Users Can't Find Content on Your Website — Here's How to Prove It
When people tell you they can't find something on your site, don't dismiss it as user error. Their searches leave a trail — and that data proves whether your content is discoverable or hidden behind a broken search experience.
Zero-result queries tell a story
A stream of zero-result queries is the clearest signal that search isn't working. Look beyond raw counts: group similar zero-result queries, track them over time, and surface the most common phrases. These queries reveal missing pages, poor indexing, or mismatches between how users phrase their needs and how content is written. Actionable next steps: capture and export zero-result queries weekly, create a 'content request' backlog for high-frequency terms, and add synonyms or redirects for obvious variations.
Support tickets expose hidden content gaps
Support teams repeatedly answer the same questions because search fails to surface the right page. Mine ticket titles and full-text transcripts for common asks, then map those asks to site content. If answers exist but users can't find them, improve page titles, metadata, and search ranking rules. If answers don't exist, prioritize content creation based on ticket frequency and estimated user impact.
Measure what matters — task completion, not clicks
Clicks are easy to measure but misleading. A user clicking a result doesn't mean their problem is solved. Track downstream signals: did they complete the task (cancel subscription, download invoice, find API key), did they return to search within the same session, or did they open a support ticket after searching? Define a small set of success metrics — zero-result rate, time-to-success, repeat-search rate, and support escalation rate — and report them to product and content teams.
Segment your search data for better diagnostics
Not all search failures are equal. Segment queries by device, account type (new vs returning users), geolocation, and language. New users often need setup and onboarding content; power users look for advanced docs. Different segments reveal different priority areas and inform where to apply manual boosts or create targeted content.
Turn queries into product signals
Search logs are early-warning indicators. A sudden spike in queries about "downgrade plan" or "payment failure" may indicate a product regression or UX change. Feed frequent queries into your roadmap and incident workflows so product teams can act on usability problems before they become support storms.
Search analytics are a direct line to what users actually want. Treat zero-result queries, support trends, and task-completion metrics as product telemetry: collect them, prioritize fixes, and measure improvements. Small changes to titles, synonyms, and ranking rules often produce outsized gains in discoverability and reduce support load.
Find the queries where users drop off and turn them into fixes.
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