Amazon Brand Analytics: A Complete Guide for 2026

Key takeaways

1. Amazon Brand Analytics (ABA) is free, first-party shopper data for brands enrolled in Brand Registry, so it is more reliable than third-party keyword estimates.

2. Search Query Performance (SQP) is the most actionable report because it shows the full funnel from impression to purchase for each search query.

3. Where the funnel breaks tells you what to fix: weak click share points to your title or image, weak cart adds to price or content, weak purchases to competitor offers.

4. Review search reports weekly and repeat-purchase and demographic reports monthly or quarterly, and tie every insight to one specific action.

5. ABA explains shopper behavior but does not change bids, so pair it with ad, pricing and inventory data before you act.

6. Atom11 puts advertising, pricing, inventory and retail data in one dashboard, with Compare mode, a Root Cause Analyzer and the Neo AI analyst, so Brand Analytics insights turn into bid, budget and automation decisions faster.

Amazon Brand Analytics (ABA) is a set of reports in Seller Central that helps brand-registered sellers understand how shoppers discover, compare, and purchase their products. It provides data on search behaviour, clicks, cart activity, conversions, repeat purchases, and product-level performance.

Yet many brand owners open it once a month, skim a CSV and close the tab. This guide explains who can access it, what each report means, how to read the Search Query Performance funnel, and how to turn the numbers into listing, advertising and product decisions you can use this week.

Quick answer: Amazon Brand Analytics is a free set of dashboards for brands enrolled in Amazon Brand Registry. It reports search demand, click and purchase share, repeat purchases, demographics and basket behavior using Amazon's own data.

What Is Amazon Brand Analytics?

Amazon Brand Analytics is the data layer for brand owners. It answers questions such as: What are shoppers typing? Which of those searches show my product? How many people click, add to cart and buy? Who else wins those clicks? Do customers come back?

Its biggest strength is the source. Before the Search Query Performance dashboard arrived, brands had to rely on ad reports or third-party estimates. ABA data comes from Amazon's own search and purchase activity, so it is a far better guide to real demand than a modeled search-volume number.

Its limit is scope. Amazon Analytics explains shopper behavior but does not replace advertising, ranking or profit reporting. Think of it as your research layer, not your control panel. We return to this in the Atom11 section below.

Who Can Access Amazon Brand Analytics?

You need three things,: a Professional selling account, Brand Representative status, and a brand enrolled in Amazon Brand Registry. Registry requires an active, registered trademark.

How to open it:

1. Enroll your trademarked brand in Brand Registry.

2. Sign in to Seller Central and confirm you hold the Brand Representative role.

3. Hover over Brands in the main menu and click Brand Analytics.

4. Open the Search Analytics drop-down to reach Search Query Performance and Top Search Terms.You can also find the Brand Analytics card under All Brand Benefits.

Can't see Amazon Brand Analytics in Seller Central? Check this first.

Amazon Brand Analytics Reports Explained

As of 2026 the suite includes six main report families: Search Query Performance, Top Search Terms, Market Basket Analysis, Repeat Purchase Behavior, Item Comparison and Alternate Purchase, and Demographics. Search Catalog Performance sits alongside them in the search analytics group. Amazon has also added Customer Loyalty Analytics and Customer Journey Analytics, so check your own menu for the current list.

Search Query Performance (SQP)

Amazon launched SQP in October 2022. It ranks the top 1,000 queries by a search query score and offers a Brand view and an ASIN view. For each query you see search volume, then your share of impressions, clicks, cart adds and purchases. Because it shows the entire funnel, it is the report most worth your time. The next section shows how to read it.

Top Search Terms

This report ranks terms by search frequency rank (SFR). Rank 1 is the most-searched query in the marketplace that week. It also shows which products win clicks and conversions for each term, even when they are not yours. Use it to spot rising themes, find competitors you did not know you shared a shelf with, and sanity-check your keyword list.

Search Catalog Performance

Where SQP is query-first, this dashboard is product-first. It shows impressions, clicks, click-through rate, cart adds, purchases, conversion rate and median price for each ASIN. Use it to find which products have a funnel problem before you dig into the queries behind it.

