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SEO Analytics: How to report &
improve performance
SEO Reporting
with (not provided)
Background
1. (not provided) keyword traffic affects all analytics
platforms.
2. Google SEO keywords used to hold a referral with q
parameter holding keyword e.g. q=keyword
3. Now redirects referral to take out q parameter, but retains
other information
4. Distinct from (not set) or (direct) traffic, which has no
referral information at all e.g. iOS browsers, https secure
search
Contents
1. What Data Is Left?
2. User/Page Based Reporting
3. Current Tools
What Data Is Left?
What data is left?
● Google Webmaster Tools
● SEO Rank Checkers
● Google Referral Information
● Historic Analytics Data
● AdWords Keyword Reports
● SEO User Behaviour
Google Webmaster Tools
Top Queries
○ Keyword - Sometimes misses important
keywords
○ Impressions - rarely displays all SEO
impressions
○ Clicks - rarely displays all
○ Avg. Position - looks reliable compared with
other ranking methods
Top Pages - Same as above but on URL level
Can download via Python tool, but keywords per page only
available manually
Impression/Click metrics only useable for trend splits
SEO Rank Checkers
SEOmoz, AdvancedWebRanking, AuthorityLabs etc.
● Can provide what keywords rank for which URL
● Prone to personalisation, location inaccuracies
● Against Google ToS
Can be used to find which URLs are ranking for which
keyword, but rankings may be inaccurate.
Google Referral Information
Take the Google referral URL, find what other information is
available aside from query.
● Keyword Ranking still available for now (cd=)
● What type of search result click (sitelink, video,
knowledge graph etc.)
● Landing Page URL
Can be used to narrow down what type of result hit a page,
to compare with Rank Checkers
Data from 2012 verifies GWT Average rankings well (85%
correlation with median position)
Historic Analytics Data
Take metrics from
keywords from
when you had
data.
Use Forecasting,
Seasonal cycles to
provide what
trends keywords
take
AdWords Data
Paid Search still has all metrics available.
Run exploratory AdWords campaigns to get benchmark
data, or use existing campaigns.
● Get reliable Search Impressions
● Per Keyword Conversion Rates
● Use GWT link with AdWords to find Paid/SEO
relationships
SEO User and Page Based Reporting
SEO User Based Reporting
Keywords are powerful as they indicate the intent of a
user hitting a website.
But can this information be found elsewhere?
Cohort Analysis - get demographic data from a user,
infer what lifetime value of that user is and where SEO
falls in that journey
SEO User Behaviour
How users behave onsite differs depending on which
keyword they arrive upon.
Examining branded multi-touch behaviour in study for a
client, we found:
● Brand Searchers touched website ~10% more often
than non-brand
● Brand Searchers average number of touches before
conversion were ~150% less than Non-brand
Can be used to make judgements on which visitor type
hits a page from (not provided)
Click Through Rates
As keywords change position, amount of traffic
fluctuates. (i.e if ranking goes down, traffic goes down)
If observed keyword changes rank, check landing URL
for projected change in traffic.
CTR from GWT and industry benchmarks.
Requires historic record of keywords and positions
Page Based Reporting
With loss of SEO metrics by keyword, SEO metrics by
URL page helpful.
Good SEO fundamentals provide inference of SEO
keyword behaviour:
● Client Study showed average of 70% of keywords
hitting URL were also in URL's <title> tag
● Requires unique title tags to be effective
● Internal links, H1, tags etc. also influence SEO
rankings
Narrow down what keywords could be making each
page's (not provided) split.
Current Tools
(not provided) % split
● Take all keywords that are not (not
provided), find % split distribution
● Apply to (not provided) traffic, estimate
what % of traffic are attributed to other
keywords
Will only work with big samples of keywords,
which are dwindling to 0.
Use GWT and other data to find split in
future.
URL Split of (not provided)
● Take landing page URL for SEO keywords
● Download title tag, metrics per URL
● Find % split of (not provided) for each URL
Benchmark against pre (not provided) era, to find
% of keywords that are in title tag
● Useful metric for focusing title tags for SEO
● Narrows down list of possible keywords to
landing URL
Google Webmaster Tool API
● Only way to download Search Queries is currently Python tool.
● Allows download of Top Queries, Top Pages
● Lacks Keywords per Top Page.
● Runs every week for historic archive
SEO keyword Forecast
Apply to
historic data to
find seasonal
trends.
