Dispelling Myths: Sales Velocity (Follow the Data Ep. 4)

Follow the Data Episode 4: Sales Velocity

Keep increasing your sales, and Amazon will reward you with a coveted spot on page 1. Sounds like a simple formula, but the facts say there are other factors in play. Join Viral Launch CEO Casey Gauss and Cameron Yoder for episode 2 of “Dispelling Myths” to find out why sales history, not sales velocity, is the key to maintaining high rank on Amazon.


Listen on iTunes . See All Episodes

Listen on Stitcher / Listen on Google Play


Follow the Data Show Notes

  • We’ve been busting myths since Day 1, and the misunderstanding of BSR is one we’ve been embattled with for some time. Check it out our Amazon BSR Myths blog post from December 2016.
  • If you’re just starting out as an Amazon Seller and feeling lost trying to figure out how sales velocity, sales history, ranking, and promotions all work, check out our 3 Keys to Success seller guide.
  • Here at Viral Launch, we’re just crazy about sales history. Not only is it important to maintaining rank, it is also a great indicator for how a product will perform in the future. Market Intelligence shows up to two years of sales history for a product market so you can make realistic projections about future sales. Sign up for a free Viral Launch account to get a free trial of Market Intelligence.
  • Want to be on the show? Leave us a voicemail at (317) 721-6590


Podcast Transcript

Casey Gauss:

Do not focus on BSR. Forget it. Only pay attention to ranking. And then really focus on building a strong sales history. Don’t go in and just give away a product over 5 days just because you want to improve your velocity and you think it’s that is going to help you maintain rank and the drive organic sales from there. Really, you need to focus on building up your average per day sales history.

Casey Gauss:

No one can find your product when it’s buried at the bottom of page 10 search results.  To climb in the rankings and capture more traffic you need sales.

Cameron Yoder:

But are all sales created equal?  I’m Cameron Yoder.

Casey Gauss:

And I’m Casey Gauss, your host for Follow the Data: Your Journey to Amazon FBA Success.  In this show we leverage the data we’ve accumulated at Viral Launch from over 20,000 product launches and our experience working with over 5500 brands on Amazon to help you understand the big picture when it comes to Amazon, and most importantly, what it takes to have success.

Cameron Yoder:

These first four inaugural episodes of Follow the Data are all part of our Dispelling Myths series in which we explore topics that have garnered a lot of conversation among the Amazon seller community but have not been proven or disproven using factual evidence.

Casey Gauss:

We’ll talk about why these Amazon theories make sense, where they’ve come from and what the data is saying about what is actually happening.

Cameron Yoder:

Casey, can you define – can you define sales velocity for us?

Casey Gauss:

Yeah, yeah.  So sales velocity is the rate at which you are selling.  It’s simple as that.  You know, one thing is, I think it probably just sounds like a cool term so people want to throw it around.

Cameron Yoder:


Casey Gauss:

Which, which, you know, I don’t blame them.

Cameron Yoder:

That’s pretty cool.

Casey Gauss:

Yeah.  Basically sales velocity is this myth that if your sales continue to increase, then Amazon will favor you with good keyword ranking.  You know, as an example, people like to set up promotions where they’re incrementally increasing because it shows that their velocity is increasing, and they think that that is what Amazon likes to see because, you know, to them it looks more organic, and they think that Amazon wants to see things that are more organic.  Also, you know, pretty much on any website or service provider’s website you’ll find the term sales velocity on there, and they are trying to tell you that it’s sales velocity Amazon cares about when it comes to keyword ranking, and it’s just not true.

Cameron Yoder:

If it’s not sales velocity, what is it?

Casey Gauss:

Yeah, it is sales history.  So it sounds –

Cameron Yoder:


Casey Gauss:

Yeah, not as cool of a term, but it’s a lot more accurate in how Amazon looks at your sales and then decides how to rank your products based on, yeah, sales.  One thing that we do kind of want to point out here is, you know, this myth we’ve been trying to kill it forever, and that is just BSR, the myth of BSR.  So essentially what BSR is is BSR is like a report card.  It’s basically an indicator of past sales, much like in a report card where you do some work and then your teacher grades it, and then you get a letter grade post-work, saying how well or how much work you did.  And so the same is true with BSR.  If I sell 100 units it will impact my BSR, but my BSR does not impact my bestseller rank, does not impact my future sales.  So please never try to improve your BSR.  Try to improve your sales, and then yes, of course, your BSR will improve from there, but yeah.

