Search Query Performance: How to Read and Use the Amazon Report

Search Query Performance (SQP) is a Brand Analytics report in Amazon Seller Central. For each search query, it shows how many shoppers saw a brand’s ASINs, clicked them, added them to the cart and bought them, and how those numbers compare with the total for the query. Brands use it to find demand, locate the stage where shoppers drop off, and decide whether the fix belongs in the listing, the offer, inventory or advertising.

This guide explains what the report contains, who can open it, how to read it, and how to connect each finding to an action. It also states where the report stops being useful.

TL;DR

• SQP reports query-level impressions, clicks, cart adds and purchases, and shows the brand’s share of each step against the total for that query.
• Access requires a Professional selling account and Brand Representative status for a brand enrolled in Amazon Brand Registry.
• The core diagnostic compares share at consecutive funnel stages for one query and one ASIN set over one period.
• SQP describes total market behavior. Amazon Ads search-term reports describe only queries that produced an ad click. Each report has its own job.
• Every gap should map to a defined action, and the next comparable period should be checked to see whether it worked.

Table of Contents

• What the Search Query Performance report shows
• Who can access the report
• Reporting periods and data rules
• A practical workflow for reading SQP
• The funnel share diagnostic
• Turning findings into listing actions
• Turning findings into PPC actions
• Search Query Score and other cautions
• Common mistakes
• Our perspective
• How Sellucent supports SQP-based growth
• Preparing an SQP review: a checklist
• FAQ
• Sources

What the Search Query Performance report shows

According to Amazon’s Brand Analytics guidance, Search Query Performance shows query-level impressions, clicks, cart adds and purchases. Brands use it to identify search demand and the points where the funnel loses shoppers.

The Selling Partner API reference for analytics reports documents the fields in detail. For each query, the report returns:

• The search query, a Search Query Score and Search Query Volume.
• Total query impressions, the ASIN’s impressions and its impression share.
• Total clicks, the ASIN’s clicks and its click share.
• Cart adds and cart-add share.
• Purchases and purchase share.
• Total and ASIN rates, and median prices.

Two features of this structure matter. First, the report gives both the absolute count and the share. Counts show scale. Shares show position against every other product shoppers saw for the same query. Second, the funnel is sequential. Impressions come before clicks, clicks before cart adds, and cart adds before purchases. This order is what makes diagnosis possible.

How SQP differs from related reports

Brand Analytics contains several reports with similar names. Amazon presents Search Catalog Performance as the complementary ASIN-level view and Top Search Terms as broader marketplace search activity. SQP sits between them. It is tied to specified ASINs but reports against the full query.

It also differs from advertising data. Amazon Ads search-term reports describe shopper queries that produced at least one ad click. SQP is market context for selected ASINs, including organic and paid results together. The practical split is simple:

Using SQP to set bids, or using ad reports to judge total market share, produces wrong conclusions in both directions.

Who can access the report

Amazon states that access requires a Professional selling account and Brand Representative status for a brand enrolled in Amazon Brand Registry. Sellers without a registered brand cannot use the ASIN-level data in the usual way. Brand enrollment is therefore the first step for any seller who wants this data.

Availability is broad. Since February 26, 2025, the Reports API includes Search Query Performance and Search Catalog Performance report types. Amazon lists availability across North America, Europe, the Middle East, India, Singapore, Japan and Australia, including the United States and the United Kingdom. The API output is JSON, and the report is requested rather than scheduled.

Sellers in different marketplaces should keep their analysis separate. A query in the US and the same query in the UK describe different shoppers, prices and competitors.

Reporting periods and data rules

The API documentation supports weekly, monthly and quarterly periods. A request cannot span multiple periods. Monthly requests can cover up to 17 months. The ASIN input is required and limited to 200 characters.

Period boundaries are strict. For a weekly report, the start date must be a Sunday and the end date a Saturday. A request that crosses a boundary is invalid.

These rules lead to three working habits:

1. Pick one period type and keep it. Compare weeks with weeks, months with months.
2. Keep the ASIN group stable. Adding or removing ASINs changes the shares and makes before-and-after comparisons unreliable.
3. Keep the marketplace constant. Do not merge US and UK exports into a single sheet.

The unit of analysis, as Amazon’s design makes clear, is a query evaluated in relation to selected ASINs and a defined reporting period. Any analysis that mixes those three elements is unsound.

