TAS 429 How to Use Product Research Data to Confirm Good Product Selection (Coaching Call)

Do you ever find yourself looking over product research data, convinced that what you are seeing it too good to be true? Have you returned to that same product data a day or two later to find that it has changed significantly? You aren’t alone! On this episode of The Amazing Seller, you’ll hear from Scott and Chris as they breakdown data provided by a TAS follower like you! The guys go over the data, explain what they see, discuss reasons why the data may have changed, why the product is still a good investment, and so much more! You don’t want to miss out on this informative and helpful episode!

Why You Might See Conflicting Product Sales Numbers

When you are conducting your product research and looking at the sale numbers, you might see different results between searches. What is the cause of these different results? On this episode of The Amazing Seller, Scott and Chris go for a deep dive and examine all of the angles. The ensuing results may be caused by one seller opting for a more aggressive PPC campaign. Other variables include updates in the algorithm by the search engine. If you’d like to hear further explanations for these differences, make sure to listen to this episode as the guys expand on these ideas and more!

Don’t Forget to Double Check Your Numbers

If you come across product sales data that seems like an untapped gold mine, use caution and a healthy dose of skepticism! Ask yourself a few questions and consider doing the search again to make sure you are seeing the data correctly. On this episode of The Amazing Seller, Scott and Chris go over data supplied by a TAS follower like you. The guys go on to explain why it's important to not get your hopes up over a few pieces of data. Take the time to listen to the totality of this episode as both Scott and Chris take their time and walk through how to interpret search results. You don’t want to miss it!

Use the Same Keyword Search Phrase Every Time

As you build up your brand and expand in the ecommerce business realm, you no doubt, have come across helpful tips that have saved you valuable time and resources. Don’t brush past topics and steps you think you’ve covered before, take the time to slow down and pay attention to new tips that could make all the difference. On this episode of The Amazing Seller, Scott and Chris carefully go over product research data and give helpful tips that have the potential to save you time and money. The guys explain why using accurate search terms when conducting product research is vital to predictable results. Don’t miss this episode as they expand on these insights and much more!

OUTLINE OF THIS EPISODE OF THE AMAZING SELLER

  • [0:03] Scott’s introduction to this episode of the podcast!
  • [3:30] Scott and Chris dive into product data.
  • [8:30] Why is there a discrepancy with the sales numbers?
  • [11:00] If the data is too good to be true, make sure to double check.
  • [16:00] Make sure you use the same phrase every time you search for data!
  • [19:00] Scott gives a recap of what they’ve covered. 

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TRANSCRIPT TAS 429

TAS 429: How to Use Product Research Data to Confirm Good Product Selection (Coaching Call)

[INTRODUCTION]

[00:00:03] Scott: Well hey, hey what’s up everyone! Welcome back to another episode of The Amazing Seller Podcast. This is episode number 429 and today we're going to be talking about how to use…

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….product research data and confirming good product selection. I'm really excited about this episode because I'm going to be sharing with you an actual conversation that I have with Chris Shaffer and myself and we took one of our students and we took their question which was really about Jungle Scout's data. They actually pulled data on a product, probably around two weeks before they ran it again and then they seen a huge difference. So they asked us, “Well what do we do now because now the numbers are not the same?” We gave our thoughts on that.

But then we also drilled down to how to look at the history whether you're looking at the data once, twice, three times, it doesn't really matter because you want to go deeper that that anyway. Jungle scout is a great tool and that's the tool that we use. The extension is the main one that use and this is going to be using that example as well but this is actually two screenshots that one of our students actually pulled and we are actually covering this inside of the private label class room and I'm going to share that actual coaching session, that hot seat if you will that we recorded for inside of the class.

Now, I wanted to do this because I wanted you to actually hear the thought process and also give you a little bit of how we go and look at the history, the trends and we also look at those numbers because a lot of times people only look at the surface which is using Jungle Scout, which is great but you have to drill down deeper. Chris and I go really deep into this and I think you're going to get a lot out it. Now, I am going to be sharing with you if you wanted to download the actual video of this or if you're watching this right now, then you may be able to see the video.

