How to Read Amazon SQP Data (And What Most Sellers Get Wrong)

Search Query Performance (SQP) is the most underutilized dataset in Seller Central. Every brand registered seller has access to it. Almost none of them use it correctly.

Here's why that matters, how to read it properly, and what the data is actually telling you.

What SQP Actually Shows You#

SQP tracks how customers interact with search results for your brand's keywords. For each search term, Amazon shows you:

• Search Query Volume — How many times that keyword was searched in the selected period
• Impressions — How many times your products appeared in results for that search
• Clicks — How many clicks your products received
• Cart Adds — How many searchers added your product to cart after clicking
• Purchases — How many of those searches converted into a sale
• Click Share and Conversion Share — Your brand's percentage of the total clicks and purchases for that keyword

The key insight most sellers miss: SQP is not about your listings. It's about the keyword.

When you see "Click Share: 4.2%," that means 95.8% of people searching that term are clicking something that isn't you. SQP tells you where the market is going — and where you're losing.

The Four Numbers That Actually Matter#

1. Click Share vs. Conversion Share Gap#

If your click share is 12% but your conversion share is 4%, that's a listing problem. You're getting clicks, but your product page isn't convincing people to buy. Look at your main image, pricing, and review count relative to whoever is capturing the other 96% of conversions.

If your click share is 4% but your conversion share is 12%, you're punching above your weight — your listing converts well when people find you, but you're not getting enough impressions. This is often a ranking or advertising problem.

2. Branded vs. Non-Branded Search Volume#

SQP separates branded queries (searches that include your brand name) from non-branded ones (category searches like "stainless steel water bottle").

A healthy brand should see branded search volume growing over time. If it's flat or declining while your ad spend is rising, you're buying sales rather than building brand recognition.

3. Keyword-Level Purchase Rate#

Divide Purchases by Search Query Volume for each keyword. This gives you the actual purchase rate — what percentage of all searches for that term resulted in a buy, across all sellers.

High purchase rate + low click share = prioritize this keyword. There's real buyer intent here and you're not capturing it.

Low purchase rate despite high volume = the keyword might drive browsers, not buyers. Watch PPC spend carefully here.

4. Week-Over-Week Rank Changes#

SQP sorts by search frequency rank. A keyword moving from rank 1,200 to rank 400 in a category is a signal that's worth acting on weeks before it shows up in third-party tools. This is where the SQP History tool pays for itself — by pulling multiple weeks of data automatically and highlighting rank changes you'd otherwise miss.

The Three Most Common Mistakes#

Mistake 1: Looking at SQP in isolation

SQP tells you what's happening at the search query level. It doesn't tell you why. Pair it with your advertising console to understand what's paid vs. organic, and with ASIN-level data to understand which specific listings are driving your performance.

Mistake 2: Using monthly rollups instead of weekly data

Amazon's monthly SQP aggregates trend lines. Weekly SQP shows you the signal — a spike in week 3 of the month that monthly data would smooth over could be a promotion, a competitor stocking out, or a trending news story that drove category interest. Weekly is where you catch opportunities.

Mistake 3: Treating click share as a vanity metric

Click share correlates with ranking more directly than most sellers realize. Amazon's A9 algorithm uses click-through rate as a relevance signal. Systematically improving your click share on high-volume terms — through better main images, competitive pricing, or review count — is one of the few ranking levers you can pull without touching ads.

How to Export SQP Without Copy-Pasting#

Amazon's SQP interface is not designed for analysis at scale. The table is paginated, doesn't support bulk download, and resets filters on every page.

AMZBoosted's SQP Report tool automates the extraction: navigate to the SQP dashboard, click run, and receive a clean CSV of the full dataset in seconds. For historical trend analysis, the SQP History tool iterates across multiple date periods and compiles the data into a multi-sheet Excel workbook automatically.

The data itself is the same — it all comes from Brand Analytics. The difference is whether you're spending your time copy-pasting or analyzing.

A Practical Weekly SQP Workflow#

1. Every Monday: Pull an SQP Report for your brand (weekly period)
2. Compare to previous week: Which keywords improved in rank? Which dropped?
3. Flag click share gaps: Any high-rank keyword where your click share is below 5% is a target
4. Cross-reference with ad data: Are you bidding on the keywords where you have conversion share but low click share? If not, you should be.
5. Quarterly: Run an SQP History pull across the last 12 weeks to build a trend report for your brand review

This workflow takes about 20 minutes with automated extraction. Without it, it takes the better part of a morning — which is why most sellers don't do it at all.

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SQP data is available to all brand-registered sellers on the US, UK, CA, DE, FR, IT, ES, JP, AU, MX, BR, and other supported marketplaces. Data is updated weekly and has a 72-hour lag.