SlideShare a Scribd company logo
Better conversion with Intelligent Analytics
@pjeedai
Turn user behaviour data
into Value
Understand causes of
bottlenecks on key areas
Think through
factors that may
impact results
Think about YOUR Data
What YOU can investigate
What YOU can investigateExamples and Ideas
Inspire
Tag Manager
Makes all this MUCH easier to do
Tags
Add Events, Scripts with Custom Triggers
Add Extra Dimensions, Metrics, Data to Pageviews, Events, Hits
Variables
Collect Data as Variables
Use Variables for fields in Google Analytics
Page Values
Collect Data from Page or from Back end Source
Send to dataLayer
Collect Data to use in Tag Manager Variables
Variables can also be captured without dataLayer
Event Variables
Variables Can Be Variable
Lookup Variables
If Bike Stock Type = New then use New Stock Variables
If Bike Stock Type = Used then use Used Stock Variables
Variables for Custom Dimensions
Custom Dimension Variables
Tools & Stacks
Google Analytics API Script
or paid plugins like
Google Analytics API to Excel, csv or database
Also API for Facebook, Twitter, AdWords, Search Console & more
Allows scheduled and batch data pulls
Google Analytics API to Excel, csv or database
Also API for Facebook, Twitter, AdWords, Search
Console & more
Allows scheduled and batch data pulls
Also has save to Drive or Cloud database options
Combine Business & Web Data
Deeper Analysis and visualisation
PowerBI also has native API link to Google Analytics API etc.
PowerQuery and PowerBI have REST JSON API
(make your own query from any source API)
Also have csv folder source extract for batch processing
Requires a little more work than just using the Analytics UI, more powerful than VLOOKUP
This is an example Data Model to split detail out
This lets you combine, calculate and filter as needed
Bigger datasets, more powerful statistical analysis
PowerBI cloud has real language querying
“What is the best performing product for revenue this Quarter?”
Geo lookup or CRM for customer addresses (or combine both)
Visualise on drill down map or overlay ArcGIS data
e.g. Conversions > Avg from Areas with Household income > average
Average alone can mask opportunity & risks
Tableau, R or PowerBI to analyse distribution patterns
Best for your lowest value, least loyal customers
May be Worst for your big spenders
Often not a business win
even if it reports as a Test or Campaign win
User & Session
Recording
Also, you know. Maybe talk to them
Ask Customer Services, Feedback form responses, BCC on Customer Service emails, Jump on a Live Chat
Hit level – Measurement Protocol
Gets a little spendy at the top end but Free Option is good to try out
Metrics and Measurement
Success Events
If [Good Thing] happens
Track [Good Thing]
Ideally [Type of Thing] | [Which Specific Thing] | [What Details]
Success Events - Detail
Why this much Detail?
• Custom Segments
• Remarketing
• Event Goals
• Filters and Offline Analysis (Dealer ID & stockID)
(need to be a bit careful of high cardinality on unfiltered or unsegmented data)
Fail Events
Fail Events
Common Issue for eCommerce, Appointments, Holidays
• Conversion Rate Affected by Stock Levels & Availability
Fail Events - Detail
Don’t just send Event on Success; Also send on Fail
• IF it failed
• WHAT type of Failure
• WHERE it failed (WHICH use case)
Stock Level Events
Event Goals
Event Goals
Goals are NOT just Sale Complete URL
Clicks, Add, Viewed, Video Play
Events are Ideal for segmenting Goals
Exeter Any Day
Event Click To Book
Individual, Create Team or Join Team
Exeter – Any Day
Exeter Saturday
Event Click To Book
Individual, Create Team or Join Team
Exeter – Saturday ONLY
Exeter Sunday
Event Click To Book
Individual, Create Team or Join Team
Exeter – Sunday ONLY
Clicks By Race Day
With 3 Event Goals – break down ways Total is reached
Compare Click Volumes per Race Day AND Total
Buy to Click Ratios
Calculate Buy to Click Ratios by Day AND Totals
Sunday has higher drop-off between Click and Buy
1560 ÷ 3164 = 49.30% 466 ÷ 1041 = 44.76% 2015 ÷ 4067 = 49.54%
Custom Dimensions
Custom Dimensions
• Product SKU
• Site ID
• Visitor ID
• User Lifetime Value
• Product Availability
• Previous Submit
• Checkout Account Type
• Guest
• New Account
• Logged In
• Experiment ID and Experiment Variant
Practically almost any Dimension you might want to track (non PII)
Limited to 20 on a standard account. 200 on GA Premium 
Custom Dimensions
Dealer ID to link back to Network CRM
Dealer Name varies (multi-franchise)
Report whole network performance but link back to Dealer Sales
Custom Metrics
Dimensions Describe Data
Metrics Measure Data
• User/Session of Described Type – Count
• Lead Value
• Original Price
• Displayed Price
• Product Level Discount Value
• Volume Level Discount Applied
• Finance Deposit
Custom Metrics
Frequently eCommerce will pass either
• Original Price (even if discounted Price is applicable)
• Discount Price (but no idea how much discount vs. Original Price)
Custom Metrics allows you to record & calculate the differences
Reports can then show Value Lost in discount/promotions
This allows you to report real Revenue performance
Calculated Metrics
Calculate Business Metrics not Web Metrics
Original Price – Discount Price Applied = Value Lost
Buy Exeter Tickets ÷ Click Exeter = Buy to Click Rate
Calculated Metrics
Buy Exeter Tickets ÷ Click Exeter = Clicks to Buy Rate
But we can now use this in Custom Reports
By Channel | By Campaign | By Device | By Gender | By Age etc.
