enjoyed this episode and we’ll see you in the next one.

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