SEO Reporting with (not provided)


  • (not provided) keyword traffic affects all analytics platforms.
  • Google SEO keywords used to hold a referral with q parameter holding keyword e.g. q=keyword
  • Now redirects referral to take out q parameter, but retains other information
  • Distinct from (not set) or (direct) traffic, which has no referral information at all e.g. iOS browsers, https secure search
  • For more information on cost please read this article on the cost of SEO

What Data Is Left?

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.

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

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

  • Monitored keyword increases from position 5 to position 1
  • CTR expected to raise by factor of 5.5
  • Repeat for every SEO keyword pointed at URL in rank checker
  • Calculate overall traffic change
  • 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


Putting all above together

  • Shortlist what keywords are likely to hit URL.
  • Compare with keywords that URL is ranking for
  • Infer traffic split of keywords
  • Monitor changes to rankings, project changes to (not provided) traffic for displayed URL
  • Account for seasonal and forecasted traffic volumes

Custom Channel Grouping & utm tagging best practices

Traffic types

Traffic types

Assisted conversion report for Social Paid is broken

Because Default Channel Grouping is wrong

Here is a Private Channel Grouping fixed example

Correct tagging...

Expected GA utm_medium for social are

  • sm (like cpc)
  • social (like organic)
  • social-network
  • social network
  • social-media
  • social media


utm_content=20160601 20160601073000

Social Paid should be...


Social Organic should be...


Social Referral should be...




Excel workbook (future data only)

Note: Using 5 GA profile filter fix on a new GA profile view (rather than re-tag)

Report Automation Examples

GA dashboard can be auto-emailed

GoogleSheets - GA plugin

GA setting: Goals


Time spent + Pages/session goals are not good macro KPI`s


Enable Smart Engagement Goals

Enable Smart engagement Goals

Also add newsletter tracking

Example KPIs

Check GA country filter

Check URL based country filter working as confliction data in GEO-ip report...

Provide instructions on how to setup GTM to report on contentGroupings

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

Manual ContentGrouping for contentType is also possible

Manual ContentGrouping for pageID is also possible

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