Market Analysis: Feature Overview

Market Analysis lets you define, analyze, and track competitive segments on Amazon. Build a segment by applying filters to narrow the Amazon catalog down to the products you actually compete against, and your data updates alongside it instantly. There's no build step, no processing delay, and no limit on the number of products in your segment.

This article covers how Market Analysis works, how to create and analyze segments, and key details about the data, filters, and analysis available to you.

⚠️ Limited beta

Market Analysis is currently available as a 60-day limited beta. Non-agency customers who previously had access to Market Segments were enrolled automatically on April 7, 2026 with access to their primary L2 Amazon category. To change your category, ask questions about ongoing access, or expand your coverage, reach out to your CSM. Agencies interested in Market Analysis should contact their CSM to discuss access.

Good to know
Instant segments — There is no build step. All data is pre-processed and ready for analysis. When you apply filters, you're narrowing down data that already exists. Results update in real time.
No ASIN limits — Segments are scoped by Amazon category, not by ASIN count. There is no cap on the number of products within your accessible categories.
Category-based access — Your subscription defines which Amazon categories you can analyze. Categories are at the Level 2 (L2) tier, one level below a top-level parent. For example, Beauty & Personal Care is the parent; Shaving & Hair Removal Products is an L2 category.
Two-year product history — Your segment returns any product that has had sales or been active on Amazon at any time in the last two years and matches your filter criteria. This may include products that aren't actively selling today.
Filters apply to current data — Most filters evaluate the product as it exists today. A Product Title filter checks the current title and returns any matching product active in the last two years. Some filters (Revenue, Price) include a date range selector so you can define the window the filter evaluates against.
Weekly data refresh — The full two-year rolling history for all ASINs in the segment refreshes every Sunday. For example, if the most recent available data runs through Saturday, May 9th, 2026, your history extends back two years from that date. See How the data works for details on data timing and availability.
Marketplace-specific — Each segment covers a single marketplace. Currently available for US, DE, UK, and MX. Additional marketplaces coming soon.
Dynamic by default — Saving stores your filter configuration, not a fixed product list. Each time you open a saved segment, it reflects whatever currently matches your filters.
💡 Integrated catalog

If your product catalog is integrated with Jungle Scout, you'll see additional data layered throughout Market Analysis: your market share line on the Overview chart, your average selling price on the Pricing tab, your share within individual price bands, and your products highlighted throughout the analysis. The information described in this article is available to all users, with or without an integrated catalog.

How to create a segment

This section covers the basics. For a detailed step-by-step walkthrough with screenshots, see the Market Analysis - How to Create a Segment guide.

1. Open Market Analysis. Click Market Analysis in the left-hand navigation. This opens a blank segment view with empty filters. It does not open your list of saved segments.

2. Select a required starting filter. Before any data appears, apply at least one of these three filters:

  • Categories — Filter by Amazon subcategory using tree navigation
  • Brands — Filter by brand name
  • Product Title — Filter by keywords in product titles

You cannot apply only a secondary filter (like Price or Star Rating) on its own. At least one anchoring filter above is required before data populates. You can select multiple L2 subcategories at once to cover a broader view, including selecting enough to cover an entire L1 parent category.

3. Layer additional filters to refine. Once data populates, add more filters to narrow your view. Results update in real time. See Filter reference for details on every available filter.

4. Review your results. Check the Overview tab to confirm the products match your competitive set. If the products look like what a buyer would consider alongside yours, the segment is right.

5. Save your segment. Save it when you're satisfied. Use the Share toggle to make it available to all other users in your account. There are no user-level or group-level restrictions at this time.

The filter panel lets you define your segment. Apply at least one category, brand, or product title filter to populate data.

Market Analysis filter panel showing category, brand, product title, revenue, price, star rating, and rating count filters.

Once filters are applied, the Overview tab displays your segment data with the tab navigation bar at the top.

Market Analysis Overview tab showing revenue trend chart, market share data, and tab navigation bar after filters are applied.

Filter reference

Every filter narrows or expands your segment's product list. Start with Categories, Brands, or Product Title to anchor your view, then layer additional filters. Filters marked Date range ask you to select a time window, then set min/max values manually or with a sliding scale.