Custom Reports
Extremely useful: within the limits of the User Interface
For complex reports use API
Custom Reports
Clicks to Book – By Ticket Type (from Event tracking)
Custom Reports
Drill down to Individual Tickets – Exeter Saturday has most Clicks
Compare performance of Exeter Saturday 2016 vs Exeter Saturday 2017
Are sales behind schedule? Traffic growth but lower Clicks to Buy Ratio?
Annotations
Record Changes to Tracking
Record Campaign and Promotion Periods
Highlight ‘odd’ data to investigate
Lots of Data
Pull data via API
Match against Business Data
Automate
Crunch Segments, Dimensions, Metrics
Take Action
PowerQuery > Data Model > PowerPivot Measures > Excel visualisation
Same Data Model, Measures and Query could also be used in PowerBI
Manual: Pull data via API to Sheets and Download. Download csv from GA UI
Automate: Next Analytics, Analytics Edge, Supermetrics, Power Query, PowerBI
Calculated Metrics
Custom Filters
Visualisations
Links to:
• Google Analytics
• AdWords
• Sheets
• BigQuery
and more
• Automatic Refresh
• Custom Filters
• Date Range
• Dimension Filters
• Custom Segments
Up to 20 Pages per Report
Unlimited Reports
Free!
Distribution matters
• 2 users off the scale of this chart
• 130+ items per purchase
“Average” is misleading if you don’t know how it is distributed
Custom Segments
Custom Segments
User has Clicked Enquiry on Used Motorcycle
Label of Event Contains Year: Segment to 2015
Channels Report
Segment can then be applied to other Reports: e.g. Channels
Segment Share of Contribution
Share of Sessions or Event Clicks easily compared
Or Targeted. Or Reported against # Stock of each Year being advertised etc.
Shortcuts
Create shortcuts to quickly re-apply Segments/Filters
Referrers
Advertising Stock
Costs Money
Different Portals
Different Audiences
Different Stock
Referrers
“Price To” from ?= Search string from Referral Path
Regular Expressions
“Price To” from ?= Search string from Referral Path BUT
Different format for “Price To” Search on EVERY Referrer site 
Expresso http://www.ultrapico.com/expresso.htm (Windows Only)
http://regexr.com/ (Browser)
Custom Channel Groups
Custom Channel Groups
Default Channels are ok if you tag inbound links and adverts accurately
But Custom Channel Groupings are better
Custom Channel Groups
Start with Default as Template
Divide Channels more precisely
Rules apply top to bottom
Different Groups
Different Levels of Detail
Paid Search is a good example
By Type:
• Shopping
• Display
• Text
• Video
By Spend:
• High Cost
• Medium Cost
• Low Cost
Buying Cycle, Competition, Volume etc.
This is a Top line Channel splitting – slightly more detail than Default Channels:
• Paid: Main Ad types, Top Funnel, Middle Funnel, Bottom Funnel
• Organic Search: Google or Other – Keyword Known/Not Provided
• Email: Which Mailing list (Mailchimp or EventBrite)
Custom Channel Groups
Custom Channel Groups
More detail on Paid Campaigns
• Paid Search
• Paid Social
2nd Dimension of Keyword
Exeter Race promotion
• Keywords mostly Exeter
• Some Top Funnel generic
Demographic Reports
Demographic Reports
Make sure Privacy Policy is compliant
Make sure this option is legal in your territories
Age Bands
User Volumes By Age Band
Gender
User Volumes by Gender
Affinity & Interests
Interesting? Useful?