[00:02:03] Scott: If not you can always head over to theanmazingseller.com/429 and you can grab the video, you can grab the screenshots, you can see exactly what we're talking about if you're listening to this. Whether it's audio version on the podcast then you won't be able to see what we're talking about. You'll be able to still get a ton of value from this but if you want to see the screenshots, the video and all of that stuff then you're going to want to go over to theamazingseller.com/429 and you can grab all that stuff over there. I think you're definitely going to want to do that.

The other thing is I want to give you the opportunity to join us on a workshop where I'm actually going to take you through these exact steps a little bit even deeper and outline the three different steps that we use by looking at the history, the trends and all of the product research that goes into it before deciding on that product.

That can be found at theamazingseller.com/workshop and we'll go ahead and we'll break that down for you in just about 90 minutes. Definitely go check that out for an upcoming workshop. Totally free but I wanted to just share that with you as well. So what do you say guys? Let's go ahead and dig in to this product research example of one product but two different sets of data that was received literally about two weeks apart. Sit back, relax and enjoy.

[HOT SEAT]

[00:03:27] Scott: All right. Chris are you ready to dig into some data here?

[00:03:33] Chris: Yeah, I am and it's interesting Scott. We got this question in the Facebook group and it's one of those things that until you've seen it, like you can think about it in theory but until you've seen it you might not really understand exactly why you and I do product research the way that we do product research. I think this example is a really good example of that. We are looking at the same product with screen shots taken, I believe it was a few days two weeks-ish apart.

I'd have to look at the actual email. It was a couple of days. Let's call it two weeks part. You can see that they look pretty different from one another. I wanted to dive in with you and see what the difference is and how we can avoid this as a trap. Like if we're only looking at the good one how can we avoid falling into a scenario where it goes from good to not so good as Andre put in the Facebook group.

[00:04:29] Scott: Yeah, again this is going out to Andre. Andre thank you for posting this. I had mentioned to you that Chris and I were going to dig into this and I wanted to share with the class because it's a good lesson and it's something worth going through and seeing this process and thinking out loud in a sense. But let me first just say that this is why this is a tool. This is a tool that brings in data and data changes.

It changes all the time but this is also a good example of find your products that you're doing some research on. Make the list, come back to those maybe in a week or even less and just keep looking at the data a little bit and seeing how it's changing. the other thing is, this is why it's important to also to cross reference and go over to camelcamelcamel or Keepea and look at the BSR, not just for that particular seller but just for that market or for those products over time.

Preferably for someone that's been selling for a consistent year, that's always a great. But if you can't then go to someone else that's selling that product that you might not even be tracking or a similar product and see what that product looks like or see what the BSR has done over the course of time. This is not where you're going to come in here and go okay this is exactly going to work because I seen the numbers on day one and these are rock solid. That's not what we're saying to do and that's what I don't want you to do. I want you to definitely do your research and give it a little bit of time.

In the meantime you're also going to be able to do your sourcing. Like if you're at this point, you might be doing your sourcing and in the meantime you can always come back to it. You haven't pulled the trigger yet. Does that make sense Chris?

[00:06:09] Chris: It does and one thing that I wanted to throw in there, we actually got asked another question similar to this in the Facebook group recently and it was like if I have Google Trends data and I have a little bit of the BSR history on it do I even need to come back and look at it again? Should I make that call? The reason that you and I talk about looking at products multiple times through the process is things can change. Amazon can shake up their algorithm, you may hit what you see in Google Trends as a little bit of a drop in overall search volume but it might be a big drop on Amazon.

It's some of those things if you look at it in throughout the entire process you can get a better idea. Seeing data at a glance is fantastic but seeing data in real time a lot of times helps us inform that decision even better.

[00:06:54] Scott: Yeah, absolutely. Let's just dig into this and I don't want to spend too too much time but I do want to just look at the differences here. Now, the one thing is Chris, let's try to compare the exact product and I think what I'm doing here is I'm trying to cross reference back and forth. Maybe you can see that better and we can look at that. Is the number two position the one that's $14.99 and $14.98, is that the same?