Filter What it does
Marketplace
Required
Set first. All data reflects the marketplace you select. Currently: US, DE, UK, and MX.
Categories
Most used
Filter by Amazon subcategory via tree navigation. Also powerful for exclusion: results show all categories with counts so you can remove off-target ones in bulk.
Brands Include or exclude specific brands. Toggle between Include and Exclude mode at the top of the filter. When including, only the selected brands appear in your segment. When excluding, all brands appear except the ones you select. You can also exclude individual brands directly from the Brands tab table by clicking the exclude icon on any row. Useful for removing off-target brands or consolidating inconsistent brand name spellings.
Product Title
Most used
Filter by keywords. Supports Contains / Does Not Contain with Any of / All of logic, multi-rule and multi-group combinations.
Revenue
Date range
Select a date range, then set min/max values. Use to focus on products with meaningful sales activity.
Price
Date range
Filters by median Buy Box price over your date range. Longer windows produce a more stable median.
Star Rating Sliding scale from 0 to 5. Setting a minimum above 0 excludes unrated products.
Rating Count
Suggested
Setting a minimum of 1 removes never-rated products. Can cut 30 to 40% of a broad result set.
Excluded Products Remove specific products by ASIN without adjusting other filters.
💡 Which filter to start with

Start with Categories when competition clusters in a specific subcategory.

Start with Product Title when competition is defined by a shared keyword.

Add Rating Count ≥1 early to remove inactive listings.

Saving and managing segments

Saving a segment stores your filter configuration. Every time you open a saved segment, it reflects products currently matching your filters against the latest weekly data. Segments are dynamic by default: as products enter or exit your filter criteria week to week, they automatically appear in or drop out. There is no "active" or "paused" status for segments in Market Analysis.

  • Editing a segment means updating its filters. Changes take effect immediately.
  • Sharing a segment: Use the Share toggle when saving. When enabled, all other users in your account can access the segment. No user-level or group-level restrictions yet.
  • New products: If a product becomes active on Amazon and meets your filter criteria, it will be included in the segment after the next Sunday refresh. Each refresh updates the full two-year rolling history for all ASINs in the segment.

Accessing your saved segments

When you click Market Analysis in the left-hand navigation, a blank segment view with empty filters opens by default. It does not open your list of saved segments. There are three ways to access your saved segments:

  • Top-left link: Click the Saved Market Segments link at the top left of the page. This opens your full list of saved segments.
  • Landing page card: When you first open Market Analysis, the landing page shows a "Saved Market Segments" card with your most recent segments listed. Click View all in the top right of that card to see the full list.
  • Bottom-left folder icon: Click the small folder icon at the bottom left of the screen. This opens a quick-access list of your most recently viewed segments, with a "View all" link to the full list. This icon is available from any screen within Market Analysis, not just the landing page.

When you first navigate to Market Analysis, the landing page shows a Saved Market Segments card with your recent segments. Click Saved Market Segments at the top left, View all on the card, or the folder icon at the bottom left to access your full list.

Market Analysis landing page showing the Saved Market Segments link at the top left, a recent segments card with a View all link, and the folder icon at the bottom left.

When you're inside an existing segment (creating or editing), you can still access saved segments using the Saved Market Segments link at the top left or the folder icon at the bottom left.

Market Analysis view from inside a segment, showing the Saved Market Segments link at the top left and the folder icon at the bottom left for accessing saved segments.

⚠️ Segments may shift week to week

Because segments are dynamic, the products may change from one week to the next as products enter or exit the filter criteria. Point-in-time snapshots are planned for a future update.

Understanding your analysis

Once you've created or opened a segment, Market Analysis presents your data across several tabs. Each tab offers multiple chart types (bar, time series, and stacked area) and the ability to toggle between revenue, units, and market share views. As you scroll, the filters and date picker stay visible at the top of the screen so you can make adjustments without scrolling back up.

Date picker

Controls the time window for your analysis. The date picker uses weekly increments and will force your selection to align with complete Sunday-to-Saturday weeks. Available presets include: Last 4 weeks, Last 8 weeks, Last 12 weeks, Last 26 weeks, and Last 52 weeks. You can also select a custom range directly from the calendar.

When you choose a preset, it selects the most recent full weeks for which data is available. For example, if today is Wednesday, May 20th, 2026, selecting "Last 4 weeks" will select Sunday, April 12th through Saturday, May 9th, 2026, which are the four most recent complete weeks of available data. You can confirm the exact dates included by checking the date range displayed in the picker or expanding the calendar dropdown.