Customer behavior reports

Market Basket shows what else buyers add to the cart, which suggests bundles and Sponsored Display targets. Item Comparison and Alternate Purchase shows which competitor ASINs shoppers view or buy instead of yours. Repeat Purchase Behavior shows reorder patterns, which helps you decide on Subscribe & Save and replenishment campaigns. Demographics shows who your buyers are, so your images and copy match your real audience rather than your assumed one.

Which Reports Earn Your Time

Not every dashboard deserves the same attention. Rank them by how directly they lead to a decision:

 Weekly, highest value: Search Query Performance and Top Search Terms. These show demand and where your funnel breaks.

 Monthly, diagnostic: Search Catalog Performance, Repeat Purchase Behavior and Item Comparison. Use them to find product-level problems and replenishment opportunities.

Quarterly, strategic: Market Basket, Demographics and the loyalty and journey reports. They change slowly and inform bundles, creative and audience choices.

Know the limits: most dashboards refresh about every three days and keep roughly three years of history. Demographics is US-only and needs a minimum number of customers (around 100) before it shows data.

Treat week-to-week swings as noise and multi-month or multi-quarter trends as signal.

How to Read Search Query Performance Like a Funnel

Compare your share at each stage. A gap between two stages shows where shoppers drop out.

Worked example (illustrative numbers). A bamboo cutting board brand sees 12% impression share but only 4% click share on the query large cutting board. The product is visible but not chosen. The team tests a new main image showing the board's actual size beside a knife, and trims the title. Two weeks later, click share on that query reaches 7% while impression share stays flat. The fix came from reading the gap, not from raising bids.

A note on accuracy. Treat SQP as directional. It will not reconcile perfectly with your sales reports, so track week-over-week trends instead of chasing exact totals.

Attribution warning: why SQP never matches your sales reports

SQP credits a purchase to a search query only when the purchase happens soon after that search, roughly within a day. A shopper who searches today and buys three days later drops out of the SQP purchase count, yet still appears in your Business Reports and in 7- or 14-day PPC attribution. That is why the numbers never reconcile. Use SQP for the shape of the funnel and the direction of share, and use Business Reports and ad reports for absolute totals.

How to Turn Brand Analytics Into Action

1. Improve listings

Pick queries where you have strong purchase share or high volume and make sure they appear naturally in your title, bullets and backend terms. Do not stuff every popular term. Relevance wins: keyword research cannot rescue a weak listing.

2. Sharpen advertising

SQP shows which queries lead to purchases, not just clicks. Add proven queries to exact-match campaigns. Negate queries that draw clicks but never convert. Where your organic click share is already strong, consider lowering bids and moving budget to terms where you lack visibility.

Use the conversion data to set a bid ceiling. Because ACoS equals CPC divided by (conversion rate x average order value), you can rearrange it:

Max CPC = target ACoS x conversion rate x average order value

Example: with a $40 order value, a 10% conversion rate and a 25% target ACoS, your break-even bid is 0.25 x 0.10 x $40 = $1.00. Bidding above that on this query loses money against your target. Competition for these slots keeps rising too: Amazon's advertising segment grew 22% in Q1 2026.

3. Guide product decisions

High-volume queries where no brand holds more than a modest click share often signal an underserved need. Market Basket data reveals natural bundles, and Repeat Purchase data shows whether a replenishment offer is worth building.

4. Defend your brand terms

Check the queries that contain your brand name. If competitors appear there, they are capturing demand you already earned. Respond with Sponsored Brands and branded exact-match defense.

What Amazon Brand Analytics Can't Tell You

ABA shows what shoppers did. It does not show why your numbers moved, and several causes sit outside the reports:

• Inventory: a stock-out drops impressions and clicks, yet nothing in ABA says you were out of stock.
  
  

• Price and Buy Box: a competitor price cut shows up as lost purchase share with no explanation.
  
  

• Ad spend and ACoS: SQP does not report your cost, so you cannot judge profitability from it alone.
  
  

• Competitor sales: you see share of clicks and purchases, not their revenue.
  
  

This is why teams that win combine ABA with advertising, pricing and inventory data in one place.

