Search Term Harvesting & Negative Bidding Engine
Turn high-converting customer queries into exact keywords while cutting wasteful ad spend.
Overview & Capabilities
Customer search behavior changes constantly. SellerSigma continuously parses your Amazon Ads Search Term Reports to identify search queries that generate sales. Converting queries are automatically harvested into Exact Match campaigns with boosted bids, while queries with zero conversions and high spend are added as negative exact/phrase match keywords to instantly stop spend leakage.
Key Benefits
Automated Keyword Promotion
Converts customer search queries with proven sales into dedicated Exact match keywords.
Immediate Spend Waste Reduction
Applies negative keywords to block non-converting search terms before they drain your daily budget.
Custom Conversion Thresholds
Set minimum order count and click criteria before harvesting search terms.
Search Term Analytics Table
Filter and analyze customer search terms across all campaigns, match types, and marketplaces.
How It Works Step-by-Step
Amazon Search Term Sync
SellerSigma automatically retrieves daily search term report data from Amazon Ads.
AI Evaluates Performance
Algorithms identify converting queries vs. wasteful non-converting search terms.
Harvest & Negative Proposals Drafted
Proposals are generated with specific bid recommendations and negative match assignments.
Apply to Amazon Ads
Approve in 1-click or let Autopilot apply negative and exact keywords automatically.
Technical Specifications
Frequently Asked Questions
Will harvesting duplicate keywords across campaigns?
No. When a search term is harvested into an Exact match campaign, SellerSigma adds it as a negative keyword in the originating Auto/Broad campaign to prevent cannibalization.
How often are search terms analyzed?
Search term reports are synced and analyzed daily.
Ready to Experience Search Term Harvesting & Negative Bidding Engine?
Get started with SellerSigma in under 5 minutes and scale your Amazon Sponsored Products automatically.