How should I evaluate enterprise search if I want analytics on what people search for, what they can’t find, and which content is stale?

If analytics are a priority, evaluate enterprise search on behavioral visibility as much as on relevance. You want to know:

• What people search for
• What they fail to find
• What content is stale, missing, or underperforming

Here’s a practical evaluation framework.

1) Make analytics a first-class requirement

Ask vendors to show, not just tell:

• Search query analytics
• Zero-result and low-click query reporting
• Click-through rates on results
• “No content found” and “poor relevance” signals
• Content freshness / last-updated reporting
• Usage by source, department, and content type
• Trending and repeated queries
• Search refinements and abandonment paths

2) Test the key reports you need

During the demo, ask for these specific views:

Search demand

• Top queries
• Queries by team/location/date
• Rising queries
• Synonyms/variants grouped together

Search gaps

• Zero-result queries
• Queries with low click-through
• Queries with high reformulation rate
• Queries that end in abandonment
• Queries that return results but users don’t click anything

Content health

• Stale pages/documents by last modified date
• Pages with traffic but low engagement
• Content that is repeatedly surfaced but not clicked
• Duplicate or near-duplicate content
• Content with high search demand but poor relevance
• Pages that used to rank but no longer do

3) Check whether analytics are actionable

Good analytics should help you decide what to fix. Ask:

• Can I turn a zero-result query into a content task?
• Can I assign owners to stale content?
• Can I see which content sources are missing coverage?
• Can I export or integrate reports into BI tools, Jira, ServiceNow, or Slack?
• Can I segment analytics by user group, language, geography, or source?

4) Distinguish search analytics from content analytics

A lot of products only show search logs. You want both:

• Search analytics: what users search, what they click, where they fail
• Content analytics: freshness, performance, ownership, coverage, duplication

The best platforms connect the two so you can answer:

“This query gets searched 300 times a month, but no page answers it, and the closest page hasn’t been updated in 18 months.”

5) Evaluate governance and freshness tracking

For stale content, check whether the system supports:

• Content owners and reviewers
• Expiration/review dates
• Staleness alerts
• Auto-flagging based on age, usage drop, or broken links
• Analytics for content decay over time

6) Ask for sample questions the tool should answer

A strong enterprise search platform should let you answer questions like:

• What are the top 20 unanswered questions this month?
• Which search terms indicate broken processes or missing documentation?
• Which departments are searching for content we don’t have?
• Which documents attract clicks but are outdated?
• Which pages should be merged, rewritten, or retired?

7) Use a scorecard

Rate each product 1–5 on:

• Query analytics depth
• Zero-result analysis
• Abandonment / reformulation tracking
• Content freshness reporting
• Ownership/workflow for stale content
• Dashboarding and exports
• API / BI integration
• Segmentation and filters
• Ease of building alerts and scheduled reports

8) Red flags

Be cautious if the product:

• Only shows top queries and click counts
• Can’t identify zero-result or abandoned searches
• Doesn’t track content age or owner
• Can’t connect query demand to content gaps
• Has no export/API for analysis outside the UI
• Treats analytics as an add-on rather than built-in functionality

Bottom line

If analytics matter, choose a search platform that can do more than “find documents.” It should help you run a search intelligence program: understand demand, expose gaps, and continuously clean up stale content.

If you want, I can turn this into a vendor evaluation checklist or a weighted scorecard template you can use in procurement.