A toggle lets you switch between comparing to the prior period or prior year. For more detail on data timing, see How the data works. Monthly increments are coming soon.

Segment summary

At the top of the view, you'll see the total number of products, brands, and categories in your segment. These counts reflect the full two-year window and don't change when you adjust the date picker. Even if you narrow the date range to 12 weeks, the product/brand/category counts stay the same because those are the totals across the entire history. The charts and trends below will reflect your selected time window.

Overview tab

Your starting point. The main chart shows total revenue or units over time. If your catalog is integrated with Jungle Scout, your market share line is overlaid on top of this view. The market share line is color-coded: green if your share is growing, red if declining, and gray if neutral. Hover any point for weekly detail.

Market Dynamics appears to the right of the main chart and surfaces insights you won't find elsewhere. It includes:

  • 1P/3P split with changes over time
  • Average selling price (ASP)
  • Momentum showing whether the segment is growing, declining, or stable
  • Seasonality patterns
  • Competitive concentration showing how many brands hold the top third of market share
  • Market volatility showing which brands lead the market and how leadership changes over time

Click any Market Dynamics card to expand it with a more detailed view and trend data.

Below Market Dynamics, you'll see breakdowns by top brands, categories, and products. These are previews of the detailed views available in each tab.

The Overview tab shows total revenue and market share over time, with Market Dynamics insights on the right. If your catalog is integrated, your market share line is overlaid on the chart.

Market Analysis Overview tab showing the revenue trend chart with market share data, Market Dynamics insights, and top brands and products for a competitive segment.

Brands tab

Shows every brand in your segment with revenue, units, market share, and 1P/3P split. You can view the data as a bar chart, time series, or stacked area chart, and toggle between revenue, units, and market share. Switching between these views can reveal different stories. For example, a brand might lead in total revenue but be losing market share to smaller, faster-growing competitors.

Slide-out detail panel: You can open the detail panel for any brand by clicking the brand name in the bar chart (note: the slide-out works from the bar chart view, not from time series or stacked area), from the Top New Brands section, or from the sortable Brands table at the bottom. The panel shows:

  • Revenue, market share, average price, product count, and units sold for the selected time period
  • A market share trend graph you can hover over to see weekly changes
  • A product segment summary showing the brand's revenue and product count within each subcategory
  • A product list with two toggles: All (every product for the brand in this segment) and New (products that didn't exist in the prior period or year)

New brands: The Top New Brands section highlights brands that have revenue in the current period but had no revenue in the comparison period. This is useful for spotting up-and-coming competitors early.

Brand names on Amazon are self-assigned by sellers, so the same brand may appear under multiple spellings. Use the Brands filter to consolidate.

The table at the bottom provides sortable fields for deeper analysis. More fields will be added over time.

The Brands tab showing a stacked area market share view with year-over-year comparison, the Top New Brands callout, and a sortable brands table.

Market Analysis Brands tab showing a stacked area chart of brand market share over time with year-over-year comparison, a Top New Brands section highlighting recent market entrants, and a sortable brand table below.

💡 Comparison period affects "New" brands and products

The date selector includes a dropdown to compare against the prior period or the prior year. Change this based on your analysis needs. This setting also affects which brands and products appear as "New." When set to prior period, "New" shows brands/products with sales in the current period but not the immediately preceding period. When set to prior year, it shows those with sales this year but not last year. Switch between them to get different perspectives on market changes.

Clicking a brand name opens a detail panel on the right showing revenue, market share, average price, product count, units, a market share trend graph, and a product list with "All" and "New" toggles.

Market Analysis detail panel showing brand-level data including revenue, market share, average price, product count, units sold, a market share trend graph, and a product list with All and New toggles.

Products tab

Shows individual products in your segment with detailed metrics. You can view the data as a time series, stacked area chart, or scatter plot. The scatter plot shows the distribution of price versus revenue (or price versus units), which helps you see where product concentration is and identify outliers. Products from your brand are shown as purple dots. Hover over any dot to see more detail. Use the dropdown in the top right of the chart to switch how many products are shown (top 50, 100, or 200).

The table below is sortable and will grow with additional fields over time, including the ability to customize which columns are visible.

The Products tab showing a scatter plot of price versus revenue, with your brand's products shown as purple dots. The sortable product table is below.

