LinkedIn emplea cookies para mejorar la funcionalidad y el rendimiento de nuestro sitio web, así como para ofrecer publicidad relevante. Si continúas navegando por ese sitio web, aceptas el uso de cookies. Consulta nuestras Condiciones de uso y nuestra Política de privacidad para más información.
LinkedIn emplea cookies para mejorar la funcionalidad y el rendimiento de nuestro sitio web, así como para ofrecer publicidad relevante. Si continúas navegando por ese sitio web, aceptas el uso de cookies. Consulta nuestra Política de privacidad y nuestras Condiciones de uso para más información.
Advanced data-driven technical SEO - SMX London 2019
@basgr from @peakaceag1
Bastian Grimm, Peak Ace AG | @basgr
Merging your logfiles, GA, GSC & web crawl data
for better SEO insights
Advanced data-driven technical SEO
@basgr from @peakaceag2
And why are log files important for your SEO work?
Why should you care?
pa.ag@peakaceag @basgr from @peakaceag3
I am a big fan of the various crawling tools, but…
It’s only the access log files that demonstrate
how a search engine’s crawler is behaving on
your site; all crawling tools are simply trying to
simulate their behaviour!
@basgr from @peakaceag4
You need to see which pages are being prioritised by the search
engines and should therefore be considered the most important
1. Understand crawl priorities
@basgr from @peakaceag5
Google may reduce its crawling behaviour/frequency & eventually rank
you lower if you are constantly providing a large amount of errors
2. Prevent reduced crawling
@basgr from @peakaceag6
It’s essential to identify any crawl shortcomings
(such as hierarchy or internal link structure)
with potential site-wide implications
3. Understand global issues
@basgr from @peakaceag7
You need to ensure that Google crawls everything important:
primarily ranking, relevant content, but also fresh & older
4. Ensure proper crawling
@basgr from @peakaceag8
It’s important to ensure that any gained link equity will
always be passed using proper links and/or redirects
5. Ensure proper linking
@basgr from @peakaceag9
Keep in mind, details depend on the individual setup!
The characteristics of a log file
@basgr from @peakaceag10
…depending on your webserver (Apache, nginx, IIS, etc.), caching
and its configuration. Make sure to understand your setup first!
Content & structure can vary…
pa.ag@peakaceag @basgr from @peakaceag11
What does a log file usually look like?
Server IP/host name1
Timestamp (date & time)2
HTTP status code5
Size in bytes6
188.65.114.xxx [21/May/2019:02:00:00 -0100]
HTTP/1.1" 200 512 "http://www.wikipedia.org/"
"Mozilla/5.0 (compatible; Googlebot/2.1;
@basgr from @peakaceag12
Log file data can be quite overwhelming because you can do so
many different things; make sure you’ve got
your questions prepared!
You need to ask the right questions!
pa.ag@peakaceag @basgr from @peakaceag13
Log file data can be different e.g. to Google Analytics data
While log files are direct, server-side pieces of information, Google Analytics uses client-
side code. As the data sets are coming from two different sources, they can be
The configuration within Google Analytics also leads to data differences when
compared to the log files, i.e. filters!
@basgr from @peakaceag14
Be cautious when requesting log files from your clients
Frequently asked questions
@basgr from @peakaceag15
We only care about crawlers such as Google and Bing; no need for any
user data (operating system, browser, phone number, usernames, etc.)
1. Personal information in logs?
@basgr from @peakaceag16
If you are running a cache server and/or a CDN which
creates logs elsewhere, we will also need these logs
2. Separate multi-location logs?
@basgr from @peakaceag17
There are different ways you could approach this:
Log file auditing tools
pa.ag@peakaceag @basgr from @peakaceag18
There are different ways you could approach this:
pa.ag@peakaceag @basgr from @peakaceag19
Do-it-yourself solution based on Excel
You’d have to manually build filtering, cross-references, etc. – it just doesn’t scale!
pa.ag@peakaceag @basgr from @peakaceag20
Screaming Frog Log File Analyser
Beginners’ level, desktop-based log file auditing with pre-defined reports.
@basgr from @peakaceag21
No sharing capabilities, log files need to be manually up/downloaded,
which is usually problematic for larger files, etc.
Desktop solutions are limited
pa.ag@peakaceag @basgr from @peakaceag22
Splunk or Sumo Logic: proprietary, paid software solutions
Enterprise tools such as Splunk usually come with a hefty (volume-based) price tag.
In all fairness though: these solutions offer features way beyond log file monitoring!