A practical workflow for reading SQP

The following sequence turns an export into a prioritized action list.

1. Confirm eligibility. Check Brand Analytics access and Brand Registry status for the brand.
2. Export a consistent period. Choose weekly, monthly or quarterly and record the dates.
3. Segment by ASIN and query. Review each ASIN, or each set of close variants, separately.
4. Rank by opportunity. Sort queries by volume, then by the gap between the brand’s share at different funnel stages.
5. Map each gap to an action. Assign it to the listing, the offer, inventory or PPC.
6. Recheck. Review the next comparable period to see whether the share moved.

Step 4 deserves attention. A query with very high volume and a tiny impression share is a visibility problem. A query with moderate volume and a large gap between click share and purchase share is a conversion problem. The first needs reach. The second needs a better detail page or offer. The same budget does not fix both.

Quarterly versus weekly views

Weekly data shows short-term movement, such as the effect of a price change or a competitor promotion. Quarterly data smooths noise and suits strategy and listing decisions. Teams that react to every weekly swing often change listings too often to learn anything. A reasonable pattern is quarterly for planning and weekly for monitoring a specific change.

The funnel share diagnostic

The most useful practitioner method compares share at consecutive funnel stages for the same query. This is a diagnostic framework, not proof of any one cause. It narrows where to look.

A worked example with illustrative numbers

The numbers below are invented to show the method. They are not data from any account.

Suppose a query has 100,000 total impressions in a month. An ASIN holds 2,000 of them, an impression share of 2%. The ASIN’s click share is 6%, and its purchase share is 7%. The product is converting better than its visibility. Shoppers who see it choose it at a higher rate than its presence in results would predict. The gap sits at the top of the funnel, so the action is to increase reach through advertising, indexing or inventory depth.

Now reverse the case. The ASIN holds a 15% impression share, a 4% click share and a 2% purchase share. It is visible but is not drawing clicks, and those who click do not buy. The main image, title and price need review first, then the detail page and offer.

The same logic applies to every query row. The work is to find the stage where share falls and ask what a shopper sees at that stage.

Turning findings into listing actions

For listing optimization, Amazon recommends using Search Query Performance to identify the keywords customers use to find a brand, then using the funnel metrics to improve the shopping experience and capture profitable trends. Amazon also reports a customer example in which quarterly sales rose by over 40% after optimizing for best search terms. That is an Amazon-published customer statement and not a universal expected result.

In practice, listing actions from SQP fall into four groups:

• Title and bullets. Add or reorder language so the listing matches high-volume queries where impression share is low but relevance is real.
• Main image and secondary images. Address weak click share on queries where the product is visible.
• Detail page content. Respond to weak cart-add or purchase share with clearer claims, comparison content and answers to common objections.
• Backend terms and variations. Check that variations and attributes support the query language shoppers use.

A listing change should be tied to a specific query group, and the change should be recorded with a date. Without that record, the next period’s data cannot be read against anything.

Turning findings into PPC actions

SQP does not set bids. It tells advertisers where paid effort is likely to pay off and where it is not.

• High volume, low impression share, healthy conversion. These queries are candidates for added ad coverage. Conversion share above impression share suggests the product wins when it is seen.
• High volume, strong impression share, weak purchase share. More spend here amplifies a conversion problem. Fix the listing or offer before increasing bids.
• Queries where the brand already holds a strong share. These may justify defensive coverage, but the cost should be weighed against organic strength.

After SQP identifies the priority queries, the Amazon Ads search-term report shows which of them already trigger clicks, what they cost and which related terms need negatives. The two sources work as a pair. Sellucent’s PPC reporting and campaign management pages describe how this paid-side work is organized.

Search Query Score and other cautions

Search Query Score appears in the report, but it should not be treated as a universal keyword-quality score or as a ranking position. Amazon documents it as a report field alongside query volume and funnel metrics and does not publish a public formula. The underlying volume, rates, counts and shares are safer to rank by.

Other limits to keep in mind:

• SQP shows behavior for queries and ASINs Amazon reports. It does not explain why a shopper acted as they did.
• Share changes can come from competitors as much as from the brand’s own changes. A drop in share may reflect a rival’s promotion.
• Small-volume queries produce unstable shares. A few purchases can swing a percentage.
• Variations between ASIN sets make period-to-period comparisons weak. Keep the set constant.
• A correlation between a listing change and a share change is not proof of cause. Record other changes made in the same window, such as price, promotions or stock-outs.