Market Analysis Products tab showing a scatter plot of price versus revenue with purple dots for integrated brand products, and a sortable product table below.

Categories tab

Breaks down your segment by Amazon subcategory. Useful for understanding which subcategories drive revenue, how market share shifts between subcategories over time (especially for seasonal categories), and for finding off-target categories to exclude.

The Categories tab showing a subcategory breakdown with revenue distribution and a sortable categories table.

Market Analysis Categories tab showing revenue distribution across Amazon subcategories with a chart and category breakdown table.

Attributes tab

Analyze trends across your segment by product attributes like size, color, material, and more. Product Attributes are currently available for the US and DE marketplaces. If you are working in a segment for a marketplace that does not yet support Product Attributes (such as UK or MX), the Attributes tab will not appear. See Product Attributes and variants below for full details.

💡 Explore as you go

Throughout Market Analysis, many elements are clickable and expand a detail panel on the right side of the screen. Look for a highlight on hover that indicates a click will open more detail. You can trigger the slide-out from brand names, product names, subcategories, and attribute values in tables and bar charts. The slide-out format is consistent across all tabs: it shows revenue, market share, average price, product count, units, a trend graph, and a product list with "All" and "New" toggles.

Pricing analysis

The Pricing tab analyzes how products in your segment distribute across price bands. It automatically groups products into 5 to 9 price bands based on round numbers, showing revenue, product count, and market share for each band.

Drill down into any price bucket by clicking the Zoom link. This breaks the selected band into smaller sub-bands so you can see exactly where products concentrate within a range. You can zoom in multiple times for increasingly granular views, then back out to see the full picture again.

Average selling price (ASP) is shown alongside the price distribution, including the 80% range where most prices fall. If your catalog is integrated with Jungle Scout, your ASP is overlaid on this chart so you can compare your pricing to the market.

Revenue migration appears on the right side of the Pricing tab. This shows how the share of total revenue is shifting between price bands over time. A price band can be growing in absolute revenue but shrinking in share of the total market, which is an important distinction for pricing strategy.

The Price Band Analysis table at the bottom provides a detailed breakdown for each price band. Here's what each column means:

Price Band — The price range grouping (e.g., $0 to $5, $5 to $10). Click any row to open a slide-out with more detail. To see a further breakdown of a band, use the Zoom link in the chart above.
Revenue — Total estimated revenue across all products in this segment within that price band.
Momentum — The percentage change in revenue compared to the prior period or prior year. A green arrow means revenue is growing; a red arrow means it's declining.
Products — Total number of products in that price band.
Brands — Total number of brands represented in that price band.
Top Brand — The brand with the highest revenue in that price band.
1P / 3P — A visual bar showing the split between first-party (Amazon selling directly, shown in teal) and third-party (marketplace sellers, shown in purple) sales. The percentage label confirms the majority channel (e.g., "74% 3P").
Rev / Product — The average revenue per product in that band, calculated as total revenue divided by total products.
Your Share — Your brand's share of revenue within that price band. Requires an integrated catalog.
Efficiency — Tells you whether your products are generating more or less revenue per listing than the average product in that price band. An efficiency above 100% means your products outperform the band average; below 100% means they underperform. Requires an integrated catalog.
Signal — An actionable insight for that price band based on your share, efficiency, momentum, and market size. Signals include: Scale opportunity (you outperform per listing but hold little share, adding products should yield strong returns), Underweight (you have low share in a growing band with significant upside if you expand), Room to grow (demand is expanding and increasing your assortment could capture more share), Monitor exposure (you have share in a declining band, consider whether to hold or shift investment), Niche presence (minimal market revenue, low volume, unlikely to move the needle), and Niche band (very little market revenue in this band relative to others).

Reading efficiency: an example

In a disposable razors segment, the $0 to $5 price band shows:

  • Market revenue of $724,384 across 62 products
  • Rev / Product of $11,684 (the market average per listing in this band)
  • Your Share of 2.6%
  • Efficiency of 158.5%

That 158.5% efficiency means each of your products in the $0 to $5 range generates about 1.6 times more revenue than the average product in that band. Your listings are outperforming, and the signal reads "Scale opportunity," meaning adding more products in this range should yield above-market returns.

