Discover how Amazon sellers are using Search Query Performance data to increase impressions, clicks, and conversions across their product catalog.
SQINT pulled the ASIN's top queries from the SQPR and showed the product ranked #6+ for several queries but had less than 2% click share. The title and images were misaligned with buyer expectations. The AI-generated listing rewrite included top-converting keywords and improved visual relevance.
SQINT revealed that several previously top-converting keywords had been overtaken by competitors, with the ASIN dropping to position 12+. CTR had dropped due to outdated images and a weaker title. The tool generated new A9-optimized content based on the highest recovery-potential search terms.
SQINT analyzed ASIN-level query data for each child listing. It uncovered that one color ("Sage Green") had just 0.3% click share for "sage bridesmaid robe" while a competitor had over 3%. The listing didn't mention "sage" anywhere — title, bullets, or backend.
The SQPR revealed high-converting queries with strong impression volume that the ASIN didn't rank for. SQINT generated AI-driven listing copy focused on urgency-based seasonal keywords and suggested backend terms with month/year modifiers to match time-sensitive searches.
SQINT identified high click share keywords with poor conversion share — highlighting wasted spend. It surfaced long-tail, high-converting keywords already ranking organically and generated SEO-optimized rewrites to align with top-converting terms.
SQINT segmented keywords by performance: high click + high conversion (reduce PPC), low click + high conversion (boost with PPC), and high click + low conversion (cut). This gave the seller a clear map of where spend actually influenced ranking.
Using post-season SQPR data, SQINT identified high-converting terms the seller missed, highlighted overlooked low-cost keywords, and compared performance against top 5 competing ASINs to find gaps in ranking, CTR, and conversion share.
SQINT revealed click share was steady but conversion share had dropped. Competitor analysis pinpointed: outdated main image, competitors bundling extras, and the title lacking trending terms like "2025 calendar" and "chore chart combo."
SQINT broke down A9 ranking inputs: click share stayed consistent while conversion share dropped for 4 key terms. Competitor analysis showed lower pricing, lifestyle thumbnails, and year-specific titles. The tool flagged that title and image optimization should be tested first — before discounting.
SQINT segmented keywords into Growth (high impressions, lower conversion, expensive) and Profit (lower volume, high conversion, low CPCs, niche terms). It visualized ROI potential and provided AI-optimized listings to support profitable organic rank improvements.
SQINT identified the core problem: low impression share on high-volume queries. The listing converted well when seen — it just wasn't being seen. The title lacked trending keywords like "USB rechargeable lantern" and "hurricane prep light." SQINT recommended targeted low-budget PPC and weekly SQPR tracking.
SQINT segmented keywords into three buckets: Scale Up (high impressions, strong CVR), Organic Only (already high rank, no ads needed), and Cut (high clicks, poor conversion). The tool provided visual insights and specific budget recommendations per keyword.