{"id":14325,"date":"2019-05-29T10:00:04","date_gmt":"2019-05-29T15:00:04","guid":{"rendered":"https:\/\/www.junglescout.com\/?p=14325"},"modified":"2025-03-12T20:56:53","modified_gmt":"2025-03-13T01:56:53","slug":"amazon-sales-estimates-update","status":"publish","type":"post","link":"https:\/\/www.junglescout.com\/blog\/amazon-sales-estimates-update\/","title":{"rendered":"Amazon Sales Estimate Case Study"},"content":{"rendered":"\n

Back in the summer of 2018, we put Jungle Scout — an all-in-one platform for selling on Amazon — to the test with the ultimate Amazon sales estimate accuracy case study<\/a>. <\/span><\/p>\n

Instead of just claiming to be the most accurate tool in the industry, we wanted to prove it. <\/span><\/p>\n

So we asked sellers for their permission to access their products’ actual Amazon sales data. We contracted a third party to collect estimates for the aforementioned items, using a selection of our competitors’ tools. And we documented every step of the study, then publicly released the results.  <\/span><\/p>\n

2019 Update<\/h2>\n

Since the initial case study, our data science team has worked tirelessly to not only maintain the level of accuracy reported in the original results, but to improve upon them.<\/span><\/p>\n

Given the complexity and ever-changing nature of Amazon’s algorithms and marketplace rules though, estimating their sales is a full-time job. But it’s always our mission to stay ahead of the game!
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Keeping the best interests of the Amazon FBA community in mind, we <\/span>included a few more competitor tools in this new analysis. For the rest of the study, we used the exact same steps we used in 2018 when collecting this year’s data. <\/span><\/p>\n

And so the question remained – Is Jungle Scout still the most accurate when it comes to estimating the number of sales on an Amazon listing?<\/em><\/span><\/p>\n

The analysis & results<\/h2>\n

Our first calculation was to determine the median difference in estimated sales relative to actual sales. The formula looked like this: <\/span><\/b><\/p>\n

((Absolute (Actual Sales – Estimated Sales)\/Actual Sales). <\/b><\/p>\n

Then we took the median of those percentage errors for each of the tools–which w<\/span>e’re calling the Overall Error Percentage–and compared them. The closer to 100% the better!<\/span><\/p>\n

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Our reaction:<\/h3>\n
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  1. The most noteworthy result from this study is that Jungle Scout’s accuracy has improved by nearly 10%! <\/strong><\/span>Last year we were looking at an Overall Error Percentage of 25.41%. Today we can see that Overall Error Percentage has dropped to<\/strong> 15.9%,<\/strong> as we continue to close the gap on Amazon’s actual sales reporting.<\/span><\/span><\/li>\n
  2. If you compare our two case studies, you’ll notice that Viral Launch<\/a> and Helium 10 (the second and third place tools) improved their Overall Error Percentage as well. Jungle Scout’s rate of accuracy is still the best, and the only software with an error percentage lower than 20%. We’re confident that conducting regular case studies would continue to prove that point.<\/span><\/span><\/li>\n
  3. While Helium 10 has the third best median, you’ll see in the results below that its range of accuracy is worse than the top two performers: Jungle Scout and Viral Launch.<\/span><\/span><\/li>\n
  4. Unicorn Smasher<\/a> stepped up their game with a paid version of their extension, which appears to dramatically improve their estimation abilities. We take back our comment about rolling the dice rather than using their extension!<\/span><\/span><\/li>\n
  5. We’re unable to compare an increase or decrease in accuracy for AMZ Scout and Sellics, who were absent from the previous study. But as they both sit over the 50% error mark, it would be difficult to trust the validity of their sales estimates, in our opinion. <\/span><\/li>\n<\/ol>\n

    A better way to determine accuracy<\/h3>\n

    When choosing a singular number that is the most robust for comparing accuracy, the median overall error percentage is a great choice. That being said, a box and whisker plot is actually a better representation of the true accuracy of each tool in our study, for any given sales estimate. <\/span><\/p>\n

    An Amazon seller typically wants to know that when they are reading a sales estimate for a product, it’s as close to the real sales number as possible. One hundred percent accuracy is what we all want! Creating and interpreting a box and whisker plot lets us do this. <\/span><\/p>\n

    Here are a few tips to help you read this chart:<\/span><\/p>\n