Compare that to the $5 to $10 band, where your efficiency is 25.0%. That means each of your products generates only about a quarter of what the average product earns in that range. The signal reads "Underweight," meaning you have significant room to expand. Understanding efficiency alongside momentum and your share helps you prioritize where to invest.

The Price Band Analysis table showing revenue, momentum, products, brands, 1P/3P split, revenue per product, your share, efficiency, and signals for each price band.

Market Analysis Price Band Analysis table showing price bands, revenue, momentum, products, brands, top brand, 1P/3P split, revenue per product, your share, efficiency percentage, and actionable signals for a disposable razors segment.

The Price filter uses the median Buy Box price of daily values over your selected date range. Short promotions have limited impact unless they run for a significant portion of the window.

Click Zoom on any price band to break it into smaller sub-bands. You can continue zooming for more granular views.

Market Analysis Pricing tab zoomed into a specific price band, showing smaller sub-bands within the selected range for more granular analysis.

🎯 Use case: Find pricing white space

Identify price bands with high demand but few products. If most revenue concentrates in the $15 to $20 range and your product sits at $25, drill in with Zoom to see who's there and how they compare. Use the revenue migration chart to understand whether that band is growing or shrinking in share.

Exporting data

You can export data from the Brands, Products, Categories, and Attributes tabs. Each tab's table includes an export button that lets you download the data as a CSV or Excel file.

Exports are available on the Brands, Products, Categories, and Attributes tabs.

Market Analysis tab navigation showing the Brands, Products, Categories, and Attributes tabs highlighted to indicate export availability.

What's included in the export

When you click the export button, the export dialog opens with the columns currently visible in the table selected by default. You can select or deselect any columns before exporting, so your export can include different fields than what's shown in the table.

The export dialog showing column selection, file name, sort order, and format options.

Market Analysis export dialog showing the Brands table with the export button highlighted and the configuration modal with column selection, file name, sort order, and format options.

File naming

The file name is auto-generated using the following format:

[Segment name] + [Tab name] + [Date range] + [Comparison type] + [Export date]

For example: "Shaving Razors - Brands - Apr 27 2025 through Apr 25 2026 - vs Prior Year - May 6 2026." The file name can be up to 200 characters long. You can edit it before downloading.

Sorting and row limits

Before exporting, choose how to sort the data. This is important because exports are limited to 20,000 rows. If your segment has more than 20,000 rows, only the top 20,000 based on your selected sort order will be included. A warning appears at the bottom of the export dialog when your selection exceeds this limit.

For example, sorting by estimated revenue descending gives you the top 20,000 products by revenue. Sorting by price descending gives you the top 20,000 by price. Choose the sort order that captures the data most relevant to your analysis.

💡 Tip: Need more than 20,000 rows?

If you regularly need to export more than 20,000 rows, ask your CSM about Data Cloud, which provides a more scalable method for accessing large datasets.

Export format

Choose between CSV or Excel. Both formats contain the same data, columns, and values. CSV is a plain text file that opens in any tool and is lighter weight. Excel is an .xlsx file that opens natively in Excel or Google Sheets and is ready for filtering, formatting, and charting without an import step. The file downloads directly to your computer. Exports are not currently available in the Cobalt Exports Manager, but this integration is planned for a future update.

Product Attributes and variants

The Attributes tab lets you analyze trends across your entire segment by product attributes like size, color, material, ingredient, and more. The tab surfaces attributes that have meaningful differentiation in your segment. If all products share the same value for a particular attribute, that attribute may not appear since it wouldn't provide useful comparative insight.

Attributes vs. variants

On Amazon, a variant is a child ASIN within a parent-child grouping. When a seller creates a product with multiple options (sizes, colors, configurations), each option is a separate child ASIN grouped under one parent. The attributes that define these options are called variation themes (for example, Color, Size, or Material).

But every product has many more attributes beyond just its variation themes. A t-shirt might vary by Color and Size (those are the themes), but it also has a Material, Fabric Type, and other descriptive attributes.

The Attributes tab groups all of these across your entire segment to show market-level trends. Variant-level data tells you which specific size or color sells best within a single listing. The Attributes tab tells you what materials, colors, or pack sizes are trending across the entire category.

The simple rule: All variation themes are attributes, but there are many more attributes than there are variation themes. The Attributes tab shows all of them in one place.