Affinity & Interests
Combine with a Segment of Users Who Clicked but didn’t Enquire
…can be Targeted with appropriate Stock
Content Grouping
Content Grouping
Must have Edit Permission for the View
• Template
• Type
• Categories
Content Grouping
Tag Manager makes it easier
dataLayer makes it simple
Page Template: Used Bikes > All Used Stock Page Titles
Makes: Ducati > Ducati Models
Models: Multistrada > Multistrada Variants (S, Enduro etc.)
Model Year: 2009, 2010, 2011 etc.
Price Bands: £5,000 - £7,499 | £7,500 - £8,999 | £9,000 - £10,499 etc
Up to 5 Groupings
Content Grouping
Pages Report – lots of detail
Hard to see which Categories work best
Content Grouping
Categories Content Group Applied:
Apparel clearly more popular than Brands and Bags
Can also be used to create Segments
Think about YOUR Data
What YOU can investigate
@pjeedai
Data is one thing
Intelligent use of data is everything
Thank you for listening
Resources
Get Started With Tag Manager & Google Analytics
https://analytics.google.com/analytics/academy/
Learning Resources
https://www.simoahava.com/
http://www.lunametrics.com/blog/
http://www.analytics-ninja.com/blog.html
Demographics and Advertising Tools Policy Requirements
https://support.google.com/analytics/answer/2700409?hl=en-GB&utm_id=ad
Regular Expression Tools
http://regexr.com/ (Online)
http://www.ultrapico.com/Expresso.htm (Windows)
Data Studio
https://www.google.com/analytics/data-studio/
API Tools
http://www.analyticsedge.com/
https://supermetrics.com/
http://www.nextanalytics.com/
https://powerbi.microsoft.com/en-us/
https://www.scitylana.com/
Connect on Linked In https://www.linkedin.com/in/timstewart/
Or ask me a question on Twitter @pjeedai

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Better conversion with Intelligent Analytics

  • 1. Better conversion with Intelligent Analytics @pjeedai
  • 2. Turn user behaviour data into Value
  • 4. Think through factors that may impact results
  • 6. What YOU can investigate
  • 7. What YOU can investigateExamples and Ideas
  • 9.
  • 10. Tag Manager Makes all this MUCH easier to do
  • 11. Tags Add Events, Scripts with Custom Triggers Add Extra Dimensions, Metrics, Data to Pageviews, Events, Hits
  • 12. Variables Collect Data as Variables Use Variables for fields in Google Analytics
  • 13. Page Values Collect Data from Page or from Back end Source
  • 14. Send to dataLayer Collect Data to use in Tag Manager Variables Variables can also be captured without dataLayer
  • 16. Lookup Variables If Bike Stock Type = New then use New Stock Variables If Bike Stock Type = Used then use Used Stock Variables
  • 17. Variables for Custom Dimensions Custom Dimension Variables
  • 19.
  • 20. Google Analytics API Script or paid plugins like
  • 21. Google Analytics API to Excel, csv or database Also API for Facebook, Twitter, AdWords, Search Console & more Allows scheduled and batch data pulls
  • 22. Google Analytics API to Excel, csv or database Also API for Facebook, Twitter, AdWords, Search Console & more Allows scheduled and batch data pulls Also has save to Drive or Cloud database options
  • 23. Combine Business & Web Data Deeper Analysis and visualisation PowerBI also has native API link to Google Analytics API etc. PowerQuery and PowerBI have REST JSON API (make your own query from any source API) Also have csv folder source extract for batch processing
  • 24. Requires a little more work than just using the Analytics UI, more powerful than VLOOKUP This is an example Data Model to split detail out This lets you combine, calculate and filter as needed
  • 25. Bigger datasets, more powerful statistical analysis PowerBI cloud has real language querying “What is the best performing product for revenue this Quarter?”