Cameron Yoder:

Hey guys, Cam here. I just want to break and clarify something that is–in a lot of ways–so obvious for us here at Viral Launch that we often forget to say it explicitly, and that is that BSR is not the key to visibility on Amazon. Keyword ranking is. You might have a great BSR but if you aren’t getting sales through a keyword, you aren’t going to gain keyword ranking which is how shoppers will find you in search. Got it? Not BSR, keyword ranking. Okay, now back to the show.

Casey Gauss:

You know, I think the analogy is as simple as this.  So if I’m standing on the Earth’s surface, to me it appears flat, right?  But when I take that 10,000-foot view, or that mile view, or however high you need to be to really start to see the curvature of the earth, you’re really able to get a different perspective.  You’re able to – you get in more data and are able to really start to understand, hey, it’s not actually sales velocity.  It’s actually sales history.  The perspective that we have of the space running hundreds and hundreds of promotions daily, we’re able in tracking keyword ranking for many keywords that are found in the listing or the targeted keywords.  We’re able to really get a great perspective of what is Amazon paying attention to when it comes to sales history or sales in general and driving keyword ranking.

Cameron Yoder:

All right, so we’ve talked a little bit about, again, defining sales velocity and defining sales history, and taking a look at what the myth is saying and what other people are saying.  But let’s jump into the data.  What – Casey, what have we found when it comes to sales history?

Casey Gauss:

Yeah, so both from the data that we’ve been able to aggregate, as well as indirectly from Amazon, we know that Amazon is actually tracking sales in these buckets, right?  So they’re tracking what does the average per day sales look like over the last 24 hours, 48 hours, three days, five days, and then in these seven-day increments, out until, you know I don’t know how long, but I know it’s at least 180 days.  Basically what that shows us is yes, Amazon cares about most recent sales, or they more heavily weight recent sales, which is where people are coming with the sales velocity, right?  So if your velocity is good then your most recent sales history is good.  So maybe the last day, maybe the last five days, who knows?  What the sales velocity kind of algorithm doesn’t take into account is history, which Amazon is definitely heavily weighting.

Cameron Yoder:


Casey Gauss:

So I can give a couple of examples of some promotions that we’ve run, which then give us insight into the sales history.

Cameron Yoder:

Go for it.

Casey Gauss:

Yeah, so, so many people have run these promotions – and it’s pretty common knowledge, I’d like to think – right now where you can’t just run a one-day promotion.  Back in, you know, 2014 you could do that.  Running a one-day promotion, a big spike in sales would help to improve your keyword ranking, but Amazon is more – more so heavily weighting sales history where if I run a one-day promotion, yes, my velocity is good.  My BSR is going to increase quite significantly.  But when Amazon goes to calculate your seven-day sales history or your 30-day sales history, it just doesn’t match up to those guys that are ranking page 1 and have been for the last six months.  Their sales history is very solid for that particular market.  So what we’ll see is maybe you’ll get a decent blip, but usually with a one-day promotion you won’t even get that nice blip anymore because there is no sales history to back it up.  What we do see if you run a 3 to 5 day promotion is generally you will get ranking because you have your most recent sales history is good.  But then it’s very short-lived because you don’t have enough sales history.  You don’t have, you know, 90-day sales history to help rank among those guys that are selling, or have been selling, again, for six months.  So we see those guys fall right back down.  

And what happens if you run a 7-day promotion and don’t see any sales right off the bat?  We see ranking sustained a bit further simply because yes, the sales velocity may end up being very bad after we’d run a 7-day promotion giving away 50 units per day, and then there is another three days after that where there are no sales at all.  Let’s just say, you know, they have terrible images, they have terrible reviews, they just don’t convert at all.  What we’ll see is that product will maintain rank for at least a little bit depending on the market, sometimes longer, sometimes indefinitely.  It really depends.  But for the majority of the time – and this is where having so much data, so much perspective really helps to reinforce these correlations or these trends, but this person will generally maintain rank for at least a week, or sometimes a lot longer, because they’ve built up that sales history.  So the more sales history they establish, the longer that rank will maintain even though their velocity is really bad because they’re not selling anymore.  Their rank will maintain because their sales history is actually pretty decent.  