Image sources: https://pa.ag/2srgTZu (splunk) & https://pa.ag/2JcuiLt (sumologic)
pa.ag@peakaceag @basgr from @peakaceag23
The Elastic Stack (ELK): Elasticsearch, Logstash & Kibana
Elasticsearch: search & analytics engine, Logstash: server-side data processing
pipeline, Kibana: data visualisation (charts, graphs, etc.) – all open source.
Image source: https://pa.ag/2JbFUhP
pa.ag@peakaceag @basgr from @peakaceag24
Other SaaS solutions: logrunner.io, logz.io (ELK) & Loggly
Especially logrunner.io, which has a strong focus on SEO-based auditing (dashboards
pa.ag@peakaceag @basgr from @peakaceag25
crawlOPTIMIZER: SaaS Logfile Auditing, made in Vienna
BRPs (Business Relevant Pages) with dedicated evaluations of these as top USP.
@basgr from @peakaceag26
No messing around with exports, up/downloads, easy sharing
capabilities and the ability to deal with massive volumes, etc.
The beauty of SaaS: almost real time
@basgr from @peakaceag27
For an easy start: trend monitoring (over time) & gathering insights
Let’s have a look at some data
pa.ag@peakaceag @basgr from @peakaceag28
Most obvious approach: spotting anomalies vs. time frame
Tip: this is why it makes a lot of sense to check your log files regularly (e.g. daily).
This looks unusual; take it
as a starting point for
pa.ag@peakaceag @basgr from @peakaceag29
User crawling frequencies over time
Understanding patterns and irregularities can be very helpful - always look at the crawl
behaviour of individual users over time.
@basgr from @peakaceag30
Use log files to look for spam bots or scrapers to block!
What other ”bots“ access your site?
pa.ag@peakaceag @basgr from @peakaceag31
Not everyone is who they claim to be!
The easiest way to detect if Googlebot really is Googlebot: run a reverse DNS lookup.
Bingbot can also be verified via *.search.msn.com.
pa.ag@peakaceag @basgr from @peakaceag32
What are the most crawled Googlebot pages?
Also, verify if they coincide with your domains’ most important ones.
Understand if these are really
your most valuable pages?
pa.ag@peakaceag @basgr from @peakaceag33
Breakdown of crawl requests & status codes per directory
You’d easily see if one of your main directories encountered crawling/response issues.
Tip: establish this on a regular basis to ensure continued performance of top directories.
@basgr from @peakaceag34
And respective actions based on those findings
Advanced auditing for SEO
pa.ag@peakaceag @basgr from @peakaceag36
Identify any kind of ”wrong“ redirect: 302/304/307/308
Action: change to 301 (except geo redirects); also watch out for redirect chains!
Investigate further to
see what’s in there
pa.ag@peakaceag @basgr from @peakaceag38
4xx client errors: too many are a sign of poor site health
Action: recover (200), redirect (301) or kill off entirely (410)
pa.ag@peakaceag @basgr from @peakaceag39
Googlebot can‘t login… (403: forbidden)
If it‘s linked, Google will try to crawl it – they are greedy!
pa.ag@peakaceag @basgr from @peakaceag40
5xx server errors: usually infrastructure-related
Action: watch closely and/or talk to IT (server availability, high load, etc.)
Check consistency; what
happens when re-trying?
pa.ag@peakaceag @basgr from @peakaceag42
Understanding the most/least crawled URLs and folders
Action: highly crawled pages/folders could be used e.g. for additional internal linking
(add link hubs), low crawled areas need to be linked more prominently.
Can be used for additional, internal linking (improve
discovery of other content)
Clearly weak, either irrelevant (remove) or requires
pa.ag@peakaceag @basgr from @peakaceag44
Investigate if (new) URLs have been crawled at all
Action: if relevant URLs haven’t been discovered/crawled at all, your internal linking is
probably too weak. Consider XML sitemaps, better/more prominent linking, etc.
If these are important URLs,
you might have a problem!
pa.ag@peakaceag @basgr from @peakaceag46
I‘m sure you‘ve all seen this?
pa.ag@peakaceag @basgr from @peakaceag47
This is what the Google Webmaster Central blog says:
Wasting server resources on pages […] will
drain crawl activity from pages that do actually
have value, which may cause a significant
delay in discovering great content on a site.
pa.ag@peakaceag @basgr from @peakaceag48
If you have ever had to deal with sites like these…
Properly dealing with >30,000,000 crawlable URLs (due to parameter usage) certainly
makes a difference in organic performance!
pa.ag@peakaceag @basgr from @peakaceag49
URL parameters cause most problems
(Combined) URL parameters often generate millions of unnecessary URLs, especially for
large domains, which Googlebot diligently crawls (once found).
pa.ag@peakaceag @basgr from @peakaceag50
URL parameter behaviour over time
Constantly be on the lookout for new parameters as well as significantly increased
crawling for known parameters.
pa.ag@peakaceag @basgr from @peakaceag51
A brief overview: #SMXInsights
Log file size, quantity
& availability are all
decisive with regards
to tool selection.