A Click-share Drop Amazon Brand Analytics Cannot Explain

Illustrative numbers. A stainless-steel water bottle brand opens SQP on Monday and sees impression share on insulated water bottles fall from 11% to 6% over two weeks, with purchase share falling alongside it. ABA confirms that something changed. It cannot say what. Here is the workflow to find out:

1. Confirm the drop. In SQP ASIN view, check which ASIN and which funnel stage moved first.

2. Check inventory. Was the top variant low or out of stock for several days? Stock-outs suppress impressions.

3. Check price and Buy Box. Did your price, a competitor price or the Buy Box owner change?

4. Check advertising. Did a budget run out, a campaign pause or a bid change in that window?

5. Check competitors. Look for a new launch, coupon, deal or surge of fresh reviews on rival listings.

6. Fix one thing and re-check. Change a single variable, then watch SQP share for one to two weeks.

In this example, the cause turned out to be a four-day stock-out on the best-selling size, during which ads kept running and the Buy Box went elsewhere. Doing this by hand means jumping between SQP, inventory, pricing and ad reports. In Atom11, Compare mode lines up the two periods side by side and the Root Cause Analyzer highlights the metrics that moved, so the investigation takes minutes instead of an afternoon.

Amazon Now Runs Two Engines, and Your Dashboard Only Sees One

Traditional keyword search, often called A9, matches queries to listings and still drives organic rank. Brand Analytics reports on that behavior. Alongside it, Amazon now runs an AI shopping layer. Rufus, Amazon's AI shopping assistant, answers shopper questions before they scroll a results page, and in 2026 Amazon began folding Rufus and Alexa+ into Alexa for Shopping, placed in the search bar. Behind it sits COSMO, a knowledge graph that maps products to uses, audiences and relationships.

The catch for sellers: a listing can rank well on keywords yet give the AI little to reason about if its use cases, audience, materials and compatibility are not stated on the page. And as of this writing, Seller Central does not break out assistant-driven sessions, so that traffic is blended into your totals and ABA cannot isolate it.

Why Your Brand Analytics Looks Healthy While Your Sessions Slide

A common pattern: SQP shows steady impression and click share, yet sessions and sales slide. ABA measures keyword-search behavior, so it can look fine while demand shifts toward AI-assisted discovery, or while price, stock or ad changes do the damage. Many sellers respond by buying more traffic or rewriting copy without knowing which change actually helps.

Signals worth watching:

● Conversion falling while traffic holds or rises, which can mean more exploratory, lower-intent visits.

● Strong SQP click share but weaker cart-add share on conversational long-tail queries.

● Sessions down week over week with no matching drop in ABA impression share.

What to do: compare a before and after period side by side across sessions, conversion, price, stock and ad spend. Then audit the listing for AI readiness: state who the product is for, its use cases, sizes, materials and compatibility in the title, bullets and description, and answer the questions shoppers are likely to ask. Change one thing at a time, and set an alert (for example, conversion down 10% over 7 days) so you catch the next slide early. Atom11's Compare mode, Root Cause Analyzer and Neo co-pilot make that before-and-after comparison a few clicks instead of a spreadsheet project.

How Atom11 Turns Brand Analytics Insight Into Ad Action

Atom11 is a full-funnel, retail-aware Amazon PPC software for brands, sellers and agencies, built by former Amazon employees. More than 2,000 brands and agencies across 18+ countries run their Amazon advertising on it.

To be clear about roles: Atom11 does not replace Amazon Brand Analytics. You still use ABA for search research. Where Atom11 helps is the step after the insight, when you need to see the ad and retail side of the same story and then act on it, all from one login.

Two customer examples show the pattern. Beco set price alerts on its three main competitors. When one raised its price, the team lifted bids 30% on that listing in one click; daily orders rose from about 8 to about 24 and ACoS fell from 19.4% to 12.2% for roughly a week. Gala used Amazon Marketing Stream data and flexible bid, budget and placement automations to cut ACoS by 40% over six months.

It also helps that automation is not a black box. Atom11's Performance Monitor shows keyword performance before and after each automation, so you can see whether a change worked.

Want to see this on your own account? Contact the Atom11 team for a walkthrough, or start the seven-day trial listed on the Atom11 site.

Conclusion

Amazon Brand Analytics is the closest thing sellers have to a window into real shopper behavior, and it costs nothing beyond Brand Registry. Start with Search Query Performance, read the funnel stage by stage, and keep a weekly routine that ends every review with one action. Then remember the limits: ABA explains search behavior, not stock, price or spend. Pair it with ad, retail and pricing data so you can tell why a number moved and respond quickly. If you want a single dashboard for that second half of the job, the Atom11 team is happy to show you how it works. Book a demo today!