Reading the Attributes tab

For each attribute (like Material), you'll see a bar chart showing revenue or units broken down by each value (Rubber, Plastic, Chrome, Stainless Steel). You can toggle between Revenue and Units. Below the chart, a table lists each attribute value with product count and revenue.

Clicking any attribute value in the chart or the table opens a detail panel on the right with revenue, market share, trend charts, average price, product count, and top products for that value. In the detail panel, you can toggle to New to see only products with that attribute value that are new to the market. This is useful for spotting emerging trends. For example, if "Tea Tree" is a growing ingredient in your segment, clicking it and selecting "New" shows you which new tea tree products are driving that growth.

The Attributes tab showing a breakdown by attribute value with a bar chart, attribute table, and the slide-out detail panel.

Market Analysis Attributes tab showing a breakdown by attribute value with a bar chart, attribute values table, and a detail panel showing revenue, market share trends, and top products for the selected attribute value.

How attribute revenue works

A single product can have values for many attributes. Each product is counted under every attribute value it has, which means revenue totals for an attribute can exceed total segment revenue. A product with ingredients "water" and "silica" appears in both groups, and its revenue is counted in both.

🎯 Use case: Spot opportunities for new product variants

If a color, pack size, or material drives significant revenue in the segment but your brand doesn't offer it, that's a signal. If "Green" is a top-selling color and you don't offer it, that could be an opportunity for a new variant.

A note on data accuracy in attributes

All attribute values are seller-assigned fields. Sellers enter these values when creating or updating their Amazon listings. Cobalt displays what is reported on Amazon. Because these fields are self-assigned, some sellers may enter values inconsistently or incorrectly.

For attributes like Color and Size, Cobalt normalizes common variations (for example, "Sky Blue," "Cobalt Blue," and "Ocean" are grouped as "Blue," and "Large," "L," and "Lg" are grouped together). However, normalization cannot catch every variation. Expect some outliers, especially for less standardized values.

You can verify data accuracy using the slide-out detail panel. Click any attribute value to see the products behind it. Check whether the product titles and details match the attribute. For example, if you click "Number of Items 50" and see that most products in the slide-out are indeed 50-piece products, the data is accurate for that value. Lower values like "Number of Items 1" may include products that are actually multi-packs but were labeled incorrectly by the seller.

Available attributes

The Attributes tab shows the following attributes. Some are commonly used as variation themes on Amazon (marked below). Others are descriptive attributes that provide additional market context. More attributes will be added over time. The attributes shown on the tab will vary by segment based on what is relevant to the products in that segment. Product Attributes are currently available for the US and DE marketplaces only.

Attribute Description
Color
Variation theme
Product color. Cobalt normalizes common color names ("Sky Blue," "Cobalt Blue," "Ocean" grouped as "Blue"). Some outliers may exist since these are seller-assigned values.
Size
Variation theme
Product size as name (S, M, L) or number. Cobalt normalizes common labels ("Large," "L," "Lg" grouped). Some outliers may exist for less standardized values.
Material
Variation theme
Primary material (Stainless Steel, Plastic, Rubber, Wood).
Capacity
Variation theme
Volume or storage capacity (16 oz, 1 Liter, 500 GB).
Metal Type
Variation theme
Type of metal (Gold, Silver, Sterling Silver). Primarily Jewelry.
Ingredients
Attribute
Ingredient list, each parsed individually. Common in Grocery, Beauty. Ingredient data comes from product metadata fields that sellers fill in on the backend of their listing, not from the title, bullets, or description. Revenue can be double-counted across ingredient groups since a product with multiple ingredients appears in each group.
Unit Count
Attribute
Used to calculate "Price Per Unit" on Amazon (e.g., "5.00 Count"). Not a variation theme.
Fabric Type
Attribute
Fabric used (Cotton, Polyester, Nylon). Rarely a standalone variation theme.
📌 More attributes coming soon

Additional attributes will be added in future updates based on customer feedback and category coverage.

Variant-Level Estimates

All estimates in Market Analysis are calculated at the variant level. Revenue is estimated at the parent ASIN level, then distributed across each child variant (size, color, pack, configuration) using additional data signals. The estimated revenue for each variant is calculated as its estimated units multiplied by its price. For a deeper explanation of how variant-level estimates work, see the Variant-Level Estimates article.

Each variant has its own buyable ASIN. Parent ASINs are containers that group variants together. They are not buyable or sellable on their own. A parent ASIN's revenue and unit figures represent the combined total of all variants housed under it.

