Jungle Scout Keyword Scout Tutorial: Amazon Keyword Research

The quick answer

How do you use Jungle Scout Keyword Scout?

Jungle Scout Keyword Scout helps Amazon sellers discover relevant search terms, estimate keyword demand, and compare competitor rankings. Enter a seed keyword, a product ASIN, or up to ten ASINs; choose your marketplace; then filter the results by relevance, search volume, ranking difficulty, and estimated advertising bids. Save a shortlist for your listing and PPC campaigns rather than using every suggestion.

Three ways to research Amazon keywords

Keyword Scout offers three useful starting points. You do not need to choose just one: a seed keyword helps you learn the vocabulary of a niche, while ASIN searches show how comparable products appear in Amazon results.

To begin, open Keyword Scout from the Keyword Optimization area in Jungle Scout, choose the correct Amazon marketplace, enter your keyword or ASINs, and run the search. Jungle Scout documents all three methods in its Keyword Scout help guide.

The marketplace selection matters. A US search and a German search can produce different vocabulary, search volumes, competitors, and ad estimates. Always research the store in which you intend to sell, even if you live elsewhere.

Start with a seed keyword: the washable pee pads example

In the video, Ed enters “washable pee pads” for Amazon US. The demonstration returns 1,972 related keywords before filtering. That number illustrates the size of a keyword universe; it is not a permanent search result or a guarantee that all those phrases are useful for your product.

Begin with a clear product description rather than a broad category like “pets.” If you sell washable dog training pads, try the obvious product name first. Then check variations for intended use, material, size, and buyer need. A phrase about disposable pads may be popular but still wrong for a washable product.

I divide the results into three groups. Primary terms describe exactly what the product is. Specific long-tail terms add relevant features or uses. Research-only terms provide context but may not belong in the listing. This separation prevents an impressive-looking search report from becoming a messy product title.

The first pass is deliberately simple: read each promising phrase and ask, “Would a shopper typing this expect to receive my exact product?” If the answer is doubtful, do not prioritize it just because the search volume is high.

Understand Keyword Scout's search volume, competition, and PPC metrics

The results table combines estimated demand, competition signals, and advertising guidance. Each answers a different question, so I would resist judging a keyword by one column. Jungle Scout's column reference explains the current definitions.

Exact versus broad is an important distinction. A search for “washable pee pads” is not interchangeable with every related search about training mats. Likewise, Keyword Scout's broad volume estimate is not a promise that an Amazon broad-match ad will show for exactly the same collection of queries. Research metrics and Amazon Ads matching rules serve different purposes.

The Relevancy Score measures the relationship between a suggestion and your seed keyword. It is helpful for sorting, but the score cannot inspect your actual product materials, size, or positioning. Relevance to the buyer remains your decision. Search volume is also an estimate of searches, not the number of people who will click or buy.

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Use filters to turn thousands of keywords into a useful shortlist

An Amazon listing has limited space, so thousands of suggested keywords are a starting point rather than a writing assignment. In the demonstration, adding a minimum word count of three reduced the results from 1,972 to roughly 1,700 after the filter was applied. That is a useful first cut, but still far too many phrases to copy into a listing.

I would narrow the research in stages. First, filter by word count to surface longer, more specific phrases. Next, review the appropriate product category and remove terms that describe a different item. Then look at estimated exact search volume and Ease to Rank together. A very specific phrase with modest demand can be more practical than a popular, vague term dominated by established products.

Use organic and sponsored product counts for another view of competition. Sponsored results represent paid placements, while organic positions describe unpaid search visibility. A strong presence in one does not automatically establish strength in the other.

If you are planning advertising, filter estimated exact- and broad-match PPC bids against a budget you can actually test. Avoid declaring a keyword profitable simply because the suggested bid is low: conversion rate, product price, margin, and actual auction results decide whether it works.

Jungle Scout's filter instructions explain how to select Filters, set minimum and maximum values, and press Apply. You can save filter presets for repeatable research. The original video even catches the easy mistake of changing a value without applying it.

Reverse ASIN research: find keywords competitors rank for

An ASIN is Amazon's product identifier. You can usually find it on a product detail page or in its URL. Copy the ASIN of a close competing product, enter it into Keyword Scout, confirm the marketplace, and search. This reveals keywords associated with that listing's positions in Amazon results.

In our tutorial, a novelty magnet listing makes the example clear. A competitor might appear for a phrase such as “cute magnets” even if you had not thought to research it. That gives you a new idea to investigate. However, an ASIN appearing for a keyword does not prove the keyword generated a specific number of sales or that the competitor intentionally targeted it.

Choose competitors carefully. Match the product type, audience, price range, and main features rather than copying an unrelated bestseller's vocabulary. A keyword describing a material or design your product does not have should stay off the shortlist.