Preparation is key
help to generate
Crawl data only
Be precise with your
requests (to the IT
department) - you
just want to know
what the search
engines are doing!
Reverse DNS use
Not every crawler is
who they pretend to
be - do not "blindly"
trust in the user-agent
These are almost
always the biggest
consistency) - audit
@basgr from @peakaceag52
Oh yeah, there’s one more thing …
@basgr from @peakaceag53
I want: no IT involvement, unlimited scalability, flexible reporting, multiple
(API) data sources and ease of use!
There's got to be another way!
@basgr from @peakaceag54
(And everyone at #SMX gets this as a gift - for free!)
We've thought of something:
pa.ag@peakaceag @basgr from @peakaceag55
Say hello to the Peak Ace log file auditing stack
Log files are stored in Google Cloud Storage, processed in Dataprep, exported to BigQuery and
visualised in Data Studio via the BigQuery Connector.
Google Data Studio
Google Dataprep Google BigQuery
Google Apps Script
@basgr from @peakaceag56
Individual reports, tailored to your needs
And what do the results look like?
@basgr from @peakaceag60
Connect and conquer…
How does it work?
pa.ag@peakaceag @basgr from @peakaceag61
#1 Log file data from web servers, CDN, cache, etc.
How often do bots actually crawl? What do they crawl and when?
Goal: improve site architecture by
analysing real bot crawling data.
▪ Amount of crawls/requests by bot type
▪ Identification of crawling patterns
▪ Overview of errors
Log filesGoogle Cloud
Import as text files
(exclude IP addresses!)
@basgr from @peakaceag62
15TB (per one file) to be pushed in Big Query
Size is absolutely NOT an issue
@basgr from @peakaceag63
nginx / Apache / etc. >> fluentd >> Big Query
Stand-alone files are messy, agreed.
pa.ag@peakaceag @basgr from @peakaceag64
#2 Google Analytics API
Enrich reports with traffic, engagement, behavioural and page speed data
Goal: compare crawling behaviour with user & loading
URL-based data on important engagement metrics:
▪ Bounce rate
▪ Session duration
▪ Avg. time on page
▪ Avg. server response time
▪ Avg. page load time
Reporting API v4
pa.ag@peakaceag @basgr from @peakaceag65
#3 Google Search Console API
Organic search performance data directly from Google
Goal: compare crawling behaviour with organic click
data & e.g. retrieve reported crawling errors.
Organic click data
URL-based server response data
▪ Status code
Console API v3
pa.ag@peakaceag @basgr from @peakaceag66
#4 DeepCrawl API
Website architecture, status codes, indexing directives, etc.
Goal: capture indexing directives, response codes and
pa.ag@peakaceag @basgr from @peakaceag67
#5 Google Apps Scripts for GA, GSC & DeepCrawl
API access: capture multiple dimensions and metrics from GA, retrieve GSC crawl and
search analysis data and DeepCrawl crawl & analysis data
Goal: send data (via/from the respective API) to BigQuery
and store the data there.
Google Apps Script
pa.ag@peakaceag @basgr from @peakaceag68
#6 Google Cloud Dataprep
Clean and process the data. Afterwards, combine these various sources with
several joins so that they‘re ready for visualisation.
Goal: combine data from log files, GSC, GA & DeepCrawl
within/by using processing flows.
Dataprep: “Excel with super rocket fuel“
▪ Amazing RegEx support
▪ Select data, receive automated
proposals for processing
▪ Join data sources by e.g. full
inner/outer join, left/right outer join…
Google Apps Script
@basgr from @peakaceag69
And use Google Data Studio to visualise:
Save everything to BigQuery
pa.ag@peakaceag @basgr from @peakaceag74
Log file auditing is not a project, but a process!
Integrate log file auditing into your regular
SEO workflow; one-off audits are good to
begin with, but they really become invaluable
if you combine them with web crawl data and
perform them on an on-going basis.
pa.ag@peakaceag @basgr from @peakaceag75
Slides? No problem:
You want our log file setup (for free)?
e-mail us > email@example.com
ALWAYS LOOKING FOR TALENT! CHECK OUT JOBS.PA.AG