In this session, we explain how to mine GA for broken device experiences, flows, funnel blocks and more... Using a new grid tool we've developed, you can pull multi-dimensional segmented funnel and metric data from Google Analytics - we explain how it works, why you need it and what problems it solves. Find where your site is leaking money through data
3. Spot the Difference
Peter Baecke
Angry Heavy Metal Singer
Likes : Eating bats on stage
Pieter Baecke
Gatekeeper of the Grid
Likes : Eating Google APIs
4. Batman, this
website just
needs…
Spot the Difference
Craig Sullivan
Need for Speed Fanatic
Likes : Having no social life
Craig Sullivan
High Priest of the Grid
Likes : Having no social life
5. Spot the Difference
Peter O’Neill
PM of Papua New Guinea
Likes : Big Inward Investment
Peter O’Neill
God of the Grid
Likes : Big Analytics Investment
6. @OptimiseOrDie
Cross Device Optimisation
1. What’s the problem here?
2. What is this costing us?
3. Can Google Analytics help us?
4. How do I get the right data?
5. What is Grid Optimisation?
6. Tool Walkthrough
7. Summary & Resources
Sep 2015, Ruuhijarvi
15. @OptimiseOrDie
What happens if you discriminate?
Mac User?
fuck you!
Internet
Explorer
fuck you!
Android
Mobile?
fuck you!iPad?
fuck you!
iPhone4?
fuck you!
17. @OptimiseOrDie
• Clothing 1M per month, 2 bugs
• Travel 2M per month, 13 bugs
• Telecoms 1.4M per month, 3 bugs
• Travel 0.6M per month, 5 bugs
• Event Site 2.5M per month, 11 bugs
– £90M per annum in bugs!
– 6 days to find, 5 days to fix
– 11,764 X Return on Investment
– What if this figure is larger than your IT budget?
How much do Broken Experiences cost?
19. @OptimiseOrDie
Most companies think they know this stuff:
• What Devices & Browsers do our customers use?
• How much money or engagement do they contribute?
• “What If” they worked better - how much is that worth?
• None of my clients had an accurate Testing List
• But you can get that from Google Analytics, right?
How Much do Bugs Cost?
21. @OptimiseOrDie
1. The Data Model Sucks
• Google Analytics is NOT helping
• I’ve now spent nearly 3 weeks on this!
• The Device Model completely sucks
• Google & Apple recently made it worse
• “My Pain is Your Gain”
22. 2. The Data Model Sucks
• This is my ideal diagram
• Split traffic by Device Category
• Split by Operating System
• Split into ‘versions’ or ‘models’
• Let’s see how reality matches up!
23. 3. Data Model – Apple iPhones
• Something is wrong with iPhones!
• Where is the iPhone Model information?
• It simply isn’t there, before the 13th January 2016
• Now we have them, but only for 5-15% of people – WTF?
Before 12/1/16 After 12/1/16
24. 4. Data Model – Apple iPhones
An explanation:
• Safari browsers show up as ‘iPhone’ only in GA
• Safari ‘in app’ browsing shows up as ‘iPhone X”
• So only in app browsing sets the model number
• Genuinely bloody confusing & fragments the data
• Mobile Device Model or Mobile Device Info are now useless
• So how can you tell what iPhone models people have?
• You have to use RESOLUTION!
25. @OptimiseOrDie
iPhone Models in Google Analytics
Screen Resolution
320 x 480 = iPhone 4/4S
320 x 568 = iPhone 5/5S
375 x 667 = iPhone 6
414 x 736 = iPhone 6+
26. 5. Data Model – Android Mobiles
• Mobile Device Info and Mobile Device Model are OK
• For example -> “Samsung SM-G900F Galaxy S5” and “SM-G900F”
• What about “Screen Resolution” for Android?
• Heaps of Galaxy models (S5, S6, S4, S5, Note 4,Note 3) – they all say the
same thing for resolution - 640x360!
• What about the new “Browser Size” dimension (viewport)?
• Many Samsung models report 980xSomething
• Tip! Use www.gsmarena.com for instant technical spec lookups!
27. How do I get useful and
reliable data?
@OptimiseOrDie
28. 3. What is reliable? (mobile)
• Reliable on iOS Mobile:
Screen Resolution
OS version
• Avoid on iOS Mobile:
Mobile Device Info
Device Model
Browser Size
• Reliable on Droid Mobile:
Mobile Device Info
Device Model
OS version
• Avoid on Droid Mobile:
Screen Resolution
Browser Size
29. 4. What is reliable? (tablet)
• Reliable on iOS Tablet:
OS version
• Avoid on iOS Tablet:
Mobile Device Info
Mobile Device Model
Browser Size
Screen Resolution
• Reliable on Droid Tablet:
Screen Resolution
Device Info / Device Model
OS version
• Avoid on Droid Mobile:
Screen Resolution
Browser Size
30. 5. What is reliable? (desktop)
• Desktop is in very good shape
• You want to split the desktop data 4 ways at least:
o Windows
o Mac
o Linux
o Chrome OS
• You then split these by browser ‘brand’ and version.
• Let’s take a look at the whole model mapped out.
31. 5. You Need a Device Experience Meta Layer
MOBILE
iOS
Resolution
(Model)
Android
Mobile
Device Info
Windows Mobile
Device Info
TABLET
iOSNOTHING
Android
Mobile
Device Info
Windows
Resolution
(Model)
DESKTOP
Windows Mac Linux
Browser
Version
Browser
version
Browser
version
32. 5. We’ve built a tool to do this!
• We wanted a tool for optimising device & browser experiences
• Why not extend this to everything else?