[00:07:21] Chris: Most likely. Again, we're only looking at the Jungle Scout screen shots so we can't see the product itself so there maybe a little bit different. But we can still get a good idea Scott of what's going on even if we can't compare one to one but number two is probably the same and it looks like number one and number three flip flopped. Let's just start probably by looking at those three.

[00:07:46] Scott: If we look at the one that we know as the obvious the $16.99 one, I'm going to guess that's probably the one that we can look at closely. It looks like in the first screenshot, the one on the left depending on what's being viewed here on our screen but this one here it looks like it said it was selling 3,000 units a month at 236 reviews. Then if we go to the other one which is more of the updated version, $16.99 it's saying it's only selling 957 and it has 261 reviews. That's probably the same product. So we're okay. Why would that drop 2,000 sales and that's where the numbers are off. So Chris what's your thoughts on that? What do you think that could be and at this point now what do you think as far as this product?

[00:08:43] Chris: The first thing for me is one Jungle Scout actually did update Jungle Scout between these two screenshots which means they rolled out some new algorithm, all that stuff. I don't think that's what we're seeing here. What we're actually seeing here and Scott you can see if like if we look at the $16.99 guy he's number one over here, he's number three over here, he's got a BSR of 856 versus a BSR of $15.67. He actually is selling less units and we know that. Now why that's happening, we're not necessarily sure of at a glance. We don't necessarily know exactly what's going on here but we do know that he's selling fewer units and that this guy $21.19 is selling more units.

He was $14.44, now he's $6.16. They did just flip flop in these Jungle Scout results. Now the other thing is there's just some people missing over there that we don't have prices and stuff on so we can't really compare down there but to me the one that he says is looking not so good, still looks pretty good with the exception this guy has got a handful of reviews in there. I think what may have happened is either the $21.19 did some sort of a launch is doing something or is just running more aggressive PPC and flip flopped those positions. Now the other thing you see in general is that the overall sales volume went down.

Now, we know what this product is. This is probably not a seasonality issue. Would you agree with that?

[00:10:15] Scott: I would, 100%.

[00:10:17] Chris: But there is still going to be seasonal trends and things. The very first thing that I would probably do is go to Google Trends and take a look to see if there's a reason for the overall drop. We know that it's not something like you just misread Jungle Scout or something like that because we can look at the BSR and the BSR is substantially lower for each of these than it was on the left over here.

[00:10:41] Scott: The one thing I want to say though. Even though looking at these like number one if you were going after a product that had 3,000 sales and then 2,000 sales and then 2,500 sales for the first three, that there is really, really high. Number one, I wouldn't think right out of the gate I found this huge home run and everyone else missed it or something like that. Because of that I don't think I would have gotten my hopes up on that. I would have been a little skeptical about that and I would have done some digging on that anyway. These numbers that came in that are more updated, that seems probably more realistic but that doesn't mean that maybe the algorithm is off a little bit or maybe it did a little bit of a change.

If I even I look back and I see these updated numbers, yes I would probably make me think like what happened but I still think they look good enough at the price point to say I can get to my ten units per day. It actually looks a little bit more realistic to me. With that all being said that doesn't mean that they just have updated it and it's somewhere in the middle. I think what I would do is I would look at those three that have the most sales and I would look at their history. That's what I would do.

[00:12:02] Chris: So Scott, here's  a question, looking at the data on the right, is this a product that you would look at even though it's lower volume than the screenshot on the left?

[00:12:12] Scott: I think I would. Here's why. I see the reviews which tells me kind of competition level and I don't think that that's that bad and then I look at some of these, yes some of them only have 233 and that's only $7.99. I'm looking at the ones that have $20 or even the $16.99 for that matter. I'm looking at those depending on what I can source it for and I'm saying there's a 957, there's 867, there's 616, there's 392, 284, 616. There's some there that have double the ten by ten by one. Now, does it meet the 3,000 if total up the ten, it's close.