Common mistakes

Several errors recur in SQP analysis:

1. Treating the report as a keyword list. Amazon’s own framing points to a decision system. Query demand shows opportunity. The funnel stages show where momentum is lost.
2. Mixing ASINs, marketplaces or periods. The API design assumes one defined combination at a time.
3. Using ad data to judge market share. Ad search-term reports cover queries with at least one ad click and miss the rest of the market.
4. Acting on a single week. Short windows exaggerate noise.
5. Skipping the recheck. A change that is not measured in the next comparable period teaches nothing.

Our perspective

We treat SQP as one input in a larger diagnostic, not as a stand-alone dashboard. The report is strongest when it is joined with advertising data, listing content, pricing and inventory. A share gap on its own has several possible causes. The purpose of the diagnostic is to narrow those causes before money or time is spent.

Sellucent builds growth systems for Amazon sellers by combining AI analytics with hands-on expertise. Our work addresses three recurring problems: inefficient ad spend, limited visibility and slow sales growth. SQP data is relevant to all three. It shows where visibility is missing, where conversion is weak and where advertising should be added or reduced. We report an average return on ad spend improvement of 68% and a revenue increase of 47% across clients, and we treat those figures as averages, not guarantees for any single account.

Our approach to this report has three rules. Compare like with like. Assign every gap to one owner and one action. Recheck in the next period before drawing conclusions. Teams that follow these rules tend to stop debating the data and start testing changes.

— British

How Sellucent supports SQP-based growth

Sellucent offers Amazon growth consultancy covering precision PPC, listing optimization, creative and full-funnel growth. For sellers who want an outside view of their account before committing to a program, the Sellucent audit provides diagnostic insight into ad spend, visibility and sales performance. Sellers who already know their gaps can review listing optimization directly, or read the case studies to see how engagements are structured.

Pricing is not published on the site. The next step is to request an audit and discuss scope.

Preparing an SQP review: a checklist

Before the first export, confirm the following:

• The brand is enrolled in Brand Registry, and the user holds Brand Representative status.
• The ASIN list is final for the review period and has no stock-outs that distort the data, or those are noted.
• A single marketplace is selected.
• The period type and dates follow the API boundaries, with weeks running Sunday to Saturday.
• Price changes, promotions and listing edits during the period are logged.

During the review:

• Sort queries by volume and mark the top group for each ASIN.
• Calculate or read the share at each funnel stage.
• Label each query with the pattern it matches.
• Assign one action per pattern and one owner.

After the review:

• Apply changes in a controlled sequence, not all at once, where practical.
• Pull the next comparable period.
• Compare the same queries and ASINs, and record what moved.

FAQ

What is the Search Query Performance report on Amazon?

It is a Brand Analytics report that shows query-level impressions, clicks, cart adds and purchases for a brand’s ASINs. It also shows the brand’s share of each step against the total for the query. Brands use it to find demand and locate funnel drop-offs.

Who can use the SQP report?

Amazon states that access requires a Professional selling account and Brand Representative status for a brand enrolled in Brand Registry. Sellers without a registered brand do not get the usual ASIN-level access. Enrolling the brand is the first step.

Is SQP the same as the Amazon Ads search-term report?

No. SQP is a Brand Analytics report that gives market context for specified ASINs. Amazon Ads search-term reports describe shopper queries that produced at least one ad click. Use SQP to diagnose funnel capture and the ads report to manage bids, targeting and negatives.

Can the report be downloaded through the API?

Yes. Amazon added the report type to the Reports API on February 26, 2025. The output is JSON, and the report must be requested, since it cannot be scheduled. Weekly requests must start on a Sunday and end on a Saturday.

Should Search Query Score decide which keywords to target?

No. Amazon lists the score as a report field but does not publish a formula. Rank queries by volume, rates, counts and funnel shares instead, and treat the score as secondary context.

Sources

• Amazon Brand Analytics, Sell on Amazon
• Analytics Reports, Selling Partner API documentation
• Analytics Reports, Selling Partner API documentation (period rules)
• Update: Added new Search Query Performance and Search Catalog Performance Analytics Report types

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