  • 26. Geo lookup or CRM for customer addresses (or combine both) Visualise on drill down map or overlay ArcGIS data e.g. Conversions > Avg from Areas with Household income > average
  • 27. Average alone can mask opportunity & risks Tableau, R or PowerBI to analyse distribution patterns Best for your lowest value, least loyal customers May be Worst for your big spenders Often not a business win even if it reports as a Test or Campaign win
  • 29. Also, you know. Maybe talk to them Ask Customer Services, Feedback form responses, BCC on Customer Service emails, Jump on a Live Chat
  • 30. Hit level – Measurement Protocol
  • 31. Gets a little spendy at the top end but Free Option is good to try out
  • 33. Success Events If [Good Thing] happens Track [Good Thing] Ideally [Type of Thing] | [Which Specific Thing] | [What Details]
  • 34. Success Events - Detail Why this much Detail? • Custom Segments • Remarketing • Event Goals • Filters and Offline Analysis (Dealer ID & stockID) (need to be a bit careful of high cardinality on unfiltered or unsegmented data)
  • 36. Fail Events Common Issue for eCommerce, Appointments, Holidays • Conversion Rate Affected by Stock Levels & Availability
  • 37. Fail Events - Detail Don’t just send Event on Success; Also send on Fail • IF it failed • WHAT type of Failure • WHERE it failed (WHICH use case)
  • 40. Event Goals Goals are NOT just Sale Complete URL Clicks, Add, Viewed, Video Play Events are Ideal for segmenting Goals
  • 41.
  • 42. Exeter Any Day Event Click To Book Individual, Create Team or Join Team Exeter – Any Day
  • 43. Exeter Saturday Event Click To Book Individual, Create Team or Join Team Exeter – Saturday ONLY
  • 44. Exeter Sunday Event Click To Book Individual, Create Team or Join Team Exeter – Sunday ONLY
  • 45. Clicks By Race Day With 3 Event Goals – break down ways Total is reached Compare Click Volumes per Race Day AND Total
  • 46. Buy to Click Ratios Calculate Buy to Click Ratios by Day AND Totals Sunday has higher drop-off between Click and Buy 1560 ÷ 3164 = 49.30% 466 ÷ 1041 = 44.76% 2015 ÷ 4067 = 49.54%
  • 48. Custom Dimensions • Product SKU • Site ID • Visitor ID • User Lifetime Value • Product Availability • Previous Submit • Checkout Account Type • Guest • New Account • Logged In • Experiment ID and Experiment Variant Practically almost any Dimension you might want to track (non PII) Limited to 20 on a standard account. 200 on GA Premium 
  • 49. Custom Dimensions Dealer ID to link back to Network CRM Dealer Name varies (multi-franchise) Report whole network performance but link back to Dealer Sales
  • 50. Custom Metrics Dimensions Describe Data Metrics Measure Data • User/Session of Described Type – Count • Lead Value • Original Price • Displayed Price • Product Level Discount Value • Volume Level Discount Applied • Finance Deposit
  • 51. Custom Metrics Frequently eCommerce will pass either • Original Price (even if discounted Price is applicable) • Discount Price (but no idea how much discount vs. Original Price) Custom Metrics allows you to record & calculate the differences Reports can then show Value Lost in discount/promotions This allows you to report real Revenue performance
  • 52. Calculated Metrics Calculate Business Metrics not Web Metrics Original Price – Discount Price Applied = Value Lost Buy Exeter Tickets ÷ Click Exeter = Buy to Click Rate
  • 53. Calculated Metrics Buy Exeter Tickets ÷ Click Exeter = Clicks to Buy Rate But we can now use this in Custom Reports By Channel | By Campaign | By Device | By Gender | By Age etc.
  • 54. Custom Reports Extremely useful: within the limits of the User Interface For complex reports use API
  • 55. Custom Reports Clicks to Book – By Ticket Type (from Event tracking)
  • 56. Custom Reports Drill down to Individual Tickets – Exeter Saturday has most Clicks Compare performance of Exeter Saturday 2016 vs Exeter Saturday 2017 Are sales behind schedule? Traffic growth but lower Clicks to Buy Ratio?
  • 57. Annotations Record Changes to Tracking Record Campaign and Promotion Periods Highlight ‘odd’ data to investigate
  • 58. Lots of Data Pull data via API Match against Business Data Automate Crunch Segments, Dimensions, Metrics Take Action
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  • 60. PowerQuery > Data Model > PowerPivot Measures > Excel visualisation Same Data Model, Measures and Query could also be used in PowerBI
  • 61. Manual: Pull data via API to Sheets and Download. Download csv from GA UI Automate: Next Analytics, Analytics Edge, Supermetrics, Power Query, PowerBI
  • 62. Calculated Metrics Custom Filters Visualisations Links to: • Google Analytics • AdWords • Sheets • BigQuery and more
  • 63. • Automatic Refresh • Custom Filters • Date Range • Dimension Filters • Custom Segments Up to 20 Pages per Report Unlimited Reports Free!