But I think depending on the competition which I'm looking at the reviews, makes me say, yeah I would probably think about it and looking at the product that I know what the product is I would also find other things that could go along with this or that people are searching for that could be related because there are some other things that could go with this that they would buy most frequently bought together.

[00:13:18] Chris: I think the other thing that really sticks out to me Scott and guys, we're looking at the one on the right here is. This guy 957 listing quality score of three, 392 listing quality score of three, 233, three, 284 three. All of these guys are under optimized and so a lot of these things play a role but we're just looking at the sales, the price and the reviews at a high level but to me this wouldn't necessarily deter me. The other thing that maybe going on here and it's one of the problems that you can run into if you just look at Jungle Scout one time or if you don't dig a little further into the data is Jungle Scout calculates the sales based on the rank in whatever category the product is listed in.

To me this is a product that can be listed in multiple categories. You may see some monkeying around of the numbers due to that as well and that's why it's important to come back and spot check these things to make sure that you're looking at things in a relative way, does that make sense?

[00:14:20] Scott: It totally does. The other thing I want to say here, if you look further down and you get into position number 18 and there's 867 sales with 204 reviews like let's look at that one. Why is that one selling, it is the same thing, it probably is. That gives me hope maybe I can go ahead and sell this product or like I said, knowing the product there's things that can go along with this that you're probably going to need to use the product. Because of that that gives me even better hope that I can probably find some other things even just little accessories or whatever that can go along with it that this person looking for this is going to need.

Again, it's one of those things that there's not a lot of reviews. If you look all up and down, all of those reviews, the most is 261. All the rest are under that and some of them are in just double digits. I think I would again reevaluate the numbers and then look at the trends, look at the history, whether that's in Keepa, whether that's in CamelCamelCamlel. Look at Google Trends and then go from there. This is definitely along the lines of Chris, wouldn't you agree that this is a non sexy product?

[00:15:39] Chris: It's definitely a non sexy product.

[00:15:41] Scott: But it's a product that people would want and need so…

[00:15:47] Chris: It definitely has some potential to build multiple product brand even if it's not a brand in the way that we typically talk about it. You can build a good product line of complementary things with this. I just bought new ones so I would know. It's one of those things. I think Scott one last thing that I wanted to touch on here if you do come back and you should come back and look at Jungle Scout data at different times, make sure you're using the same exact search. Amazon treats every search individually and so things are going to change, things are going to move around a little bit but if you type in garlic press and you type in stainless steel garlic press you're going to get two different sets of search results.

Capitals can even make a difference in some cases. If you have like a spreadsheet or you're tracking all this stuff, just copy and paste it. That way you don't have to worry about adding a work, misspelling it, maybe use the soda versus pop thing. You don't have to worry about looking at slightly different data so that you're comparing apples to apples and not apples to cranberries. There are different keywords that can describe all of these products that we are looking at and if we use a slightly different keywords then we're going to get different data back. That's why we always want to use a try to look for Scott that main keyword phrase so garlic press.

We want to just try to describe the product in the most generic way possible without not describing the product, if that makes sense. It doesn't necessarily need adjectives, it doesn't necessarily need any of those… Don't search it with a color, search it at the head portion of whatever describes the product. You're trying to sell a garlic press, search just for garlic press and see what those result come back with.

[00:17:31] Scott: One last thing before we wrap up is I want to say like on the new Jungle Scout that you are sharing here, with us the listing quality score, the LQS I think that's really important to look at and in this example if you're looking at number three, the $16.99 one the one that's getting a lot of sales, at 157 sales, it's giving it a quality score of just like three. So like that's pretty good to be able to actually say, “Wow, I can actually make this listing better because maybe it only has maybe one picture. Maybe it's really crappy. Maybe it has like only three words in the title.

Maybe it has only one bullet. There's a lot of things that you can improve there. That gives me hope that I might be able to take position number three. That's kind of exciting looking at that and only 261 reviews is not that competitive in my eyes. It's to the top of where I want to be but knowing all the other ones that are under that, really good. There's a lot of listings here. Even the number five position at $20, 392 sales. Another three listing quality. I would look at those and see where you're going to be able to improve that. The big question though Chris and let's just wrap this up, the big question was there's new data. What should I do with it?

