1.
Better conversion with Intelligent Analytics
@pjeedai

2.
Turn user behaviour data
into Value

3.
Understand causes of
bottlenecks on key areas

4.
Think through
factors that may
impact results

5.
Think about YOUR Data

6.
What YOU can investigate

7.
What YOU can investigateExamples and Ideas

8.
Inspire

9.
Tag Manager
Makes all this MUCH easier to do

10.
Tags
Add Events, Scripts with Custom Triggers
Add Extra Dimensions, Metrics, Data to Pageviews, Events, Hits

11.
Variables
Collect Data as Variables
Use Variables for fields in Google Analytics

12.
Page Values
Collect Data from Page or from Back end Source

13.
Send to dataLayer
Collect Data to use in Tag Manager Variables
Variables can also be captured without dataLayer

14.
Event Variables
Variables Can Be Variable

15.
Lookup Variables
If Bike Stock Type = New then use New Stock Variables
If Bike Stock Type = Used then use Used Stock Variables

16.
Variables for Custom Dimensions
Custom Dimension Variables

17.
Tools & Stacks

18.
Google Analytics API Script
or paid plugins like

19.
Google Analytics API to Excel, csv or database
Also API for Facebook, Twitter, AdWords, Search Console & more
Allows scheduled and batch data pulls

20.
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

21.
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

22.
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

23.
Bigger datasets, more powerful statistical analysis
PowerBI cloud has real language querying
“What is the best performing product for revenue this Quarter?”

24.
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

25.
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

26.
User & Session
Recording

27.
Also, you know. Maybe talk to them
Ask Customer Services, Feedback form responses, BCC on Customer Service emails, Jump on a Live Chat

28.
Hit level – Measurement Protocol

29.
Gets a little spendy at the top end but Free Option is good to try out

30.
Metrics and Measurement

31.
Success Events
If [Good Thing] happens
Track [Good Thing]
Ideally [Type of Thing] | [Which Specific Thing] | [What Details]

32.
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)

33.
Fail Events

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Fail Events
Common Issue for eCommerce, Appointments, Holidays
• Conversion Rate Affected by Stock Levels & Availability

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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)

36.
Stock Level Events

37.
Event Goals

38.
Event Goals
Goals are NOT just Sale Complete URL
Clicks, Add, Viewed, Video Play
Events are Ideal for segmenting Goals

39.
Exeter Any Day
Event Click To Book
Individual, Create Team or Join Team
Exeter – Any Day

40.
Exeter Saturday
Event Click To Book
Individual, Create Team or Join Team
Exeter – Saturday ONLY

41.
Exeter Sunday
Event Click To Book
Individual, Create Team or Join Team
Exeter – Sunday ONLY

42.
Clicks By Race Day
With 3 Event Goals – break down ways Total is reached
Compare Click Volumes per Race Day AND Total

43.
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%

44.
Custom Dimensions

45.
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 

46.
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

47.
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

48.
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

49.
Calculated Metrics
Calculate Business Metrics not Web Metrics
Original Price – Discount Price Applied = Value Lost
Buy Exeter Tickets ÷ Click Exeter = Buy to Click Rate

50.
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.

51.
Custom Reports
Extremely useful: within the limits of the User Interface
For complex reports use API

52.
Custom Reports
Clicks to Book – By Ticket Type (from Event tracking)

53.
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?

54.
Annotations
Record Changes to Tracking
Record Campaign and Promotion Periods
Highlight ‘odd’ data to investigate

55.
Lots of Data
Pull data via API
Match against Business Data
Automate
Crunch Segments, Dimensions, Metrics
Take Action

56.
PowerQuery > Data Model > PowerPivot Measures > Excel visualisation
Same Data Model, Measures and Query could also be used in PowerBI

57.
Manual: Pull data via API to Sheets and Download. Download csv from GA UI
Automate: Next Analytics, Analytics Edge, Supermetrics, Power Query, PowerBI

58.
Calculated Metrics
Custom Filters
Visualisations
Links to:
• Google Analytics
• AdWords
• Sheets
• BigQuery
and more

59.
• Automatic Refresh
• Custom Filters
• Date Range
• Dimension Filters
• Custom Segments
Up to 20 Pages per Report
Unlimited Reports
Free!

60.
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

61.
Custom Segments

62.
Custom Segments
User has Clicked Enquiry on Used Motorcycle
Label of Event Contains Year: Segment to 2015

63.
Channels Report
Segment can then be applied to other Reports: e.g. Channels

64.
Segment Share of Contribution
Share of Sessions or Event Clicks easily compared
Or Targeted. Or Reported against # Stock of each Year being advertised etc.

65.
Shortcuts
Create shortcuts to quickly re-apply Segments/Filters

66.
Referrers
Advertising Stock
Costs Money
Different Portals
Different Audiences
Different Stock

67.
Referrers
“Price To” from ?= Search string from Referral Path

68.
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)

69.
Custom Channel Groups

70.
Custom Channel Groups
Default Channels are ok if you tag inbound links and adverts accurately
But Custom Channel Groupings are better

71.
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.

72.
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

73.
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

74.
Demographic Reports

75.
Demographic Reports
Make sure Privacy Policy is compliant
Make sure this option is legal in your territories

76.
Age Bands
User Volumes By Age Band

77.
Gender
User Volumes by Gender

78.
Affinity & Interests
Interesting? Useful?

79.
Affinity & Interests
Combine with a Segment of Users Who Clicked but didn’t Enquire
…can be Targeted with appropriate Stock

80.
Content Grouping

81.
Content Grouping
Must have Edit Permission for the View
• Template
• Type
• Categories

82.
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

83.
Content Grouping
Pages Report – lots of detail
Hard to see which Categories work best

84.
Content Grouping
Categories Content Group Applied:
Apparel clearly more popular than Brands and Bags
Can also be used to create Segments

85.
Think about YOUR Data

86.
What YOU can investigate

87.
@pjeedai
Data is one thing
Intelligent use of data is everything

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Thank you for listening

89.
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