How To Get The Most Out Of The Google Analytics API For Non Developers

Twitter: @charlesmeadencharles@digitalnation.co.uk
Getting The Most Out The Google Analytics API
If You’re Not A Developer
Charles Meaden
Digital Nation

Introduction
• Involved in analytics for 22 years
• Started off analysing log files, now concentrate mainly on Google Analytics
• One of the reasons why we are based in Swansea #Nofilters

Who Is This Talk Aimed At?
• Anyone who wants to
– speed up their reporting
– Extract actionable data
• Who looks at this…
{"reportRequests":[{"viewId":"96284643","dateRanges":[{"startDate":"2018-08-
21","endDate":"2018-09-
19"}],"segments":[],"metrics":[],"dimensions":[],"orderBys":[],"samplingLevel":"L
ARGE"}]}
• And thinks – what this all mean

Why Do We Use the API
Save
Time
Be detectives

Quick and Easy Ways to Extract Data API
• Google Sheets – free
• Supermetrics – paid
• Next Analytics - paid
• Analytics Edge – paid
• This talk uses Analytics Edge, but the principles remain the same

Why Analytics Edge
• Allows us to pull in data from multiple sources

Why Analytics Edge
• Append / compare and combine from multiple sources

Why Analytics Edge
• Append / compare and combine from multiple sources
• Transform and manipulated the data

Two more reasons
• The core application, plus the Google Analytics and
Google Search Console connectors cost us just
£139 per year
• The developer Mike Sullivan is outstanding in
fixing the very few bugs that have appeared
• His Misunderstood Metrics series is well worth
checking out
– Look on the right hand menu of his web page for the
links to all 12 articles

Get Data Down Quicker and Faster…
• How often do you run the same report time and time again?
• How often do you need to wait for this?

Landing Page by Medium / Source in Google
Analytics
• It takes the following 10 steps plus ‘loading time’ to extract data
1. Log in
2. Select property
3. Select Acquisition
4. Select All Traffic
5. Select Source / Medium
6. Select Secondary Dimensions
7. Select the Landing Page dimension
8. Set date range
9. Change show rows
10. Export as CSV
• If more than 5000 rows, then select the next page and wait for it to
load….

In Analytics Edge

As it’s in Excel
• Store key variables in cells and call them
from the application
• Store all the setting in one Excel file
• Makes it really easy to change and adapt
• Can use all of the Excel formatting and
functions
• Lot of people still like reports in Excel…

You’re Limited Only By Your Imagination
• Rather than be constrained by looking at what data the API can pull out
• Look at the ideal type of actionable reports you want to build
Data Ideal

Get Around Sampling

Download Over A Million Rows
• Had a well known UK retailer with a
bounce rate of less than 3% on the
home page
• That just feels wrong….
• Added Simo Ahava Key Custom
Dimensions to capture
– Client ID
– Session ID
– Timestamp
• Left it running for a week to collect data
• Exported the results as a CSV file

Only Grab Certain Results
• Find any instance of Personally
Identifiable Information
• Find all query strings

Create Missing Google Analytics Reports
• We create a most navigated to pages report
• Using Analytics Edge we extract
– The page name
– Entrances
– Page views
• Analytics Edge allows you to create a set of macros to step through and
transform the data

Most Navigated To Reports
• Editable 3 step macro to extract, transform and write the data

Most Navigated To Reports
• Not good that the second most navigated page is a zero search results
page!

Get Data from Hundreds of Segments
• The API supports dynamic segments
• Allows you to build segments on the fly
• Easy to use taxonomy
– sessions::condition::
– sessions::condition::ga:deviceCategory=~desktop;
– sessions::condition::ga:deviceCategory=~desktop;ga:medium=~organic;
– sessions::condition::ga:deviceCategory=~desktop;ga:medium=~organic;ga:landingPagePath=~/sport
swear
• Supports regex and a ‘not’ condition
– Very handy for trying to deal with horribly complicated URL’s

User Funnels
• If you’re not blessed with 360, easily create user funnels
– users::conditions::ga:deviceCategory=~desktop;ga:pagePath=~/categorypage/
– users::conditions::ga:deviceCategory=~desktop;ga:pagePath=~/productpage/
– users::conditions::ga:deviceCategory=~desktop;ga:pagePath=~/basket/
– users::conditions::ga:deviceCategory=~desktop;ga:pagePath=~/checkout/
– users::conditions::ga:deviceCategory=~desktop;ga:pagePath=~^thankyou$

Dashboards
• This one has 253 queries
• For each site area we grab
• Last week, previous week and
last year
• Sessions, Revenue, Bounce
and Ecommerce Conversion
Rate
• For each device category

Merchandising Reports
• Two examples of reports that we built to help
merchandisers
• Simple
– Allow the user to select the category page from a drop down list
– Extract all the searches carried out on that page
– Extract and summarise all the events fired for the faceted and
filtered search
• Advanced
– Extract product and category level Enhanced Ecommerce
information
– Calculate the average ‘buy to detail’ and ‘cart to detail’
– Place categories and products into 4 categories
• Little Seen – Little Bought
• Little Seen – Often Bought
• Often Seen – Little Bought
• Often Seen – Often Bought

Boston Matrix
Often Seen
/ Little Purchased
Often Seen
/ Often Purchased
Little Seen / Little
Purchased
Little Seen /
Often Purchased
Often
Seen
Little
Seen
Often
Purchased
Little
Purchased

Google Search Console API
• Analytics Edge can extract data out of the Google Search Console API
• Combine it with Google Analytics to add search queries to the landing
page data
• We use to
– Grab as many queries as possible
– Classify queries into intent groups
– Really understand brand vs non brand traffic

Extract All The Queries From Google Search
Console
• Analytics Edge contains a repeat macro
• Use this to grab all the queries containing a,b,c etc
– We run 89 queries including common parts of words such as er,at
• With some clients, we are getting 100,000+ keywords
• For a well known retailer, we extracted 468,463 phrases used to show
their site in the Google SERPS over a 16 month period

Classify Queries Into Intent Groups
• Analytics Edge allows to make multiple passes over the data
• We build macros to extract the most popular used 2,3 and 4 word
combinations used in the search queries
– For the phrase ‘red tennis shoes’, ‘green tennis shoes’ , ‘cheap tennis
shoes’ we would extract tennis shoes
• These are ‘eyeballed’ to determine content groups
• Filters in Analytics Edge support regex, which allows us to build
out capture groups
– The example here uses the regex b word boundary to capture any
search query that contains a question
• The repeat macro facility takes the first query and extract any
phrase to a new worksheet. It then then works through the list,
deduping as it goes

Brand vs Non Brand Traffic
• People searching for a brand don’t always land on the home page and
sitelinks make it harder to track
• Google Search Console data will always be less accurate than Google
Analytics
• Using the Google Analytics and Google Search Console API, we do the
following
1. Download all search queries and landing pages
2. Divide them between brand and non brand search queries (including
misspellings)
3. For each landing page calculate the number of clicks that came from brand and
non brand terms
4. Using the click split, calculate the percentage of traffic for each landing page that
came from brand and non brand
5. Extract all organic landing page traffic from Google Analytics for the same period
6. Use the percentage split to calculate how much traffic is brand related
• You may find brand traffic is far higher than you thought

Thank You…
• Any questions or feeback, please
• Email me at Charles@digitalnation.co.uk
• Follow me on Twitter @charlesmeaden
• Connect with me on LinkedIn

How To Get The Most Out Of The Google Analytics API For Non Developers

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