When a reverse ASIN search shows few or no keywords, it may mean the product is not appearing in the tracked top search positions for enough terms. Jungle Scout explains that its reverse lookup focuses on keywords where the ASIN appears within the top 100 results. A sparse report is not proof that nobody buys the product.

Variants also matter. Depending on your filters, a parent or variation family may contribute additional keyword associations. Use the variant exclusion option when you specifically want to analyze the selected ASIN rather than a broader family of sizes or colors.

Multi-ASIN search: compare your listing with several competitors

The multi-ASIN workflow becomes especially useful when you already sell a product. Add your own ASIN first, then add several genuinely comparable competitors. Keyword Scout supports up to ten ASINs in one query. The first or highlighted ASIN provides the reference point for comparing the other products.

In the video, Ed uses the anchor ASIN to explain three questions: Where does my product rank? How many competing ASINs rank for the same keyword? And is my product ahead of or behind the other listings in that particular comparison?

A relative position of two means you are second among the products being compared; it does not mean you rank number two across all of Amazon. The searched-ASIN counts also exclude the highlighted ASIN, which matters when interpreting a shared-keyword opportunity.

Suppose three comparable cactus magnet products rank for a highly relevant phrase, while your listing ranks behind both rivals. That could justify reviewing your title, offer, images, or ads. A lower position is a reason to investigate, not automatically a reason to delete the keyword. Conversely, a phrase where you already rank strongly can be a useful benchmark to protect.

The separate organic and sponsored views help avoid mixing paid visibility with unpaid ranking. Check the official ASIN metric explanations if you want precise definitions for the comparison fields.

Save keywords and turn research into listing improvements

Once the results are focused, select useful terms and add them to a Keyword List. I prefer separate lists for primary listing terms, relevant long-tail phrases, and PPC candidates. Naming them for the product and marketplace makes the research easier to revisit later.

The keyword list is a workspace, not evidence that every phrase belongs in your title. Put the most descriptive phrase where a shopper immediately understands the product; use supporting details naturally in bullets and descriptions. Keep your product attributes accurate and remove repetition that makes the copy awkward.

Amazon's guidance for backend search terms requires generic, relevant wording and excludes brand names, ASINs, and other prohibited expressions. Its generic keyword field is limited to fewer than 250 bytes, which is not always the same as 250 characters. Product titles and other fields have their own category-specific rules.

Pay special attention to competitor brands. You can study their rankings, but that does not give you permission to place their trademarks in your own backend search terms. Genuine product compatibility claims can involve different rules; describe compatibility accurately and consult the relevant product-detail policies instead of treating every brand reference as automatically acceptable.

For the next step, my Jungle Scout Listing Builder tutorial shows how to turn a clean keyword bank into customer-friendly listing copy.

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Start with one product, a few close competitors, and a short list of decisions you want the data to support. Compare current Jungle Scout plans and promotions before subscribing; the tool limits and final offer may depend on the plan you select.

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Build a realistic Amazon PPC keyword test

Keyword Scout's estimated bids can help you prepare, but they are not the amount Amazon guarantees you will pay. I would select a small group of highly relevant terms and create a controlled experiment rather than launching dozens of targets at once.

For each candidate, write down the phrase, estimated exact volume, relevance to the product, estimated bid, and what you hope to learn. Put closely related keywords into the appropriate campaign or ad group. Check the real search term report, clicks, orders, advertising cost of sales, and product margin before increasing spend.

Use exact targeting when you want a tighter test around a chosen search term. Use broader targeting for controlled discovery, with negative targets where appropriate. The match type influences which searches can trigger an ad, while bids, relevance, competition, and other factors influence delivery and cost.

An estimated high-volume keyword with no conversions is not automatically better than a specific phrase bringing qualified orders. The purpose of the research is to help you spend more intelligently, not to chase the largest number in a column.

Common Keyword Scout mistakes to avoid

The biggest mistake is treating research output as a finished strategy. A keyword may be popular without fitting your product. An Ease to Rank score can be attractive even when competing products have stronger offers. And a reverse ASIN report shows ranking associations rather than verified competitor sales attribution.

Another mistake is forgetting the marketplace or filter settings. Check the selected country, review the time period, and make sure you actually pressed Apply. If you analyze a variation family, verify whether variant keywords are included before comparing two searches.

Finally, avoid using one snapshot as proof of a trend. Look at historical search volume where your subscription allows it, then compare the results with seasonal shopping behavior and live Amazon listings. Jungle Scout currently describes historical keyword data as available for up to two years on eligible plans; access varies by subscription.

My preferred approach is simple: research, shortlist, implement, and measure. Repeat it when new results suggest something has changed. That gives every keyword a clear role in your business.

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