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  • 67. Distribution matters • 2 users off the scale of this chart • 130+ items per purchase “Average” is misleading if you don’t know how it is distributed
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  • 72. Custom Segments User has Clicked Enquiry on Used Motorcycle Label of Event Contains Year: Segment to 2015
  • 73. Channels Report Segment can then be applied to other Reports: e.g. Channels
  • 74. Segment Share of Contribution Share of Sessions or Event Clicks easily compared Or Targeted. Or Reported against # Stock of each Year being advertised etc.
  • 75. Shortcuts Create shortcuts to quickly re-apply Segments/Filters
  • 76. Referrers Advertising Stock Costs Money Different Portals Different Audiences Different Stock
  • 77. Referrers “Price To” from ?= Search string from Referral Path
  • 78. Regular Expressions “Price To” from ?= Search string from Referral Path BUT Different format for “Price To” Search on EVERY Referrer site  Expresso http://www.ultrapico.com/expresso.htm (Windows Only) http://regexr.com/ (Browser)
  • 80. Custom Channel Groups Default Channels are ok if you tag inbound links and adverts accurately But Custom Channel Groupings are better
  • 81. Custom Channel Groups Start with Default as Template Divide Channels more precisely Rules apply top to bottom Different Groups Different Levels of Detail Paid Search is a good example By Type: • Shopping • Display • Text • Video By Spend: • High Cost • Medium Cost • Low Cost Buying Cycle, Competition, Volume etc.
  • 82. This is a Top line Channel splitting – slightly more detail than Default Channels: • Paid: Main Ad types, Top Funnel, Middle Funnel, Bottom Funnel • Organic Search: Google or Other – Keyword Known/Not Provided • Email: Which Mailing list (Mailchimp or EventBrite) Custom Channel Groups
  • 83. Custom Channel Groups More detail on Paid Campaigns • Paid Search • Paid Social 2nd Dimension of Keyword Exeter Race promotion • Keywords mostly Exeter • Some Top Funnel generic
  • 85. Demographic Reports Make sure Privacy Policy is compliant Make sure this option is legal in your territories
  • 86. Age Bands User Volumes By Age Band
  • 89. Affinity & Interests Combine with a Segment of Users Who Clicked but didn’t Enquire …can be Targeted with appropriate Stock
  • 91. Content Grouping Must have Edit Permission for the View • Template • Type • Categories
  • 92. Content Grouping Tag Manager makes it easier dataLayer makes it simple Page Template: Used Bikes > All Used Stock Page Titles Makes: Ducati > Ducati Models Models: Multistrada > Multistrada Variants (S, Enduro etc.) Model Year: 2009, 2010, 2011 etc. Price Bands: £5,000 - £7,499 | £7,500 - £8,999 | £9,000 - £10,499 etc Up to 5 Groupings
  • 93. Content Grouping Pages Report – lots of detail Hard to see which Categories work best
  • 94. Content Grouping Categories Content Group Applied: Apparel clearly more popular than Brands and Bags Can also be used to create Segments
  • 96. What YOU can investigate
  • 97. @pjeedai Data is one thing Intelligent use of data is everything
  • 98. Thank you for listening
  • 99. Resources Get Started With Tag Manager & Google Analytics https://analytics.google.com/analytics/academy/ Learning Resources https://www.simoahava.com/ http://www.lunametrics.com/blog/ http://www.analytics-ninja.com/blog.html Demographics and Advertising Tools Policy Requirements https://support.google.com/analytics/answer/2700409?hl=en-GB&utm_id=ad Regular Expression Tools http://regexr.com/ (Online) http://www.ultrapico.com/Expresso.htm (Windows) Data Studio https://www.google.com/analytics/data-studio/ API Tools http://www.analyticsedge.com/ https://supermetrics.com/ http://www.nextanalytics.com/ https://powerbi.microsoft.com/en-us/ https://www.scitylana.com/ Connect on Linked In https://www.linkedin.com/in/timstewart/ Or ask me a question on Twitter @pjeedai