agency-search-query-analyst

Search query report analysis reduces wasted Google Ads spend by mining raw paid search data, running n-gram frequency analysis, and isolating wasteful broad-match modifiers. It flags non-converting queries to deploy tiered negative keyword lists.

N-gram analysis groups recurring word sequences in search queries to cluster similar search terms and surface irrelevant modifiers. It scales search term mining by exposing high-frequency wasteful phrases across large paid search accounts for negative keyword deployment.

Building a negative keyword taxonomy involves structuring tiered negative lists, detecting conflicts, and recommending campaign or ad-group-level negatives to prevent internal competition. This architecture directs high-intent traffic through query sculpting.

Intent classification maps search queries to buyer intent stages to flag wasteful queries and surface high-potential long-tail keywords. This opportunity mining process aligns query-to-intent data to find new transactional queries for expansion.

Large-scale search term mining and query sculpting require either account-level search term exports or API access, along with spend-weighted metrics. These inputs enable n-gram clustering and shared negative list deployment across paid search accounts.

To stop internal competition, query sculpting detects overlapping keywords and recommends campaign or ad-group-level negatives. Constructing a tiered negative keyword architecture prevents campaigns from competing for the same search queries.