A case study kind of on the other side is in terms of maximizing ranking, is we had a seller in a very, very competition-heavy beauty niche, right?  And so they’re giving away 100 units a day at a promotion, promotional price.  They’re also selling organically.  But after – it took them 30 days to get to position number three, or sorry, position number four.  This is a pretty brand-new product, and they’re maintaining this position, but they’re not increasing just by giving away 100 units a day.  Their BSR was better, so you know, assumedly their velocity was much better than the guys ranking ahead of them.  And so anyways, what they had to do was they had to start giving away 125 units a day, and they did that for another 15 days, which put them to position two.  But even still this guy in position one had probably been ranking for at least the last, you know, six months or so.  And so over the last six months, you know, he’s built up a really, really solid sales history.  And so it’s very difficult for this newer product that when Amazon is going and calculating the 90-day sales history, maybe 180-day sales history, you know they just don’t have any sales because it’s a brand-new product.  And so they’re not able to compete.  And so it took this guy 60 days of giving away – 30 days at 100 units a day, another 30 days at 125 units a day on top of now at this point they’re selling really well organically.  It took them that long in order to be able to outrank this guy in first position because the guy in first position had such a strong sales history.

Rebecca Longenecker:

Are you looking to launch a product but feeling overwhelmed and frustrated by how complicated the process seems?  Giving away inventory can be nerve-racking.  That’s why Viral Launch offers free coaching.  Talk to one of our trained Amazon seller coaches and create a custom launch strategy.  Don’t have time to talk with a coach?  Check out our How to Launch course on the Viral Launch YouTube channel.  You can have a coach walk you through the whole process at your convenience and with the option to play back all the information.

Cameron Yoder:

To summarize – and correct me if I’m wrong, Casey – but to summarize, if you have a longer history of sales with and for your product it will carry more ranking weight than sales for a product with a shorter history, right?  So longer history carries more ranking weight than shorter history when it comes to sales?

Casey Gauss:

Agreed.  At the same time, though, that’s not to say that, you know, if I’m giving away 100 units I would definitely put those 100, depending on the market, I would put those 100 units over 10 days or five days, depending on how competitive the market is.  But you know, if you’re giving away 10 units I would probably rather give away those 10 units over three days than 10 days because it’s not really going to – when Amazon is calculating your average per day sales, you know, one unit a day is not really going to be enough to move the lever.

Cameron Yoder:

Right.  You have to have – well you don’t have to, but it is more effective and efficient to have the combination of the right strategy for sales velocity combined with the presence of a sales history.

Casey Gauss:

Yeah, correct.  And you know, another example, or another almost anecdote is basically – so it’s definitely more difficult for us to rank products that have been on page 10, or you know, not selling very well for, you know, a couple years.  So products that were launched maybe in 2014, off to some initial success and now not doing so well, those products are definitely more difficult for us to rank.  And the reason being is they’ve actually built up a really poor sales history.  And so when Amazon is going and calculating the 180-day average, maybe they’re looking out to a year, maybe further.  It is definitely, you know, when Amazon goes and calculates, oh, you know, you’ve sold 1000 units over the last year, the average per day sales history is very, very poor.  

Even if your velocity is killer right now, Amazon is definitely looking at your sales history.  So maybe you’ve sold 1000 units in the last, you know, 10 days, right?  100 units a day.  That’s really awesome.  Of course, depending on your market.  But that’s really great.  But even still, Amazon is still looking at oh, how have you done over the last 30 days, 60 days, 90 days, year?  And so it just doesn’t compute, and what we see is those guys end up losing their keyword ranking much more quickly, simply because, you know, they don’t have the sales history to compete against those on page 1.

Cameron Yoder:

Right.  So launching – we talked a little bit about launching and what it takes to get to the top of page 1 for a pretty volatile or competitive market, right?  How even if you have a history of a lot of sales or a history of not too many sales, it takes a decent amount of units to get to page 1.  But talk about – talk about less volatile or less competitive markets when it comes to sales history.

Casey Gauss:

Yeah, so sales history is all relative to the market that you’re looking to enter, right?  So if you’re entering a really niche market where these guys are selling page 1, you know, top of page 1 on average.  They’re selling 300 units a month, let’s say, so that’s 10 units a day.  So you only need to build a sales history of 10 units a day.  So you don’t need to be nearly as aggressive as the guys that are selling 30,000 units a month.  It requires the same strategy, right?  Like the same metrics are involved.  The same math is involved on Amazon’s algorithm.  So you just have to put the right numbers in.  It may be a giveaway of seven units a day for 10 days at a promotional price to maintain that rank or to build a good enough sales history to maintain that rank.  Of course you need to sell well organically post-launch in order to continue –

Cameron Yoder:

Right, to maintain.

