Log files are where you stop guessing and start seeing what search engines actually do on your site.
This guide walks you through a practical, second person approach to log file analysis for SEO. You will learn how to spot crawl waste, uncover hidden opportunity, and turn a messy pile of server requests into a clear plan of action.
If you want the broader audit context too, it pairs nicely with Totally Digital’s SEO audit content and services.
What log file analysis is
Your server logs record requests made to your website. That includes humans, bots, uptime monitors, scrapers, your own team, and search engine crawlers.
When you analyse logs for SEO, you are usually trying to answer questions like:
- Which URLs does Googlebot actually crawl, and how often?
- How much crawl is going to redirects, 404s, parameter URLs, and duplicate paths?
- Are important pages being crawled often enough, or at all?
- Are bots hitting slow pages, erroring, or timing out?
- Are there sections of the site that are effectively invisible to search engines?
Google defines crawl budget as the set of URLs it can and wants to crawl, shaped by crawl capacity and crawl demand. That framing matters, because it means you can influence both sides by improving site health and making the right URLs more desirable to crawl.
Why this matters more for UK businesses than you might think
In the UK, digital competition is intense in almost every vertical. ONS retail data regularly shows online taking a material chunk of total retail sales, for example 28.6% of retail sales were online in November 2025. That is a big slice of demand being decided by search, brand, and performance.
And while your site might feel fast on a decent connection, crawling is not “a normal user on fibre”. Crawlers are ruthless and repetitive. They will happily burn through your weak spots at scale, especially on large sites with filters, internal search, and messy parameter behaviour.
Ofcom reports the UK average download speed rising to 223 Mbit/s in 2024, driven by more full fibre availability and take up. Users are moving faster, expectations rise, and slow back end responses stand out even more.
When log file analysis is worth doing
You do not need log files for every site. But you almost always want them if any of the following apply:
- You have 10,000 plus URLs, or rapidly growing indexable pages
- You run ecommerce with faceted navigation and filters
- You have a publisher style archive, tags, author pages, and pagination
- You have a large blog with years of content and lots of internal search
- You have frequent deployments, migrations, or URL structure changes
- You see spikes in crawl requests, or Search Console crawl stats look odd
- You have ongoing indexation issues, despite “doing the basics”
If you are in one of those buckets, logs become one of the quickest ways to find out where SEO effort is being wasted.
What you need to get started
1) Access to logs
You typically need one of these:
- Raw server logs from your hosting provider (Nginx, Apache, IIS)
- CDN logs (Cloudflare, Fastly, Akamai)
- Load balancer logs
- A managed platform export (varies by host)
If you are not sure where to start, your dev team will. If you do not have a dev team, this is exactly where a technical SEO agency saves you time.
2) A timeframe
For most audits, aim for:
- 30 days to spot patterns
- 60 to 90 days for seasonality and stability
- Shorter windows (7 to 14 days) if you are investigating a specific incident
3) Tools
You can do log analysis a few ways:
- Excel or Google Sheets (fine for small sites, not fun for big ones)
- Screaming Frog Log File Analyser (practical for many SEO teams)
- BigQuery, SQL, and Python (great at scale)
- Dedicated log platforms like Splunk, Elastic, Datadog (if the business already uses them)
If you are building an SEO toolkit, it helps to know costs in real money. A Screaming Frog SEO Spider licence is listed at £199 per user per year, and the free version is limited to crawling 500 URLs.
That matters because log work is rarely one and done. You want a repeatable workflow you can run monthly or quarterly.
What to look for inside a log line
Every log format is slightly different, but you are normally looking for:
- Timestamp
- Requested URL path (and query string)
- Status code (200, 301, 404, 503)
- User agent (to identify Googlebot, Bingbot, etc.)
- IP address (sometimes useful, but be careful with privacy)
- Bytes served
- Response time (if available, extremely useful)
Your first job is hygiene:
- Parse the logs into a structured table
- Normalise URLs (lowercase where appropriate, remove fragments, consistent trailing slashes)
- Split path and query string so you can analyse parameters properly
- Identify bots using user agent patterns
Step by step: a practical log file analysis workflow
Step 1: Filter to the bots you care about
Start with Googlebot, and usually Googlebot Smartphone too. You can widen later.
