Keyword Intent Mapping
Search terms were grouped into transactional, comparison, and discovery buckets and assigned separate budget logic.
Apparel
Amazon SEO
A premium apparel account regained profitable growth by rebuilding campaign architecture around high-intent demand pockets.
Performance Snapshot
56% HI Demand
Revenue Mix
8.1x
ROAS
+42%
CVR Lift
-38%
Wasted Spend

This apparel account had respectable top-line revenue but shrinking contribution margin month after month.
The core issue was poor intent matching between search terms, listing relevance, and bid allocation.
We treated the turnaround as an SEO-led restructuring project supported by tighter PPC routing.
Large keyword universe with mixed intent and duplicate coverage across campaigns.
Low-converting search traffic inflating spend without quality order growth.
Listing copy drifted from top-converting search language.
Category competition pushed CPC up on broad terms.
Leadership required profitability gains without reducing visibility.
Search terms were grouped into transactional, comparison, and discovery buckets and assigned separate budget logic.
Titles, bullets, and backend fields were rewritten around high-converting terms to improve both indexing and conversion.
Each major query cluster was mapped to the best-converting ASIN to reduce mismatch and lift session value.
Weekly search term insights directly informed listing updates so ranking and ad efficiency improved together.
Broad discovery was retained where useful, but negatives and exact isolation prevented recurring inefficiency.

Keyword clusters were rebuilt by intent so spending focused on purchase-ready traffic, not research traffic.
Listing relevance and index coverage improved together, lifting conversion while reducing wasted clicks.
Conversion rate improved significantly on priority ASINs.
High-intent terms contributed the majority of ad-attributed revenue.
Waste from low-intent clicks declined materially.
The account returned to profitable growth without sacrificing rank momentum.

