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1
@BrianClifton
verified-data.com
poor
^
The State of Google
Analytics Data
10 years of auditing Google Analytics
and what I have learnt...
BrianClifton.com
2
About Brian Clifton
Circa 1974...!
BrianClifton.com
(1st) Head of Web Analytics, EMEA
2005-8
1990's Chemistry
100k books sold
Launched 2018
3
A short history of web analytics… the biggest hockey stick I have ever seen!
2005 2006
Industry total:
30,000 accounts
Within the first week:
100,000 accounts created…!
2007
one year “pause”
14-Nov-2005
First FREE
enterprise tool
verified-data.com
2018
+30
million
websites
4
Defining Poor Data Quality...
verified-data.com
LoremIpsumis
simplydummytext
oftheprintingand
typesettingindustry.
LoremIpsumhas
beentheindustry's
standarddummy
texteversincethe
1500s,whenan
unknownprinter
Lorem ipsum
dolor sit amet,
consectetur
adipiscing elit, sed
do eiusmod
tempor incididunt
ut labore et dolore
magna aliqua. Ut
enim ad minim
veniam,
Duplicate
data
Missing
data
Inaccurate
data
Incorrect
data
BAD DATA IS...
Lorem Ipsum is
simply dummy text
of the printing and
text ever since the
1500s, when an
unknown printer
X
Lorem Ipsum is
simply dummy text
of the printing and
typesetting industry.
Lorem Ipsum has
been the industry's
standard dummy
text ever since the
1500s, when an
unknown printer
5
The problem - a general lack of trust...
verified-data.com
Reasons for this:
• Data setup is often not understood
• Data collection is rarely verified
• Poor data governance - particularly Google Analytics
6
Can we quantify this lack of trust?
469
Take the survey at www.menti.com and use code 918 302
7.8
6.4
6.3
6.3
5.7
Low Trust High Trust
Q: Do you trust your analytics data?
7
Even experts need help...
verified-data.com
Good Data? Bad Data?
• Because websites constantly change
• Changes usually performed by others
• Time pressures lead to campaign "laziness"
• Getting governance wrong costs $$$ (GDPR)
• Bad data looks just like good data!
Take the survey at www.menti.com and use code 918 302
8
What is the cost of poor data quality...?
verified-data.com
Source: Harvard Business Review
- Up to 50% of employee time is wasted hunting for
data, finding and correcting errors, and searching for
confirming sources.
Take the survey at www.menti.com and use code 918 302
9
`
...and the haystack is
constantly moving!
But, the needle looks just the same as straw...
10
The Study
before automation
11
Websites audited
The study was from the manual audit of 75 commercial websites, 41% of which had an
e-commerce facility. These are all brand leaders - 13 of which with a global presence.
Typically traffic volume was between 100,000 and 10 million visits per month (three over 100M).
verified-data.com
Count
`
Country or Region
12
The weighted scorecard method...
Data Quality Index 40.7
Out of 100
13
The weighted scorecard method...
Quality Index 40.7
Out of 100
14
The weighted scorecard method...
Quality Index 40.7
Out of 100
1.0
1.0
2.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
0.5
1.0
1.0
15
The weighted scorecard method...
Quality Index 40.7
Out of 100
Green =10
Amber = 5
Red = 0
16
The weighted scorecard method...
40.7Quality Index
Out of 100
Green =10
Amber = 5
Red = 0
Multiply weights x Score
17
To calculate the data's Quality Index...
Out of 100
Data Quality Index 40.7
Green =10
Amber = 5
Red = 0
Sum and normalised
(out of 100)
18
Overall score patterns...
Visitor Segmentation
Column = website audit
Quality Index
Audit Scorecard
Item
Account Setup & Governance
GATC Deployment
AdWords
Site Search Tracking
File Download Tracking
Outbound Link Tracking
Form Completion Tracking
Video Tracking
Error Page Tracking
Transaction Tracking
Event Tracking
Goal Setup
Funnel Setup
Visitor Segmentation
CampaignTracking
Score out of 100
75 websites
19
RESULTS 1
verified-data.com
Lowest score = 4.5 Highest score = 73.1
Average = 35.7
Only 12.0% of sites score above 50
Quality Index
Count
Histogram of Quality Index
Quality is generally very low...
20
RESULTS 2
Audit Scorecard
Item
Account Setup & Governance
GATC Deployment
AdWords
Site Search Tracking
File Download Tracking
Outbound Link Tracking
Form Completion Tracking
Video Tracking
Error Page Tracking
Transaction Tracking
Event Tracking
Goal Setup
Funnel Setup
Visitor Segmentation
CampaignTracking
1 in 5
sites have a
PII issue
PII is a big problem... still
21
PII most often found in URLs and page titles...
Usually by
accident...
22
Other places for PII - CD, events, ecomm fields...
Can also be
deliberate...
23
Where does PII come from...?
Also login areas via <title> tags
e.g. "Welcome back Brian@..."
Collected mostly via form fields...
Audit Scorecard
Item
Account Setup & Governance
GATC Deployment
AdWords
Site Search Tracking
File Download Tracking
Outbound Link Tracking
Form Completion Tracking
Video Tracking
Error Page Tracking
Transaction Tracking
Event Tracking
Goal Setup
Funnel Setup
Visitor Segmentation
CampaignTracking
24
RESULTS 3
Examples of Transaction Tracking failures:
• Significant difference from backend data e.g.
revenue, transactions
• Odd values e.g. negative tax, shipping mix ups
• Repeated transaction IDs
• Discounting accounted differently
• Currency mixing
25%
get these
correct
Audit Scorecard
Item
Account Setup & Governance
GATC Deployment
AdWords
Site Search Tracking
File Download Tracking
Outbound Link Tracking
Form Completion Tracking
Video Tracking
Error Page Tracking
Transaction Tracking
Event Tracking
Goal Setup
Funnel Setup
Visitor Segmentation
CampaignTracking
25
What we have found by auditing...