What you'll see in Market Analysis: Products are shown at the variant and standalone ASIN level only. Parent ASINs are not currently displayed. If there is enough data to determine how sales split across a parent's variants, you'll see differentiated estimates for each child. If there is not enough data for individual variants, the parent-level estimate is split evenly across all variants.

📌 Parent-level view coming soon

There is currently no view that shows parent-level data with child variants listed beneath it, or a way to identify whether a product is a parent or child ASIN. A parent-level view is planned for a future update. When available, parent ASINs will represent the combined revenue and unit sales of all variants housed under them.

Variant-Level Estimates apply across all Cobalt accounts, in both Market Analysis and Market Segments. When making competitive comparisons, look at a brand's total revenue rather than any single variant's figure.

How the data works

Market Analysis provides two years of rolling historical data. Understanding how and when this data updates helps you interpret what you see and plan your analysis.

Weekly refresh

The entire dataset refreshes every Sunday. Each refresh updates the full two-year rolling history for all ASINs in the segment. When the data refreshes:

  • You gain the next available complete week of data.
  • The oldest week (from two years prior) drops off.
  • All estimates for all ASINs in the segment are recalculated and updated across the entire two-year history.

Data availability

To ensure accuracy, Market Analysis collects and processes data from multiple sources before generating estimates. A full week of activity must be complete and processed before it becomes available, which means the most recent complete week of data is always at least one full week behind the current calendar week.

Here's how that works in practice:

Data weeks run Data refreshes Most recent data available
Sunday to Saturday Every Sunday Through 2 Saturdays ago

Example: Viewing data on Wednesday, May 20th, 2026

Week Data available?
Sun May 17 - Sat May 23, 2026 (current week) Not available Week is still in progress.
Sun May 10 - Sat May 16, 2026 (last week) Not available Complete but still being processed.
Sun May 3 - Sat May 9, 2026 (most recent available) Available Became available after the Sunday, May 17th, 2026 refresh.

Your two-year history extends back from the most recent available week. In this example, your data covers from approximately mid-May 2024 through Saturday, May 9th, 2026.

After the next refresh on Sunday, May 24th, 2026, data for the week of Sun May 10 - Sat May 16, 2026 will become available, and the oldest week from two years prior will drop off.

Data availability as of Wednesday, May 20th, 2026

April & May 2026

Sun Mon Tue Wed Thu Fri Sat
12 13 14 15 16 17 18
19 20 21 22 23 24 25
26 27 28 29 30 1 2
3 4 5 6 7 8 9
10 11 12 13 14 15 16
17 18 19 20 21 22 23
24 25 26 27 28 29 30
Most recent available week    Historical data available    Not available    Today

Historical data extends back two full years from the most recent available week. April dates shown here represent a small portion of the full history.

Continuous estimate improvements

Every Sunday, all estimates for all ASINs in the segment are recalculated using the latest data and estimation models. Cobalt continuously refines its estimation approach, and when improvements are made, they are applied across the entire two-year history, not just the most recent week. This means:

  • Estimates for past weeks may change from one refresh to the next, even for historical periods.
  • If you compare data from the same historical week across two different refreshes, you may see small differences. This is expected and reflects improved accuracy.
  • The goal is to ensure the most accurate data is always available. Over time, your historical data becomes more precise as models improve.
Important for recurring reporting

If you use Market Analysis data in recurring reports or presentations, be aware that historical estimates may shift slightly between refreshes due to model improvements. This is normal and reflects increased accuracy. For the most consistent reporting, pull data on the same day each week after the Sunday refresh.

All users work from the same underlying data, processed centrally each week. The same product shows the same figures regardless of which user's segment it appears in or when the segment was created.

Frequently asked questions

Which marketplaces are available?

US, DE, UK, and MX with full historical data. CA coming soon. FR, IT, and ES will follow. Marketplace data is released only when complete historical coverage is available so you can run full year-over-year comparisons from day one. Product Attributes are currently available for US and DE only. Product Attributes for UK and MX are coming soon, with other marketplaces to follow.

Which products are included in Market Analysis?

Market Analysis covers any product that meets a minimum sales threshold (approximately 0.5 sales per day) or has been included in a segment at some point. This represents more than 95% of revenue on Amazon.

How accurate are the revenue estimates?