Casey Gauss:

– to build sales history so that you can continue to maintain that rank.

Cameron Yoder:

Like you said, it’s relative to the market at hand.

Casey Gauss:


Cameron Yoder:

Completely.  So the big takeaway, what is our – what is our audience’s takeaway, Casey?

Casey Gauss:

Two things.  One, do not focus on BSR.  Forget it.  Only pay attention to ranking.  And then two, really focus on building a strong sales history.  Don’t go in and just give away product over five days just because you want to improve your velocity and you think it’s that velocity that is going to help you maintain rank and then drive organic sales from there.  Really you need to focus on building up your average per day sales history.  And so if you have older products, you know, there’s some great ways of relaunching those products within Amazon’s terms of service.  Please don’t violate Amazon’s terms of service.  We’re never advocates for that.

Cameron Yoder:

Right, right.

Casey Gauss:

But maybe you should find a way to couple it with some additional product that you throw into the packaging or something so that you can relaunch that ASIN, if you’re trying to revive an old ASIN, just because it has, you know, such a bad sales history.  The tough part is, you know, if you have a great review quantity relative to the market then you have to figure that out.  But anyways, please focus on building that sales history, not sales velocity.

Cameron Yoder:

I am an advocate for the mentality, in this case especially, that it is a marathon, and it’s not a sprint.  Gain that sales history.

Well hey, that’s all for this week.  Thank you so much for joining us on Follow the Data.  For more reliable information about what’s really happening on Amazon, subscribe to our podcast and check out the Viral Launch blog at Viral-Launch.com.

Casey Gauss:

And don’t forget to leave us a review on iTunes.  Please, please.

Cameron Yoder:


Casey Gauss:

If you like the podcast, of course.  If you didn’t, please let us know how we can improve it.  

Casey Gauss:

We like honest feedback, so please send us your honest feedback. If you want to be featured on the show leave us a voicemail and tell us your thoughts on today’s episode and/or any questions you have about Amazon Viral Launch or, you know, life in general.  We’ll take them all.

Cameron Yoder:

We’d love to hear your life advice, please.

Casey Gauss:

Our number is 317-721-6590.  Join us next week as we dispel the myth of diversification.

Cameron Yoder:


Casey Gauss:

Until then, remember the data is out there.


About the Amazon FBA Seller Podcast:

Viral Launch CEO, Casey Gauss, and Amazon Seller Coach Cameron Yoder bring data-driven insights to the Seller community in their weekly discussions. 

On the show you’ll get the latest Amazon selling strategies and best practices based on the company’s experience launching over 22,000 products and working with over 5,500 brands. Casey and Cam will bring you up to speed on the latest Amazon news, share stories of success and failure, explore the difficulties of entrepreneurship, and discuss the way Amazon is changing retail. 

At the center of the show is the Viral Launch commitment to offering reliable information to today’s entrepreneurs.

Amazon Best Sellers Rank (BSR): Definitive Guide

At Viral Launch, we thrive on understanding and discovering the intricacies and science of the Amazon marketplace. Because the more we understand about Amazon the better equipped we are to map out the process of selling successfully for you. One of our targets was to reverse engineer the Amazon Best Sellers Rank (BSR) algorithm.

The intent was to build an incredibly robust Amazon sales estimation algorithm with unprecedented accuracy. While we have built a far more accurate BSR-to-sales mapping algorithm than what is currently available, reverse engineering the Amazon Best Sellers Rank algorithm requires a far greater amount of data and sophisticated machine learning tactics.

Here are our findings on BSR and the downfalls of using Amazon’s Best Sellers Rank as a tool to estimate sales. 

 What is Amazon’s Best Sellers Rank?

A product’s Best Sellers Rank can be found on the product’s detail page. As you can see, products are typically listed in multiple product categories. There is usually a top level category: in this example it is #71 in Beauty & Personal Care. And there is a subcategory: this product is the #1 best seller in the sub category, Serums.

Often you’ll find a product in multiple subcategories and, somewhat less frequently, in multiple top level categories. For sales estimation equations, it is the top level category that the algorithms pay attention to. If someone had enough data to map out the current 64,000+ subcategories, they might use those numbers. But at the moment, that seems unlikely.