Be careful though: plenty of bots pretend to be Googlebot. If you are making decisions based on “Googlebot crawled this”, validate properly. In a serious audit, you verify reverse DNS, or you rely on trusted platform identification.
Step 2: Group URLs into meaningful buckets
Staring at millions of rows is pointless unless you group.
Common grouping approaches:
- By directory: /blog/, /category/, /products/, /collections/
- By template: product detail pages, category pages, blog posts, internal search
- By parameter set: ?sort=, ?filter=, ?page=, ?q=
- By status code group: 2xx, 3xx, 4xx, 5xx
Your goal is to quickly answer: where is crawl concentrated?
Step 3: Separate “crawl volume” from “crawl value”
A directory getting 40% of your crawl does not mean it is important. It might mean it is a trap.
Crawl value is about whether those crawls support indexation and revenue outcomes:
- Key landing pages
- Product and category pages that convert
- High intent B2B service pages
- Content that supports topical authority and demand capture
If you want to connect this to your wider organic strategy work, these pages usually sit inside an SEO performance framework like.
Step 4: Identify crawl waste patterns
This is where the fun starts. Typical crawl waste looks like:
Redirect chains and loops
If Googlebot hits:
- URL A (301) to URL B (301) to URL C (200)
That is 2 wasted requests before it even reaches content. Multiply by thousands of URLs and you are burning crawl on avoidable plumbing.
What to do:
- Update internal links to point directly to the final URL
- Reduce chain length to 1 redirect max
- Fix redirect loops immediately
404s and soft 404s
404s are not automatically “bad”, but frequent bot hits to 404s usually means:
- Broken internal links
- Old URLs still referenced externally
- Bad pagination logic
- Parameter URLs generating nonsense
What to do:
- Repair internal links
- Add redirects where there is a relevant replacement
- If the URL should never exist, remove the source creating it
Parameter bloat and faceted crawl traps
Ecommerce and large content sites often create infinite combinations:
- Sort orders
- Filters
- Tracking parameters
- Pagination mixed with filters
If you have ever dealt with faceted navigation issues, Totally Digital’s ecommerce audit piece is worth a read.
What to do:
- Decide which parameter combinations deserve to be indexable
- Block true crawl traps via robots.txt where appropriate
- Use canonical tags, internal linking rules, and noindex carefully
- Ensure your sitemap only includes URLs you genuinely want indexed
Internal search pages being crawled
If Googlebot is crawling:
- /search?q=whatever
- /?s=whatever
- /site-search/results?query=whatever
You usually have a quality issue brewing. Internal search is often thin, duplicate, and infinite.
What to do:
- Noindex internal search result pages
- Prevent internal linking to them where possible
- Block crawl in robots.txt only if you are confident you are not blocking important URLs by accident
Calendar and infinite pagination spaces
Classic trap:
- /events/2024/01/
- /events/2024/02/
- /events/2034/09/
Bots will crawl forever if you let them.
What to do:
- Limit infinite generation
- Use sensible pagination and archive boundaries
- Remove internal links to non valuable archive combinations
Thin tag pages and duplicate archives
Blogs often create:
- /tag/seo/
- /tag/seo-audit/
- /category/seo/
- /author/rick/
If these pages are thin and heavily crawled, that is a waste.
What to do:
- Consolidate taxonomy
- Noindex thin archive pages
- Strengthen the handful you actually want ranking
Step 5: Find opportunity, not just waste
Crawl waste is only half the story. Logs also show where you are under investing.
Important pages barely crawled
If your money pages are crawled once a month while your filters are crawled 50 times a day, you have a prioritisation problem.
What to do:
- Improve internal linking to priority pages
- Reduce crawl noise from low value URL variants
- Ensure priority pages return 200, load fast, and are not blocked
- Include them in XML sitemaps and keep sitemaps clean
New pages not being discovered quickly
If you publish often, you want Googlebot to find new URLs quickly.
