Jungle Scout Ads Analytics: Amazon PPC Guide (2026)

The quick answer

What is Jungle Scout Ads Analytics?

Jungle Scout Advertising Analytics, also called Ads Analytics, brings Amazon advertising and sales data together so sellers can review PPC performance at the company, product, campaign, and keyword levels. It shows ad spend, ad-attributed sales, ACoS, TACoS, ROAS, and a waterfall breakdown of recorded revenue and costs. Its main advantage is helping you judge advertising against the wider business, not only the clicks it generates.

How Jungle Scout Advertising Analytics works

The tool combines information associated with your connected Amazon Seller Central account and its advertising reports. Rather than switching between several screens to answer whether a campaign helped your business, you can review related figures in one place. Jungle Scout's official Ads Analytics guide explains the Overview, Sales Activity, and Advertising Performance views.

Start by connecting the appropriate Amazon account, selecting the correct marketplace or store, and checking your Product Costs and Settings. Without accurate cost-of-goods information, a reported net profit can give you more confidence than it deserves. Some figures may also depend on your subscription and available advertising data.

In the current Jungle Scout ecosystem, the seller-facing platform is called Catalyst. The precise menu, terminology, and feature access can change, so use the live account and plan comparison if a video screenshot looks different. Ads Analytics is an analysis tool; reviewing its data does not itself mean bids or budgets are automatically changed.

Read the company-wide Amazon PPC dashboard

The first screen Ed demonstrates presents an overview of the advertising account. You can see attributed advertising sales, the money spent on those ads, and how often ads appeared in search results or other placements. Customizable widgets can surface clicks, click-through rate, and conversion-related metrics as well.

Understand the waterfall chart and your net profit

The waterfall chart is my favorite part of the demonstration because it connects advertising to the wider business. It begins with organic sales and ad-attributed sales as separate revenue streams, adds other recorded revenue where applicable, and then subtracts advertising spend, cost of goods sold, Amazon fees, and other tracked expenses.

The final bar shows the net result based on the data available to the dashboard. A green positive result is encouraging. A red negative result tells you the recorded costs exceeded the recorded revenue. Neither color replaces checking whether all relevant expenses and adjustments were entered correctly.

When you see a disappointing result, trace the biggest deductions. Has ad spend risen faster than total revenue? Did storage fees increase? Were returns, inbound shipping, or supplier costs entered accurately? The chart narrows your next investigation without telling you automatically which decision to make.

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Compare Jungle Scout's available plans and check whether Ads Analytics is included in the option you choose. You can review the latest offer before committing.

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Organic sales versus sponsored sales: what should you look for?

One graph in the demonstration compares organic revenue with advertising-attributed revenue. That split matters because paid ads can support a product launch while organic visibility develops. But sellers should not assume that every increase in organic sales was caused by the advertising budget.

Ed compares Amazon advertising to putting fuel into an engine. More investment can generate more sponsored traffic, and stronger sales may be associated with improved search visibility. The important word is may. Better rankings and organic demand also depend on relevance, conversion rate, price, competition, seasonality, customer experience, and other factors.

There are times when spending more is a deliberate choice. During a launch, a seller might accept expensive clicks while gathering conversion data and testing relevant keywords. A mature product with a stable ranking may prioritize maintaining visibility at a lower advertising cost. Neither strategy is automatically correct for every listing.

For a deeper look at what happens when launch spending ends, see my guide to managing Amazon PPC after a product launch.

ACoS, TACoS, and ROAS explained with real calculations

These three metrics appear throughout the video. They are closely related, but their denominators are not the same. Knowing the formulas is more useful than memorizing a universal target percentage.

A lower ACoS means you spent a smaller share of attributed sales on ads. A lower TACoS means advertising represented a smaller share of all sales. Higher ROAS means more attributed revenue for each advertising dollar. However, a sudden drop in TACoS can come from rising organic sales, reduced spending, or a combination of both. You need the underlying numbers to know which happened.

Important correction to the video: ROAS of 1 means advertising revenue equals advertising cost. It is an ad-revenue-to-spend break-even point, not a true business break-even point. Product costs, Amazon fees, and other expenses still need to be paid. A ROAS of 3 may be profitable for one product and loss-making for another.

For example, suppose a product has a 20% contribution margin before ads. On $100 of attributed revenue, only $20 remains to cover advertising. Spending $25 yields an ACoS of 25% and ROAS of 4, yet the sale loses $5 after ad spend. Your simplified break-even ACoS is 20%, while break-even ROAS is 5. Amazon's ACoS guide explains why the target depends on product margins.