How is the Amazon’s Best Sellers Rank (BSR) Calculated?

The “best selling” product in a category has a BSR of #1 in that category. The second “best selling” product in a category has a BSR of #2 in that category. Amazon calculates a product’s Best Sellers Rank or BSR by considering the number of orders for that product compared to other products in the same category within a given amount of time. 

We tried to figure out the time frame in which orders are taken into account using a few different machine learning algorithms. We wanted to know how much weight Amazon was placing on various timeframes. The most successful of these algorithms was Linear Regression. 

[PRO INSIGHT: We also tried Decision Forest Regression, Bayesian Linear Regression, and Boosted Decision Tree Regression algorithms] Generally, with this kind of dataset, we would expect to use Linear Regression to help us understand how Amazon weights sales each hour. For example, using Linear Regression, we can determine that sales today are more heavily weighted than sales a year ago when calculating BSR.

To briefly explain how Linear Regression helped us reverse engineer the BSR equation, let’s break it down. Linear Regression is an AI equation that finds the proper coefficients for an equation by sorting through massive amounts of data. The equation looks something like BSR = X(a)+ Y(b) + Z(c)….. and so and and so forth.

Variables a, b, and c are the numbers of orders for each period of time, and X, Y, and Z are the amounts each period of time is weighted. For example, sales over the last hour (a) are worth 40% of the BSR calculation (X) and sales two hours ago (b) are worth 20% of the BSR calculation (Y).

Unfortunately, this approach did not return the exact calculation we were looking for. But it did help us uncover some great insights. 

What We Discovered About BSR

Though BSR has been difficult to work with, through trial, error, and analysis of massive amounts of data, we definitely learned a lot! Some of these are not new discoveries, but for those unfamiliar here you go:

  • BSR updates for a product within 2-3 hours of a sale (we assume depending on when the payment clears relative to Amazon updating the market’s BSR).
  • The BSR calculation more heavily weights recent sales.
  • Historical sales still hold considerable weight in the calculation.
  • We’ve seen two products with near identical BSRs have different sales by a couple of hundred during the last month. (Ex. BSR #76,430 and #76,433 with monthly sales of 94 and 310 monthly sales respectively).
  • We’ve seen products with much lower BSRs with far fewer sales (Ex. BSR #720 at 366 sales over the last month.).
  • New items with no sales do not have an Amazon Best Sellers Rank.
  • When it comes to listing variations, some types of variations do not have their own BSR. Instead sales roll up to the parent ASIN. Other variation types do have their own Best Sellers Rank.
  • BSR is order dependent and unit independent. (e.g. 90 items in a single order has as much impact as an order for 1 unit).
  • BSR can swing by tens, even hundreds of thousands in the lower ranks with a single sale. Likewise, BSR can plummet just as fast (we’ve seen drops of 10,000 per hour until another sale occurs).
  • BSR is re-calculated every hour for every product. We’ve never seen two products with the same BSR in the same hour.. so you can’t just re-calculate the top X products each hour as some people suggest.

So as you can see, BSR can be both an indicator of how well a product has sold in the past and an indicator of how well it has sold over the last few hours. The problem is you can’t tell exactly which unless you have detailed BSR history. Becuase BSR fluctuates so drastically and frequently, it’s almost impossible to determine anything from a product’s BSR at a single given moment.

An Example of BSR Fluctuations

Let’s take Product A and Product B. Product A has been selling steadily at 40 units per day in the Patio, Lawn, and Garden department for the last 6 months and Product B has only ever had 1 sale which was 31 days ago.

Let’s say that Product B get’s their stuff together and starts really promoting their product. Let’s say it sells 120 units total over the last two days. We would expect Product B to have a very similar BSR to Product A even though Product B has only sold 120 units over the last 30 days and Product A has sold 1,200.

Pretty crazy huh?

Different Ranks But Same Sales

With there being millions of products per category it is very possible for two ASINs to have the same number of sales but have very different BSRs.

Let’s say that Product A  has had 197 sales and Product B has had 200 sales over the last 30 days and their BSR is sitting at 12,000 and 10,0000 respectively. 

Okay, now let’s say that Product A had three sales in the last three hours, while product B has had none. We would expect Product A to be ranking somewhere in the 8,000’s even though they have had the same number of sales over the last month. 