What to do:
- Add “new content” modules on strong pages
- Ensure category pages link to new items
- Use a proper internal linking structure, not just a blog feed
- Submit updated sitemaps
Orphan pages that are crawled anyway
Sometimes Googlebot crawls pages that your own site barely links to, usually because of:
- Old backlinks
- Past internal links that were removed
- XML sitemaps still including them
That can be an opportunity:
- If the page is good, bring it back into your internal linking system
- If it is outdated, redirect or consolidate it
- If it is thin, improve it or remove it
Wasted crawl on slow pages
If your logs include response times, look at:
- High crawl frequency URLs with slow response
- Pages returning 5xx errors under load
- Crawl spikes that coincide with server issues
What to do:
- Fix performance bottlenecks on the most crawled templates first
- Consider caching strategy improvements
- Work with devs to reduce expensive queries
- Use monitoring and reporting so you see it before rankings drop
This is often where SEO meets data and analytics:
https://totally.digital/services/data-analytics/
Turning findings into a fix list you can actually ship
A good log file analysis ends with a prioritised backlog, not a 40 page deck nobody touches.
Use a simple prioritisation grid:
- Impact: will this free crawl for important URLs or improve indexation quality?
- Effort: is it a quick config change or a full platform rewrite?
- Risk: could this accidentally block or deindex valuable pages?
Typical high impact, low effort fixes:
- Update internal links to remove redirect chains
- Remove sitemap URLs that redirect or 404
- Noindex internal search results
- Fix broken links creating 404 crawl loops
- Add rules to prevent infinite URL generation
Higher effort but often worth it:
- Faceted navigation strategy redesign
- Parameter handling logic improvements
- Consolidation of taxonomy and archives
- Performance work on heavy templates
If your site is part of a broader design and build roadmap, it is worth aligning SEO and dev from day 1.
How often should you do log analysis?
For most UK businesses:
- Quarterly is a sensible baseline
- Monthly if you are large, fast moving, or ecommerce heavy
- Weekly if you are in a migration, incident response, or indexation crisis
Log analysis is especially valuable after major changes:
- Site migrations
- New faceted systems
- Large internal linking changes
- Platform upgrades
If you want to keep the overall programme structured, start from a repeatable audit and reporting cadence.
Common mistakes that make log analysis useless
- Looking at “all bots” at once and getting lost in noise
- Not grouping URLs into templates, so you cannot see patterns
- Treating crawls as equal, instead of separating value from waste
- Forgetting that a crawl is not an index, and an index is not a ranking
- Making robots.txt changes without understanding the knock on effects
- Ignoring server performance signals, especially 5xx and slow responses
A simple checklist you can use on your next run
Use this as your next pass:
- Googlebot crawl volume by directory and template
- Top crawled URLs, and whether they deserve it
- Percentage of crawls by status code group (2xx, 3xx, 4xx, 5xx)
- Top redirect sources and chain length
- Top 404 URLs and where they are linked from
- Parameter URL volume and the worst offenders
- Crawl frequency of your top 20 priority pages
- New content discovery speed (first crawl after publish)
- Response time distribution for the most crawled templates
- Sitemap coverage versus what Googlebot actually crawls
Bringing it all together
Log file analysis is one of those SEO tasks that feels technical, but it is really about focus.
You are not doing it to create charts. You are doing it to make sure search engines spend their time on the pages you want ranking, converting, and growing your business.
If you suspect crawl waste, index bloat, or “Google is looking at the wrong stuff”, you do not need more opinions. You need evidence. Logs give you that evidence.
Or go straight to the services overview and pick the track that fits your goals.
If you want, I can also adapt this into a “log analysis playbook” template you can reuse for each client, with a reporting table and a prioritised fix backlog.
If you’re tired of traffic that doesn’t convert, Totally Digital is here to help. Start with technical seo and a detailed seo audit to fix performance issues, indexing problems, and lost visibility. Next, scale sustainably with organic marketing and accelerate results with targeted paid ads. Get in touch today and we’ll show you where the quickest wins are.