Amazon SQP Keyword Optimization: Branded Terms, Gaps, and Poor Performers

Amazon's Search Query Performance report is the richest organic signal most brand- registered sellers have – and one of the most misread. Teams export it monthly, scan impression share, maybe tweak a headline, and file it away. The operators who win treat SQP as a structured diagnostic: branded defence, hidden opportunity, and visible waste – each with different fixes.

This workflow does not require Claude or a spreadsheet model. It is the manual foundation that makes AI-assisted analysis worthwhile when you scale it. For the Claude deep-dive, see How to Analyze Your Amazon SQP Report with Claude.

Step 1: Access the SQP Report

In Seller Central, open Brand Analytics → Search Analytics → Search Query Performance. Select your reporting period (monthly granularity only) and download or work in the browser view. Brand Registry enrollment is required – without it, this workflow is not available.

The report exposes funnel metrics per query: impressions, clicks, cart adds, and purchases – each with a brand share column showing your slice relative to all brands on that query.

Step 2: Optimize Branded Search Terms

Filter the Search Query column for your brand name and core branded product lines. On branded queries you should dominate purchase share. Gaps mean someone else is intercepting shoppers who intended to find you.

Check Search Funnel – Purchases Brand Share and Search Funnel – Impressions Brand Share side by side. Healthy branded queries show high purchase share relative to impressions. If impression share is strong but purchase share lags, your listing is visible but losing the click or the conversion – different fixes.

Branded PPC is insurance here, not growth. Bid enough to defend top placement on your name while you fix the underlying content issue if one exists.

Step 3: Find High-Opportunity Keywords

Scan non-branded queries where:

• Impression share is lower than purchase share
• Impression share is still meaningful (roughly above 2.5% – ignore ultra-low-volume noise)

That pattern means shoppers buy from you when they see you – but you are not visible often enough. You are under-shelved on a query that already converts. These are the highest-ROI organic and PPC opportunities in the report because demand is proven.

Queue actions: title and bullet alignment to the query, image relevance check, then controlled budget increase on exact-match campaigns – measuring whether impression share moves next cycle.

Step 4: Check Organic Rank and PPC Performance

Before investing heavily in a high-opportunity query, validate two things:

1. Organic rank: if you already hold top-five placement, incremental PPC may buy little visibility you do not already have. Content refinement may be the lever.
2. PPC performance: pull the campaign targeting that query. Is budget capped? Is ACoS already at target with room to scale? A query can look like an SQP opportunity while ads are already maxed – the bottleneck is elsewhere.

Step 5: Find Poor-Performing Keywords

The inverse pattern flags waste: queries where impression share or click share exceeds purchase share. You are visible – sometimes highly visible – but shoppers choose someone else at the purchase step.

Common causes:

• Wrong ASIN advertised vs ASIN purchased (check purchased product reports)
• Price or review disadvantage on that specific query intent
• Content mismatch – the query implies a use case your listing does not answer

Do not reflexively cut spend. Diagnose first: a visibility-without-conversion query on a high-volume term is a content problem until proven otherwise. A visibility-without- conversion query on an irrelevant term is a negative keyword candidate.

Turning SQP Insights Into a Repeatable Queue

Run the same five steps every month when new SQP data drops – typically around the 10th–15th of the following month. Output should be a prioritised action list, not a presentation:

• Branded gaps → defence + content fixes
• High-opportunity → content + measured PPC scale
• Poor performers → diagnose ASIN mismatch, then cut or rewrite

At catalogue scale, the bottleneck is not analysis quality – it is running the same workflow consistently across every brand and marketplace. That is where continuous SQP monitoring replaces the monthly export-and-forget cycle described in why manual AI workflows break at scale.

For competitive context on branded queries you do not appear on, pair this workflow with tracking competitor branded search volume.