Timing Is Everything

Product A has only ever had 2 sales on Amazon, and they both occurred 18 months ago. The product is now sitting with a BSR in Patio, Lawn, & Garden of #2,000,000. Product B on the other hand has only had 1 sale, but that sale occurred 12 months ago. Because Product B had a sale more recently than Product A, we would expect its BSR to be something like #1,000,000.

Even though Product A has had more sales, those sales happened earlier and reached “the bottom” of the BSR calculation, while Product B didn’t hit “the bottom” of the BSR calculation until much later. As BSR updates each hour, products that don’t report a sale generally get pushed down the ranks (increasing in BSR), and products that have a sale rise above.

BSR Is Bad For Sales Estimation (But It’s The Best We Have)

In our journey of crafting the most accurate sales estimation algorithm, we brainstormed all possible indicators of sales on Amazon’s platform. One thought was estimating sales based on an assumed average review rate per market, which would look something like this: if an average of 25 reviews were added per product in a month, and we assume review rate is 1% of organic sales then we would assume there were 2,500 sales that month.

This is obviously not the proper approach. But in brainstorming, no idea is a bad idea. The most popular alternative is tracking inventory levels, which has some major weaknesses. This approach does not allow for situations in which sellers are driving sales from external sources as well as listings whose inventory levels are above 999 units, or listings where the Max Order Quantity is set.

You may be wondering why we were so turned off by the way existing tools use BSR. Essentially, we were opposed to using the Best Seller Rank because it is such a volatile metric. BSR is globally updated per hour meaning each product’s Best Sellers Rank is calculated and adjusted each hour.

Each time Amazon pushes a BSR update, a given product’s rank can fluctuate dramatically. For example, we watched a product’s Best Seller Rank jump from 98,000 to 38,000 in one hour due to one sale. Then in the next hour it fell back down to 76,000. This drastic fluctuation is happening across the marketplace all the time.

Moving forward, let’s call the Amazon best sellers rank that you find on Amazon a “snapshot” (because it is just a snapshot in time as BSR changes hourly).

Let’s walk through an example of how snapshot BSR is a poor metric for estimating sales volume. Imagine you are wanting to source a tea kettle. When are people most likely to remember that they need to purchase a new tea kettle? Probably, most people remember to purchase a new tea kettle in the morning when they have their morning tea/coffee before work. That means, that BSRs for tea kettles are likely going to be lower (showing higher sales estimates) in the morning than at night.

So, if you do your sourcing research in the mornings, you are going to estimate higher sales volume than if you do your research at night. The same can be true for times of the week. Let’s say for example’s sake that half of tea/coffee drinkers only drink tea/coffee on work days to get some extra pep in their step on the way to work. That would mean that BSR/sales figures are going to be different when looking over the weekends versus weekdays.

Essentially because there is no direct calculation and because Amazon Best Sellers Rank can fluctuate so drastically within the scope of a day, week, and/or month, the Amazon Best Seller Rank is a poor indicator of past sales.

How We Built Our Sales Estimation Algorithm With This Knowledge

We don’t feel comfortable sharing too many specifics, but here are a couple of key aspects that allow us to have an incredibly accurate estimation algorithm in our Amazon product research tool.

As you can see, the Amazon Best Sellers Rank can be extremely volatile hour to hour, day to day, and week to week. So in order to build a sales estimation tool with any degree of accuracy, we had to build a tool that was going to take into account the vast fluctuations in BSR that occur all month, and we’ve done just that.

Using a snapshot of BSR to estimate the number of sales over the last month is like trying to predict the plot of a movie based on a single still frame. It can be extremely inaccurate. One feature of our algorithm that I would like to highlight is that we continually update our BSR-to-sales mapping algorithm each night.

Nightly updates allows our calculation to remain consistent with the natural trends of the market. Due to seasonal trends across Amazon, as well as Amazon’s increasing popularity, estimation tools that do not refresh their algorithm regularly will find their estimations quickly becoming stale and continuing to decrease in accuracy as time goes on.

See just how accurate our sales estimates are with a free trial of Market Intelligence!


Busting Myths: Amazon Best Seller Rank (BSR)

Your Amazon Best Seller Rank  does not help you drive future organic sales, in the same way that a report card from a previous semester does not impact your grades in a new semester. It is only an indication of the past.”

