Market Intelligence Dashboard User Guide

The Market Intelligence dashboard is your go-to tool for understanding category-level performance on Amazon. It shows you how the top 100 best-selling products in your tracked categories are performing, including pricing, ratings, estimated sales, market share, and brand presence, giving you the competitive context to make informed decisions.

The dashboard was fully released in April 2026 and received a major v2 update in May 2026 that added Parent/Child ASIN filters, Price Bands, a Top N Brands slicer, new market visuals, and new metrics (Rank Score, Est. Market Size, Est. Market Share).

Questions this dashboard helps answer

• Which brands have the largest share of sales in my category?
• How has estimated market share evolved over the past 6 or 12 months?
• What is the typical price range for best-selling products in my category?
• Which products consistently appear in the Top 100, and which come and go?
• How does my brand's Best Sellers Rank (BSR) compare to competitors?
• Are there new brands or products gaining traction in my category?
• What is the estimated total market size (in sales) for a given category?

Before you start

What you need:

• At least one Amazon category added as a source in DataHawk (go to Sources in the DataHawk app)

Set up: Download and configure the Power BI template. See Connect to Power BI.

Data coverage: The dashboard analyzes the top 100 best-selling products in each tracked category.

Dashboard tabs at a glance

Time periods and comparisons

All three tabs use the Timeframe filter to set the date range for analysis. Market History shows a monthly breakdown across that timeframe, while Market Overview aggregates totals across the entire selected period.

Dashboard filters

All three tabs share the same set of filters:

Aggregated views filters

The dashboard provides aggregated and historical views of the following data among Category Best Sellers (top 100 selling products):

Each tab also includes a shortcut to Add Sources, letting you add more categories or products directly from within the dashboard.

Dashboard reports tab by tab

A note on unknown or missing data

In some cases, DataHawk cannot collect complete listing details for a product in a given period. When this happens, sales are still estimated using virtual rank signals, so overall market totals and trends remain accurate. However, the specific product or brand behind those sales cannot be reliably identified, and will appear as XXXXXXXXXX or Unknown.

These estimates reflect real market activity but lack item-level metadata. This is expected behavior and does not indicate a data error.

---

For analysts: data sources & methodology

Source tables and datasets

This dashboard is built on REPORTS.REPORT_MARKET_BEST_SELLER_RANK_AND_ESTIMATES (as of January 2026, replacing the previous REPORTS.REPORT_MARKET_PRODUCT_SALES_RANK_AND_ESTIMATES). For a full column reference, see the Exhaustive Column Referential.

Dashboard-specific fields

• Estimated Sales: Estimated sales for a product at the given date. Sum aggregations provided.
• Estimated Sales/Product/Month: Estimated monthly sales per product. Min, max, and median aggregations provided.
• Rank Score: Computed as 1 / BSR. Easier to aggregate and to read on trend lines than raw BSR (added in v2, May 2026).
• Presence in the Top 100: The share of time a product appeared in the Top 100 for a given category.
• Est. Market Size: Estimated total sales for a category, broken out by Category and by Price Segment (added in v2).
• Estimated Market Share: Approximate % of total category sales attributed to a brand or product. The v2 release also exposes Market Share broken out by Total Category and by Price Segment.

Top 100 coverage methodology

As of November 2025, sales estimates are run every day for all 100 ranks in every tracked category, regardless of whether the product at that rank was successfully collected. The dashboard then maps each rank to the observed product:

• Product present: Sales are computed with the product price and the row is enriched with product info (brand, name, picture, rating, etc.).
• Product missing: Sales are computed with the weekly median price of the category, and product fields fall back to null or "Unknown" (specifically product_key, channel_product_id, group_channel_product_id, rating, rating_count, picture_url, is_membership_program are null; name, brand, brand_catalog are "Unknown").

This guarantees full top-100 coverage even when the bestsellers collection had gaps, especially historically. Products in the Top 100 of a category are referred to as Category Best Sellers throughout the dashboard.

Attribution and methodology

Market data is organized around four entity layers: Marketplace (Amazon or Walmart, by country), Category (as defined by the marketplace), Brand, and Product. Estimates are computed per-product per-day, then rolled up to brand and category levels at query time.