March 12, 2020 by Andrew Minalto - 2 Comments

STOP chasing that PERFECT Jungle Scout Opportunity Score!

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Jungle Scout Opportunity Score

Welcome back!

2 weeks ago, I published a post about the top three secrets that will make or break your Amazon FBA business in 2020! I knew that this post would attract many views because people are always looking for the secret—that magic ingredient that will create a successful Amazon business.

Most people think that the secret is to simply spend X amount of hours on Jungle Scout until they hit the jackpot and find a product with super-high demand, low competition and an opportunity score of 9 or 10. Well, let me tell you that this will never work. It is not the way to do proper market research on Amazon. Here’s why…

The Opportunity Score is DEAD!

Opportunity Score

Years ago, when Jungle Scout first launched and competition on Amazon for private-label FBA products was very low, the Opportunity Score was the perfect way to QUICKLY find profitable products. Basically, if you saw an Opportunity Score of 9 or 10, it meant that there was very good demand for the product, very few sellers (1 to 3 sellers, max. 5 sellers for that product) and that listings would have very low review scores.

Times have now changed. As I explained in my previous post, in 2020, you really can’t be lazy with the product research and development stages. There is no way around it. You have to put a lot of hours, creativity and hard work in if you want to launch a successful Amazon FBA product.

Finding a product that has an Opportunity Score of 9 in the Jungle Scout Chrome tool doesn’t mean anything!!!

Even more so now that the Opportunity Score is based on the listings that are displayed on your page, which can be 10 or 50 listings. It will also radically change if you manually remove some listings from the results and if you use various keyword forms in the search.

In fact, the OS value can sometimes fluctuate from 9 to 6 in a matter of a few minutes if you change your search criteria.

But that’s not even the most important thing.

The main problem is that people think that they can find a good product to sell on Amazon JUST by analysing Jungle Scout (or any other Amazon research tool) numbers.

You will see these posts on Facebook all the time. People post screenshots of Jungle Scout Chrome data and ask others whether it’s a good product or not?!

Jungle Scout Results

I’m sorry, but it doesn’t work that way. You can’t PICK a good product based solely on Jungle Scout’s Chrome tool data, and definitely not based on the Opportunity Score alone.

If it was up to me, I would REMOVE the Opportunity Score indicator from the Jungle Scout app completely! Yes, remove it so that people are not blindly following it and making bad decisions. I’m not saying that the Jungle Scout tool is bad for market research—I personally use it all the time and find it invaluable—BUT you have to understand how to use it properly and not follow the Opportunity Score alone.

How to PROPERLY use the
Jungle Scout Chrome Tool

Jungle Scout Extension Results

The main reason why you should use the Jungle Scout Chrome tool is to see market size/sales volume for any given product—and that’s it! This is the main idea behind it the tool. It lets you know exactly how much in sales any given product generates per month.

The secondary function is to instantly get an overview of the competition by looking at the review score and ratings for all the top listings at a glance.

And only then comes the Listing Quality Score (LQS), Opportunity Score and other things. You have to remember that Jungle Scout is just software. It does a very good job of making complex calculations (like counting all the sales for a product), BUT it’s actually not that smart in terms of analysing real competition or giving you advice on which product has the most potential.

Sure, these extra tools can be helpful, especially when you have spent hundreds of hours looking at this data and already know what kind of results you can expect from one or another indicator, but in most cases, they’re just that: a helpful indicator. They are not a true reflection of whether a product is a good or bad opportunity.

The way I personally use the Jungle Scout Chrome tool is by searching for a product on Amazon, running the tool, and then looking at the sales for the top 20 listings. If the numbers I see match my search intent (more on that later), then I glance over to the reviews column to see how competitive the market is.

Example Product Data

If that looks ok, then I will decide pretty quickly to spend more time doing manual research into that market, NO MATTER what the LQS or Opportunity Score says.

I will take a look at other data, yes, but I won’t base any decisions on that data. I manually check out the top-selling listings, look at how professional those brands are, what the top reviews say, etc., before I decide whether I need to spend more time on that product or not.

Another thing I usually check at the same time is brand domination, as I try to stay away from any niches that are already dominated by either a:

  • Household brand;
  • Well-known niche brand.

You can easily see this by looking at the brand name column in the data. If the vast majority of sales go to just one brand AND it’s a well-known household brand or well-known brand in that niche, then I will usually avoid that product. For example, this item:

Vileda Brand Domination

Don’t mix this up with simply one seller dominating the market. It’s not the same thing. Brand domination is when the brand that makes the majority of sales in a niche is WELL KNOWN. Not just some random brand that does well in that space and that most people have never heard about.

As for the actual sales numbers and reviews/ratings, what numbers should you look for?

It totally depends on what you’re after! There’s no one right answer to this. If you’re looking for a small, niche product with low competition, you will look for sales in low thousands, maybe £10k in combined sales for top 10 listings.

On the other hand, if you plan on investing £20k in your product launch, then another £10k in initial PPC costs and you’re looking for a product that can make you £5k in profit per month, you will look for totally different numbers from way bigger niches with greater competition.

It’s crucial that you understand this and don’t look for an unsuitable product for your buying power, knowledge and future plans.

I talk a lot about this in my Amazon Sharks program—and for a good reason! It’s the number one mistake most newbies make! They pick a market that is far too competitive for their buying power and knowledge level, then they complain that Amazon doesn’t work. No, you’re simply delusional about how this works, that’s all.

Conclusion

Conclusion

I hope that by now you fully understand the proper way of doing market research using the Jungle Scout Chrome tool and won’t waste your time blindly searching for products with a high Opportunity Score.

Even if you find a product with a high Opportunity Score, remember that it doesn’t really mean anything. Yes, for a brief moment, the competition may be very low, but you never know how many other people are already working on the same idea! It could be that by the time you launch your product in a few months, there are already twenty new sellers doing the very same thing.

That’s why the three secrets are so important. Most people are simply too lazy to put the extra work in! They just come up with a new name, package the product nicely and hope to win customers over with their shiny, new brand. It’s simply not enough anymore, sorry.

If you have any further questions about anything related to the Jungle Scout Chrome tool data or how to properly analyse the numbers, feel free to leave your questions below the post. I will personally answer all of them within 24 hours, Mon.-Fri. (Usually much sooner).

Andrew Minalto

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2 Comments
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  1. John Edwards

    On the money… As you know brand domination was a cloud thought process to me during market research…

    Now its an instant recognition to me within the data as well as all the other data points you mention here.

    Cool post Andrew.

    1. Andrew Minalto

      Good stuff John! 🙂

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