In an effort to continue expanding our capacity for helping Amazon private label sellers solve their problems, achieve success, and increase profitability, we spend a good amount of time engrossed in a plethora of conversations across the various FBA/Private Label centered Facebook groups. As we’ve mentioned before, this is the true breeding ground for rumors, misinformation and miscommunication. It can get ugly. For young, novice sellers still trying to understand how to navigate the space, listening to rumors can lead to costly mistakes and sometimes even financial ruin (literally). We’ve seen it plenty of times. It’s terrible, unfortunately, and becoming more and more common!

As a company that cares deeply for people and enjoys watching/helping people succeed, rumors/misinformation are extremely frustrating. This is especially true when we see “gurus” or service providers profiting off the misinformation. So, in our effort to help sellers succeed, we’re doing our best to clear up miscommunications and rumors so you have all the information necessary to make informed intelligent businesses decisions to help you prosper!

Now to the subject matter.

The Amazon private labelling world has an obsession with the Amazon Best Seller Rank (BSR). Everyday we have sellers emailing in, wanting us to help them improve their BSR or help them to reach a specific BSR threshold. We see the same in the Facebook groups. It is completely unnecessary and is founded on misunderstanding. We explain how..

Myths Around Best Seller Ranking / BSR:

  • Amazon Best Seller Ranking (BSR) helps keyword ranking.
  • Amazon Best Seller Rank impacts sales.
  • “I need to improve my BSR”
  • Reviews are taken into account when calculating BSR
  • Keyword ranking impacts BSR
  • Listing price at the time of sale impacts BSR

What We See/Hear Sellers Saying About BSR in Facebook groups:

  • “My BSR increased, but why haven’t my organic sales?”
  • “How can I improve my BSR?”
  • “My BSR is better than my competitors, but they are outranking me. Why?”

How Is Your Listing’s BSR Calculated?

An ASIN’s Best Seller Ranking is calculated solely based on the number of units sold over a given period of time. That is it.

Your BSR is not directly related to your listing’s keyword ranking, price, quantity of reviews, or any other metric.

Sales estimation tools like Jungle Scout operate on this same premise. By looking solely at a product’s BSR in specific categories, they are able to estimate that product’s monthly sales volume with a decent degree of accuracy.

For example, if listing A sells more than listing B, listing A will have a lower/better BSR. It’s as simple and rudimentary as that.

When describing Best Seller Ranking, I often use an analogy of a report card. BSR is like a report card showing how many units you sold compared to others in the same category. Just like a report card, your BSR is a representation of past activity. Your BSR does not help you drive future organic sales, in the same way that a report card from a previous semester does not impact your grades in a new semester. It is only an indication of the past.

Debunking the Myths of Amazon Best Seller Rank

Myth: Amazon Best Seller Ranking (BSR) helps keyword ranking.

Our Amazon product launches have uncovered the most contradictory evidence to the BSR assumptions. When running a promotion with a poorly optimized listing, we see a great spike in BSR (ex. #28,400 to #1,600), but see little to no movement in keyword ranking.


This is the Jungle Scout data from the search “dog toys”.

As you can see, the two listings in the red box have higher Best Seller Ranks than the listings in the blue box. If BSR had a direct effect on rankings, we would expect to see a more uniform increase in BSR scrolling down the search results. Many searches will show similar results.

There are many factors being taken into account when it comes to keyword ranking and sales. It is especially difficult to properly attribute the cause of keyword ranking between increases and BSR and sales simply because BSR increases from sales.

Myth: Amazon Best Seller Rank impacts future sales.

Referring back to data we’ve obtained from our product launches, we’ve observed plenty of instances in which promotion increases a listing’s Best Seller Ranking significantly but does not lead to an increase in organic sales for a variety of reasons. There is a lot that goes into improving a product’s sales on Amazon, which is why we continually preach the importance of doing everything extremely well. Cutting corners leads to lost money!

Myth: Reviews are taken into account when calculating BSR

This is definitely false. The cause of this misconception again falls to misattribution. Reviews generally have a significant impact on sales (click conversion). Typically, listings on page 1 with more reviews drive more sales, which means their Best Seller Rank will improve.

This is the Jungle Scout data from the search “iphone 7 plus case”. (Update: we have since released Market Intelligence, the best Amazon product research tool in the galaxy, with sales trends, the most accurate sales estimates, and a star-rating validation).

As you can see, the listings within the red boxes have far fewer reviews than the listing in the blue box, however, their BSR is significantly better/lower.

Here is an example of a listing with over 1,000 reviews at a star rating of ~4.5 with a Best Seller Ranking of over 10,000.

