Finding Striking Distance Keywords in Google Search Console
“Striking distance” keywords are search queries for which your domain currently ranks on the second page of Google (typically positions 11 through 20). These queries represent a state of high potential but zero visibility; you are mathematically close to the first page, yet receiving a negligible Click-Through Rate.
Prioritizing these queries is a foundational SEO strategy. Advancing a URL from position 12 to position 8 requires significantly fewer resources than establishing a brand new page for a highly competitive term. The search engine already recognizes your document’s relevance; it simply requires an incremental optimization push to cross the page-one threshold.
The Bottleneck in Native Analysis
To isolate these opportunities within the native Google Search Console interface, SEOs must apply manual position filters, export query data, and cross-reference those queries with their respective ranking URLs. This workflow is highly inefficient and difficult to execute at scale across a large content portfolio.
Streamlining Incremental Optimization
Kong Metrics systematically extracts and maps these high-potential opportunities, transforming raw data into an actionable optimization queue.
1. Automated Filtering Parameters
The platform automatically isolates your portfolio to display only queries oscillating between positions 11 and 20 that also meet a minimum impression volume threshold, ensuring you aren’t optimizing for zero-volume terms.
2. Direct URL Mapping
Rather than forcing you to guess which page is ranking for a query, the tool maps striking distance queries directly to their active URLs. This provides your editorial team with the exact target page requiring on-page enhancements or internal linking.
3. Traffic Yield Prioritization
By sorting these opportunities by total impression volume, you can accurately forecast which position 11 keywords will yield the highest absolute traffic increase upon breaching the first page, allowing for highly efficient resource allocation.