Analyze Amazon advertising performance by ASIN

A company-wide average can hide a struggling product. In the walkthrough, Ed selects a washable pet-pad listing, and the waterfall chart updates to focus on that ASIN. This is particularly useful when you sell products with different selling prices, competition, or margins.

The Sales Activity view helps you compare the product's total revenue with advertising costs and see changes by date. Imagine a product with $3,000 in organic revenue, $2,000 in ad sales, and $600 in ad spend. Its ACoS is 30%, TACoS is 12%, and ROAS is approximately 3.33. Those figures describe ad efficiency, but you still need the product's cost structure before declaring it profitable.

Pay attention to the time series, too. In one example from the video, the advertising spend and ad revenue points nearly touch on October 2. That signals a day when the recorded revenue from ads was close to what was spent on them. It is a reason to investigate, not proof that the entire product was unprofitable.

Check whether the pattern recurs. A single day's data can be distorted by attribution delays, low order counts, changes to bids, or temporary traffic patterns. I would review enough completed days to understand the trend before making a large change to a campaign.

Break down campaigns, ad groups, and product ads

The Advertising Performance area moves from overall results into the structure of your Amazon PPC account. At a basic level, a campaign contains ad groups, and those groups contain advertised products and targeting settings. The video focuses on Sponsored Products, the sponsored listings many sellers encounter first in Amazon search results.

Start with the campaign view to compare clicks, total spend, attributed sales, ACoS, ROAS, and cost per click. Then drill into ad groups and product ads to identify where strong or weak results are concentrated. A campaign that looks average overall can contain one product driving efficient orders and another using much of the budget.

Keep in mind that a dashboard view is not the same thing as full campaign management. Jungle Scout Catalyst provides advertising analysis, while its enterprise-oriented Cobalt platform has broader PPC management and optimization capabilities. Do not assume that inspecting a weak keyword in Ads Analytics automatically changes its bid.

Use keyword and search-term reports to improve targeting

One of the most actionable parts of the tutorial is the distinction between a keyword you target and a search term a customer actually types. They can be different, especially when you use broad or phrase matching. A seller might bid on a general phrase and discover that a more specific customer query generates the best results.

The keyword view helps evaluate selected targets, bids, impressions, clicks, spending, and attributed sales. The search-term view helps reveal the real phrases that triggered the ads. Comparing the two can show where your customers' language differs from the language you originally selected.

I would look for relevant terms that have enough clicks and attributed conversions to support a decision, rather than shifting the whole budget after one sale. It may also make sense to exclude consistently irrelevant queries using negative keywords where appropriate. Before doing so, verify that the query truly does not describe a useful customer.

Remember that exact match, phrase match, and broad match are targeting configurations, not guarantees that every reported query will be identical to the keyword. Always use the actual search-term data and the current Amazon Ads matching rules to understand what appeared and why.

A practical weekly Amazon PPC analytics workflow

You do not need to change campaigns every day to benefit from the dashboard. A consistent review of the same metrics often provides better context than reacting to whichever number looked worrying this morning.

1. Use a completed reporting window. Check the marketplace, date range, and attribution timing. Compare equivalent weeks or another relevant period.
2. Review the overall waterfall. Note changes in ad spend, organic revenue, product costs, Amazon fees, and estimated net profit.
3. Identify outlier products. Filter to ASINs where costs rose, margins weakened, or sponsored sales changed sharply.
4. Drill into campaigns. Look for a specific ad group, product, keyword, or search term that plausibly explains the result.
5. Choose one test. Record a bid adjustment, a negative-keyword decision, a listing improvement, or a controlled budget change, then revisit the outcome later.

If you are still learning Jungle Scout more broadly, my complete Jungle Scout beginner tutorial connects advertising analytics with product research, listing optimization, and other seller tools.

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What Jungle Scout Ads Analytics cannot tell you on its own

A clear dashboard is valuable, but reported advertising sales are attributed according to the advertising platform's rules. They are not always a direct measure of incremental sales that would have been impossible without ads. Likewise, missing expenses or an incorrect cost per unit can make the profit waterfall overly optimistic.

My approach is to treat Ads Analytics as an investigation layer: use it to find patterns, then verify the cause in Amazon Ads, your listings, inventory records, and financial inputs before making an expensive decision.

Frequently asked questions about Jungle Scout PPC analytics