Guide Technical SEO Stable

How to run a log-file analysis

How to use server logs to see exactly how search and AI crawlers behave on your site, and act on it.

ID
SS-GD-013
Version
1.0
Confidence
Established · 82
Evidence
Moderate
Updated
2026-07-08
Review
2026-10-08

Executive summary

Server logs are the ground truth for crawler behaviour. Collect a representative window, verify which requests are genuine bots, then analyse where crawl effort lands, which valuable pages are ignored, and how quickly new content is discovered. Logs turn crawl-budget debates into evidence-led decisions.

What this helps you decide

Which crawl-efficiency and indexation changes are justified by how crawlers actually behave on your site.

Business problem

Crawl tools show what a site could offer crawlers; only server logs show what crawlers actually do. Without them, teams guess about crawl budget, missed pages and bot behaviour, and often guess wrong.

Step-by-step process

  1. 1
    Collect a representative window

    Gather at least two to four weeks of raw access logs so patterns and infrequently crawled sections are visible.

  2. 2
    Verify genuine crawlers

    Confirm bot requests by reverse-DNS or published IP ranges, because many requests spoof search-engine user-agents.

  3. 3
    Segment by bot and section

    Break hits down by crawler and by URL pattern to see where each spends its effort across the site.

  4. 4
    Find the waste and the gaps

    Identify low-value patterns absorbing crawls and, crucially, valuable pages that receive few or no crawler hits.

  5. 5
    Measure discovery and errors

    Check how long new pages take to be crawled and how many crawler requests hit 404s, 5xx errors or redirects.

  6. 6
    Turn findings into actions

    Feed the results into crawl-budget, redirect and architecture fixes, prioritising the valuable pages crawlers currently miss.

  7. 7
    Set a recurring pull

    Automate a regular log export so crawl behaviour becomes a monitored metric rather than a one-off study.

Worked example

Checklist

  • Collect at least two to four weeks of raw access logs
  • Verify bots by reverse-DNS or official IP ranges
  • Segment crawl hits by bot and URL pattern
  • Flag both wasted crawls and under-crawled valuable pages
  • Measure discovery time and crawler error rates
  • Automate a recurring log pull for ongoing monitoring

Common mistakes

  • Trusting the user-agent string without verifying the request is a genuine crawler
  • Analysing a window too short to reveal how rarely deep sections are crawled
  • Studying logs once and never turning the findings into crawl or architecture fixes

30-minute experiment

KPIs to track

  • Share of verified crawler hits on valuable pages
  • Average discovery time for new pages
  • Crawler error-response rate

FAQs

How much log data do I need?

Two to four weeks is a sensible minimum. It is long enough to reveal patterns and to include sections that crawlers visit only occasionally.

Why verify crawlers instead of trusting the user-agent?

Because scrapers and bots routinely spoof search-engine user-agents. Reverse-DNS or official IP verification ensures your analysis reflects real crawler behaviour.

Recommended next steps

    Apply the method Crawlability Framework Framework See the wider capability Crawl Optimisation Capability Decide your next move Should I allow AI crawlers? Decision

Where this fits - and what's next

The SearchScore path from a problem you feel to visibility you can measure.

    Problem Spot the pattern Method Pick the framework Do it Follow the guide Check Run the checklist Score Interactive audit TrackSearchScore Tracker StartFree audit →