Apply to all
SEO traffic or
individual
keywords
SEO keyword CTR Prediction
Apply to Impressions
and ranking
keywords to find
projected traffic
Unreliable under
position 10
May have different
CTR distribution
depending on query
Monitoring SEO Rank changes
Predict traffic changes according to CTR and rank change
1. Monitored keyword increases
from position 5 to position 1
2. CTR expected to raise by
factor of 5.5
3. Repeat for every SEO
keyword pointed at URL in
rank checker
4. Calculate overall traffic
change
5. Compare with actual traffic
change to that URL
SEO keyword Clustering
Apply Machine
Learning to find
user behaviour
e.g. Split brand vs
non-brand
behaviour
Summary
Putting all above together
1. Shortlist what keywords are likely to hit URL.
2. Compare with keywords that URL is ranking for
3. Infer traffic split of keywords
4. Monitor changes to rankings, project changes
to (not provided) traffic for displayed URL
5. Account for seasonal and forecasted traffic
volumes
Further Reading
http://www.slideshare.net/MarketingFestival/5-michaelking-jak-se-vyporadat-s-not-provided
Custom Channel Grouping
& utm tagging best practices
Traffic types
Earned
Media
Owned
Media
Paid
Media
Traffic types
Direct
(owned)
Display
(Paid)
Organic
(Earned)
Assisted conversion report
for Social Paid is broken
Social
Because Default Channel
Grouping is wrong
“Social Paid” incorrectly grouped under “(Other)”
Here is a Private Channel
Grouping fixed example...
Note: assumes that utm_campaign=*_paid_* is Social Paid in Private Channel Group:
https://analytics.google.com/analytics/web/template?uid=WsCugGmAReeaI4JEOfta4A
Correct tagging... Expected GA utm_medium for social are
1. sm (like cpc)
2. social (like organic)
3. social-network
4. social network
5. social-media
6. social media
Current... utm_medium=FacebookIrelandLtd
utm_source=Facebook.com_N5851.270751FACEBOOK_131474803_70473783_304144507_5441400
utm_campaign=Essence_paid_FacebookIrelandLtd
utm_content=20160601 20160601073000
utm_id=
utm_term=n/a
dclid=COCYws21hs0CFVMg0wod3oUDnw
.
.
.
Social Paid should be... utm_medium=sm
utm_source=facebook.com
utm_campaign=2016_01_01_Essence_paid_AirportCampaign
utm_content=N5851.270751FACEBOOK_131474803_70473783_304144507_5441400
utm_id=N5851.270751FACEBOOK_131474803_70473783_304144507_5441400
utm_term=n/a
dclid=COCYws21hs0CFVMg0wod3oUDnw
.
.
.
Social Organic should be... utm_medium=social
utm_source=facebook.com
utm_campaign=2016_01_01_Essence_organic_AirportCamp
utm_content=N5851.270751FACEBOOK_131474803_70473783_304144507_5441400
utm_id=N5851.270751FACEBOOK_131474803_70473783_304144507_5441400
utm_term=n/a
dclid=n/a
.
.
.
utm_medium=referral
utm_source=facebook.com
utm_campaign=n/a
utm_content=n/a
utm_id=n/a
utm_term=n/a
Social Referral should be...
Excel workbook
(future data only)
bit.ly/utm-tagging-examples
Note: Using 5 GA profile filter fix on a
new GA profile view (rather than re-tag)
1.Source=^Facebook\.com_(.*)
Campaign=.*_paid_.*
CampaignCode=$A1
2.Source=^Facebook\.com_(.*)
Campaign=.*_paid_.*
AdContent=$A1
3.Source=^Facebook\.com_(.*)
Campaign=.*_paid_.*
Output Source=facebook.com
4.Medium=^facebook(.*)
Campaign=.*_paid_.*
Output Medium=sm
5.Medium=^facebook(.*)
Output Medium=social
(future data
only)
Report Automation Examples
Example Dashboard:
https://analytics.google.com/analytics/web/template?uid=NyGD2Rg0RaufLDoIan18tg
GA dashboard can be auto-emailed
GoogleSheets - GA plugin
GA setting: Goals
Goals
Time spent + Pages/session
goals are not good macro KPI`s
Instead...
Enable Smart Engagement Goals
Enable Smart engagement Goals
Also add newsletter tracking
Example KPIs
bit.ly/better-kpis
3. Check GA country filter
Check URL based country filter working as
confliction data in GEO-ip report...
4. Provide instructions on how to
setup GTM to report on
contentGroupings
PostCategories & PostType
(e.g. blog post, video content, white paper, infographic, etc)
Example of content groups...
Use GTM
CSS
selectors
Use GTM
customVariable
script
to tidy data collected
How to test...
Remember to add 5 contentGroups
in GA settings 1. contentType
2. pageID
3. author
4. readTime
5. publishDate
Alternative method, if GTM changes take too long for IT dept to approve...
Manual ContentGrouping for
contentType is also possible
PageGroup Field Match value
homepage url ^/t5/BusinessNow-(.*)/ct-p/..($|\?)
site search url ^/t5/forums/searchpage/
blog post title .*/ba-p/[0-9]+
category page url .*/label-name/.*
404 page title .*Page Not Found.*
Manual ContentGrouping for
pageID is also possible