If BSR was impacted directly by a listing’s review rating and/or quantity, we would expect different figures.  

Myth: Best Seller Rank is affected by a product’s price at the time of sale.

There are a few key indicators to this myth being false.  We can’t rely solely on Jungle Scout data for reference as we don’t know if their sales estimation algorithm is taking price into account or not. Simply looking through the search results at varying BSRs and comparing the current selling price is not sufficient as we don’t know how many units are actually being sold. The question is, “Does the price at the time of sale have weight on calculating the BSR,” not “Does your current price have impact on your current BSR?” If that were the case, raising your price would result in an instant improvement in Best Seller Ranking, which we obviously know is not the case.

Route 1: Looking at the BSR of similar ranking products with varying price points.

These are the search results for the keyword “coasters”. As you can see, the second listing is 25% more expensive, yet has a higher BSR. The listing priced at $12.95 has a lower Best Seller Ranking than the $18.99, $15.99, and $14.99 options. Again this is not concrete proof but one example.

Route 2: Looking at actual sales data.

We mange a good number of listings by now. Going through a number of those product’s sales and BSR history within the same category, we are able to see that regardless of price, the products fell within the same BSR range when sales were similar. If you have just a couple of products in the same category that sell fairly similar volumes, it is pretty easy to see for yourself.

How Can You Use BSR To Improve Your Sales?

Should you try to increase your BSR?

When we see this question, it is generally in reference to using promotional services to increase BSR, in which case the answer is no. Increasing your Best Seller Rank through promotional sales serves no direct purpose apart from pushing to obtain a best seller badge, which happens to be against Amazon’s TOS.

Since Viral Launch has been in business, we’ve seen plenty of sellers get excited about an improvement in BSR driven by giveaways. From our perspective it’s a no brainer. Of course the BSR improves. If sales are the sole factor in calculating your Best Seller Ranking, and you drove additional sales, whether at full price or at a discount, then of course the BSR is going to improve. And like we mentioned, that improvement in Best Seller Ranking will have no direct impact on future sales.

For example, (keyword ranking aside) if you gave a massive volume of units to help you reach a BSR of #2 in all of Health & Beauty, you would see no improvement in organic sales as a direct result. Customers do not find products to purchase by sifting through the browse trees, they purchase products after running a search, selecting an item, and then making a purchase.

Essentially, if you give units away at a loss with the intention of improving your Best Seller Ranking, you are wasting money. That is not a strategic move.

How BSR Can Help You Make Smart Business Decisions.

Using the Best Seller Rank metric is fantastic for estimating product’s monthly sales. Even though current tools are not incredibly accurate, they are far better than pure guesses and can be extremely helpful when putting together launch strategies, optimizing your listing, and validating sourcing ideas. From our perspective, this is the only real use for this over-hyped vanity metric.

Should You Be Paying Attention to Your Product’s BSR

Largely, no. If you are using BSR as a sales estimator for your own products, then you should look at your actual sales volume as shown in your Seller Central dashboard as those figures will be more accurate. Generally, the only benefit of watching your BSR is in comparing yourself to your competitors. Is your BSR increasing, but competitors’ BSRs are not? Then you you need to make some adjustments to your offering/listing so you can continue selling at the same volume as your competitors are. Is your BSR increasing at the same rate as competitors? If so, this is typical of seasonal items. As sales slow for a sub-market, all competitors will see an increase in BSR.

Your listing’s Best Seller Rank can fluctuate quite a bit over the course of a day, week, or month. The focus should really be on maintaining/improving search rankings, optimizing your listing, and improving your review funnel as these are the activities that will have an impact on your organic sales and ultimately your business’s bottom line. Continually watching your BSR is like watching the grass in your yard grow, it’s going to grow and at varying rates depending on external factors, but you watching your yard grow does not affect the process. It is only a waste of time. Being aware of your actual sales and responding to changes in the market or your listing are activities that will lead to better bottom line.


More often than not, rumors and misinformation are spread simply due to wrongful attribution. It’s so easy to wrongfully attribute the cause of sales improvements, ranking changes, BSR changes, etc. simply because there are so many moving parts. Amazon is a complex animal. It is wrongful attribution that I hold as the culprit for a lot of the myths around the Amazon Best Seller Rank.

Know any other rumors? Have any questions? Am I wrong? I’d love to know what you think in the comments!

Exit mobile version