Cobalt's estimates are highly accurate, built on years of data modeling and refinement with a large historical data set. While all estimates should be used directionally, they provide a strong and reliable foundation for competitive analysis, market sizing, and identifying trends.

Can I use Market Analysis data in dashboards?

Not yet. Market Analysis segments cannot be used as a data source in Cobalt dashboards at this time. If you use dashboards and filter by a segment, that uses Market Segments, not Market Analysis. Dashboard integration for Market Analysis is in development.

Can I rebuild my Market Segments in Market Analysis?

Yes. If you have existing segments in Market Segments, you'll need to recreate them in Market Analysis by setting up the same filter criteria. There is no way to copy or transfer segments between the two experiences. Building fresh in Market Analysis gives you instant results, the full two-year data history, and access to Product Attributes.

Can I still access Market Segments?

Yes. During the beta, both experiences are available in your left-hand navigation. Market Segments remains unchanged and works the same way it always has, with the addition of Variant-Level Estimates. Market Segments continues to support dashboard integrations (using segments as a data source) and data export. You may notice differences in sales estimates between the two experiences even if the segment uses the same filters, because Market Analysis works with a larger pool of products and provides two years of continuously refreshed history rather than a point-in-time view.

What if a product I expect isn't showing up?

Start by checking your filter criteria to make sure the product meets all of them (category, title keywords, price range, rating count, etc.). If the product meets your criteria but isn't appearing, let the segment run through a Sunday refresh. If the product meets the filter criteria during the refresh and we were not previously collecting or generating estimates for that ASIN, it will typically appear in the following week's data.

If the product still isn't showing up after a refresh cycle, reach out to support. For Market Analysis to produce estimates for an ASIN, the product must be active on Amazon and have a Best Sellers Rank (BSR) in a parent category.

What happens after the 60-day beta?

Your CSM has either already reached out to schedule a review of Market Analysis, or will be soon. You can also reach out proactively. The beta gives you 60 days to use the feature with access to your primary L2 category. If you want continued access beyond the beta or want to add access to additional categories, have a conversation with your CSM about ongoing access.

Can I analyze categories I'm not selling in?

Yes, as long as the category is within your contracted access. You can build a segment for an adjacent category, a different price tier, or a format you don't currently sell.

Why do some brands show up under multiple names?

Brand names on Amazon are self-assigned by sellers. The same brand may appear under multiple spellings. If numbers look lower than expected, check for naming variants. Use the Brands filter to consolidate.

Can products be double-counted in the Attributes tab?

Yes. Each attribute value is parsed individually. A product with ingredients "water" and "silica" appears in both groups. Revenue totals across all values of an attribute will be higher than total segment revenue.

Why does my market share look different across segments?

Each filter set measures share within a different pool of products. An 8% share of the broad shaving razor market and a 48% share of women's disposable razors can both be true. Build segments at the levels that matter for your decisions.

Coming soon

Market Analysis is in active development. Here's what's on the roadmap. We'll update this article as new capabilities become available.

Dashboard integration — Use Market Analysis segments as a data source in Cobalt dashboards.
Parent/child product view — See parent-level data with child variants grouped beneath it, and identify whether a product is a parent or child ASIN.
Additional marketplaces — CA coming soon. FR, IT, and ES will follow.
Product Attributes for additional marketplaces — Currently US and DE only. UK and MX coming soon. Other marketplaces will be added.
Snapshots — Save point-in-time views of your segment data for comparison.
Monthly date increments — Month-level selections in the date picker for month-over-month analysis.
Additional product attributes — More attributes based on customer feedback and category coverage.
Segment sharing improvements — Cross-organization sharing and user/group-level access controls.
Improved 1P/3P display — Updates to 1P/3P metrics and how they are presented across the experience.
New analysis tabs — Additional tabs are planned, including seller breakout, keyword analysis, and review analysis.
Sellers tab — A dedicated tab for seller-level analysis is in development.
Additional product fields and metrics — More fields and data points will be added to the Products tab and exports.
Additional filters — The filter list will continue to grow.
AI integration — Market Analysis data will be layered with AI capabilities, including through AI Workflows and potentially within the feature itself.

Have questions or feedback? Reach out to your Customer Success Manager or email cobaltsupport@junglescout.com.

 

 

 

 

Was this article helpful?
0 out of 0 found this helpful