It's way off. I think it could be an algorithm update a little bit or it could just be again be maybe the sales have dropped and now we know that. But I would then look at the history but regardless looking at the new shot with even the new numbers even if you just went off of that and if they were halfway in between what the other numbers were, you're still in a good place in my eyes. Seeing the listing quality score, that also gives me even more hope that I can do a better job and probably rank pretty well. I think that's it. Chris, are you good? Is everything good?

[00:19:24] Chris: Yeah. I think that about wraps it up.

[00:19:25] Scott: Cool. So Andre hopefully this helped you or anyone else that's watching this inside of the class and keep submitting these. I can't say we can do this for all of them but we will pick some and randomly do these. Then this way we can give back and share with you the thought process that we go through. Guys, stay connected in the group, and TAS Breakthrough U and we'll see you soon. Take care.

All right. There you go. I think you can see that there's a lot more that goes into looking at the numbers than just looking at the numbers. You actually have to look deeper and not just count on those numbers that Jungle Scout or any other tool is giving you and I think once you understand that process then it opens up a lot more doors for you and also it protects you further from just looking at the surface numbers. So once again, if you guys are listening to this and not watching this, if you're listening to this on the podcast, head over to theamazingseller.com/429. Grab the show notes, the transcript.

I'll have screenshots of the two examples that we were using that will also be a screen share video that you can watch and all the resources will be there for you. I'll also remind you one more time about the workshop, we do a 90 minute workshop where we breakdown the three parts, the three huge parts of really going through the product research stage and really helping you find those products but then also going in and digging deeper, looking at the history, looking at the trends and really seeing a bigger picture than just the surface numbers but we have to start somewhere and that is with looking at the data once you get to pull those numbers using a tool like Jungle Scout.

Then the last thing I should probably mention is that if you guys are at all interested in trying Jungle Scout which again is my tool of choice I do have a discount for all of our TAS listeners and you can go check that out. There's also a few additional resources there if you go through my affiliate link and yes this is an affiliate link, you will buy me a cup of coffee so I'm totally transparent there with you.

[00:21:33] Scott: But if you want to go check that out and get that discount and those extra resources head over to theamazingseller.com/js and you can do that. Guys that's it. That's going to wrap it up. Hopefully you enjoyed this and I look forward to seeing you on a workshop or I'll just see you around and as always, remember that I am here for you, I believe in you and I am certainly rooting for you but you have to, you have to… Come on say it with me, say it loud, say it proud, “Take action.” Have an awesome amazing day and I'll see you right back here on the next episode.

[END]

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3 comments
  • Hello Scott,
    Have you ever tested Jungle Scout accuracy on your own Amazon listings or your member’s products?
    I wonder how accurate JS is? I wonder if you can say: it’s 85 or 90% accuracy?
    Thanks for your comment in advance

    Cheers,
    Damian

    • Hey Damian, I look often in respect to my own listings and it tends to be pretty close, when it’s off it also tends to estimate LOW, which is a good thing! I’d rather luck out and get more sales than I expect after launching a product than fewer than I expect.

  • Hello Scott
    Thanks to you and the great TAS Community on facebook i finally took action and ordered my first product.
    While preparing the launch phase i stumpled over the topic of chinese sellers listing their products directly on Amazon.
    I think this has the potential of changing the Business in a way that will make it hard for us to compeed against.
    What would be the best stragety to prepare for that, besides building a brand – which can not be copied that easy?
    There was a discussion on the TAS Facebook page, but nobody really knew how to prepare.

    Thanks and best regards from germany to the U.S and the TAS Community.

    Jonas

    • Hey Jonas, first it’s important to remember that most chinese companies would never do that, it’s not their business model. Factories like to wholesale and generally don’t sell in retail marketplaces, there will be some competiton from all over the place but it’s honestly not something I would worry about, focus on what you can control and build a great brand and experience and you’ll be just fine!

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