• And so The Grid was born:
For Early Beta Access : ProfitGrid.io
• And now Pieter will show you how it works!
34. @OptimiseOrDie
1. Data Cubes for Optimisation
• Sessions
• % Sessions
• Users
• Pageviews
• % new sessions
• Bounce rate
• Pageviews per session
• Average time on site
• % who use site search
35. @OptimiseOrDie
2. Data Cubes for Optimisation
• Ecommerce conversion rate
• Non bounce Ecom conversion rate
• Transactions
• Revenue
• Items
• Average transaction value
• Items per transaction
37. @OptimiseOrDie
4. Segmented and ‘On the fly’ funnels
• Google Analytics Basic doesn’t have the funnel stuff that
serious optimisers need!
• Our Funnel Builder lets you use segments, pages, regular
expressions or events, to tell us what the steps are in
your model
• This means ‘On the Fly’ funnels for any date range
• You get ‘User’ funnels as well as ‘Session’ funnels
• Hell, we even do the calculation of loss rates per funnel
step for you!
• The next bit is the interesting bit – how we then segment
this data across many dimensions
38. % Loss per step
Funnel success
Funnel Step 2
Funnel Step 1
Sales
Ecommerce
Behaviour
@OptimiseOrDie
5. Adding the funnel cubes
Traffic • Here are our finished cubes!
40. Funnel success
Funnel Step 2
Funnel Step 1
Sales
Ecommerce
Behaviour
@OptimiseOrDie
7. Dimensions we have or are building
Traffic
• New & Returning Visitors
• Channel breakdown
• Country breakdown
• iPhone Models
• Android Models
• Windows Browsers
• Mac Browsers
• Landing page(s)
• Content page(s) viewed
• Demographics
• Days to conversion
• Path Length
Want something? Get in touch!
46. 1. Roadmap
Beta Version
• Full grid system
• New & Returning
• Device Category
• Channels,
Countries
• Mobile & Desktop
• Tablet & Browser
• Please give us
feedback!
Full Release
• Content Grouping
• Landing Grouping
• Age / Gender
• Enhanced Ecom
• Days to
Conversion
• Path Length
• 1-2 additional data
cubes
• Fixes/Bugs &
Feedback
Auto Grid
• Auto Grid Mining
(detection of
broken
experiences or
dimensions)
• Statistics Flags
• Sampling
workarounds
• Automatic and
intelligent grid
analysis
• Colour coding
Machine Grid
• Tripwire Analytics
• Historical Data fed
into Machine
Learning shizzle
• Continuous
monitoring for
busted
experiences,
marketing or flows
– in real time.
• Automatically
detect costly
issues now, next
week, all year!
47. 2. We use it – what did we find?
• Saves the analyst huge amounts of manual work
• Narrows the discovery time for ‘big wins’ by days, not hours
• Makes you consider data that’s normally not there at all
• Know what needs fixing and what to leave well alone
• Gets you a very precise list for device lab or QA testing
• Get completely segmented funnels & step drops in 2 minutes instead of 6-8
hours!
• Find the experiences, channels, flows or devices that are broken!
• Find the ‘missing conversions’ in every site
• Oh yeah, it’s free!
48. Hacking
efficiency/time/
delight/productivity/fun
Tell your friends good
Lovable Empathetic Delightful
Self actualisation Life changing Rewiring
FUNCTIONAL
ACCESSIBLE
USABLE
USEFUL
PERSUASIVE
COMPELLING
TRANSFORMATIONAL
Mobile Tablet Browser Device Rendering
Performance Accessibility Platforms
Comprehension Affordance Simplicity Relevance Clarity Context
Utility Tasks Goals Steps Completion Progression
Resonant Authentic Compelling
Consistent Benefits Value Trust
Social Integration and Proof
Habits Nudges Addictions Lifecycle
Promotions Personalisation Brand
Belonging Trusted Emotive
Craig’s Hierarchy of Product Needs:
49. Thank you!
Early Beta Access ProfitGrid.io
XDO – Full Article bit.ly/XDOfull
Build your own device lab bit.ly/MobileDeviceLab
Google Analytics Templates bit.ly/XDOTemplates
Mobile Checklist for XDO bit.ly/MobiCheck
Excel Grid and Dimensions bit.ly/TheGridLayout
Feedback & Suggestions sullivac@gmail.com
pieter@zetom.nl
@OptimiseOrDie
Editor's Notes
I’ve been working on this presentation and thinking about it for over two months now. And this is one of the first graphs I wanted to include, because it represents the hype cycle in AB testing.
This is what a lot of companies go through with new technology adoption, so I wanted to show you what the AB testing hype cycle would look like [CLICK]
I’ve been working on this presentation and thinking about it for over two months now. And this is one of the first graphs I wanted to include, because it represents the hype cycle in AB testing.
This is what a lot of companies go through with new technology adoption, so I wanted to show you what the AB testing hype cycle would look like [CLICK]
I’ve been working on this presentation and thinking about it for over two months now. And this is one of the first graphs I wanted to include, because it represents the hype cycle in AB testing.
This is what a lot of companies go through with new technology adoption, so I wanted to show you what the AB testing hype cycle would look like [CLICK]
I’ve been working on this presentation and thinking about it for over two months now. And this is one of the first graphs I wanted to include, because it represents the hype cycle in AB testing.
This is what a lot of companies go through with new technology adoption, so I wanted to show you what the AB testing hype cycle would look like [CLICK]
I’ve been working on this presentation and thinking about it for over two months now. And this is one of the first graphs I wanted to include, because it represents the hype cycle in AB testing.
This is what a lot of companies go through with new technology adoption, so I wanted to show you what the AB testing hype cycle would look like [CLICK]