Examples of failures:
• Limited use of campaign tracking
• Confused use of campaign tracking parameters
• Duplicate use of parameters e.g. Email v e-mail v email
marketing
• Using campaign tracking internallyOnly 18%
get this correct
26
Overall results
24%
54%
50%
20%
34%
19%
24%
8%
50%
26%
25%
18%
8%
7%
18%
Percentage
Correct
Item
Account Setup & Governance
GATC Deployment
AdWords
Site Search Tracking
File Download Tracking
Outbound Link Tracking
Form Completion Tracking
Video Tracking
Error Page Tracking
Transaction Tracking
Event Tracking
Goal Setup
Funnel Setup
Visitor Segmentation
CampaignTracking
44%
32%
25%
30%
5%
10%
16%
23%
3%
19%
36%
39%
18%
8%
47%
32%
14%
25%
50%
61%
71%
60%
69%
46%
55%
39%
43%
73%
85%
35%
Percentage
Amber
Percentage
Wrong/missing
27
Advanced web metrics is about doing the basics
really well and applying it in a clever way
My key learning during this time...
28
Take control of your data with automation
It doesn't have to be like this...
29
Automated, Deep-Dive, Comprehensive Auditing...
verified-data.com
DISCOVERY - looks for content, simulates visitor action, then
listens for tracking signals.
STRESS TESTS - with artificial intelligence performed on
your Google Analytics account.
Verified Data's unique HYBRID method:
30
Further details of study:
verified-data.com/study
Take the survey at www.menti.com and use code 918 302

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The (poor) State of Google Analytics Data

  • 1. 1 @BrianClifton verified-data.com poor ^ The State of Google Analytics Data 10 years of auditing Google Analytics and what I have learnt... BrianClifton.com
  • 2. 2 About Brian Clifton Circa 1974...! BrianClifton.com (1st) Head of Web Analytics, EMEA 2005-8 1990's Chemistry 100k books sold Launched 2018
  • 3. 3 A short history of web analytics… the biggest hockey stick I have ever seen! 2005 2006 Industry total: 30,000 accounts Within the first week: 100,000 accounts created…! 2007 one year “pause” 14-Nov-2005 First FREE enterprise tool verified-data.com 2018 +30 million websites
  • 4. 4 Defining Poor Data Quality... verified-data.com LoremIpsumis simplydummytext oftheprintingand typesettingindustry. LoremIpsumhas beentheindustry's standarddummy texteversincethe 1500s,whenan unknownprinter Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, Duplicate data Missing data Inaccurate data Incorrect data BAD DATA IS... Lorem Ipsum is simply dummy text of the printing and text ever since the 1500s, when an unknown printer X Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer
  • 5. 5 The problem - a general lack of trust... verified-data.com Reasons for this: • Data setup is often not understood • Data collection is rarely verified • Poor data governance - particularly Google Analytics
  • 6. 6 Can we quantify this lack of trust? 469 Take the survey at www.menti.com and use code 918 302 7.8 6.4 6.3 6.3 5.7 Low Trust High Trust Q: Do you trust your analytics data?
  • 7. 7 Even experts need help... verified-data.com Good Data? Bad Data? • Because websites constantly change • Changes usually performed by others • Time pressures lead to campaign "laziness" • Getting governance wrong costs $$$ (GDPR) • Bad data looks just like good data! Take the survey at www.menti.com and use code 918 302
  • 8. 8 What is the cost of poor data quality...? verified-data.com Source: Harvard Business Review - Up to 50% of employee time is wasted hunting for data, finding and correcting errors, and searching for confirming sources. Take the survey at www.menti.com and use code 918 302
  • 9. 9 ` ...and the haystack is constantly moving! But, the needle looks just the same as straw...
  • 11. 11 Websites audited The study was from the manual audit of 75 commercial websites, 41% of which had an e-commerce facility. These are all brand leaders - 13 of which with a global presence. Typically traffic volume was between 100,000 and 10 million visits per month (three over 100M). verified-data.com Count ` Country or Region
  • 12. 12 The weighted scorecard method... Data Quality Index 40.7 Out of 100
  • 13. 13 The weighted scorecard method... Quality Index 40.7 Out of 100
  • 14. 14 The weighted scorecard method... Quality Index 40.7 Out of 100 1.0 1.0 2.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.5 1.0 1.0
  • 15. 15 The weighted scorecard method... Quality Index 40.7 Out of 100 Green =10 Amber = 5 Red = 0
  • 16. 16 The weighted scorecard method... 40.7Quality Index Out of 100 Green =10 Amber = 5 Red = 0 Multiply weights x Score
  • 17. 17 To calculate the data's Quality Index... Out of 100 Data Quality Index 40.7 Green =10 Amber = 5 Red = 0 Sum and normalised (out of 100)
  • 18. 18 Overall score patterns... Visitor Segmentation Column = website audit Quality Index Audit Scorecard Item Account Setup & Governance GATC Deployment AdWords Site Search Tracking File Download Tracking Outbound Link Tracking Form Completion Tracking Video Tracking Error Page Tracking Transaction Tracking Event Tracking Goal Setup Funnel Setup Visitor Segmentation CampaignTracking Score out of 100 75 websites
  • 19. 19 RESULTS 1 verified-data.com Lowest score = 4.5 Highest score = 73.1 Average = 35.7 Only 12.0% of sites score above 50 Quality Index Count Histogram of Quality Index Quality is generally very low...
  • 20. 20 RESULTS 2 Audit Scorecard Item Account Setup & Governance GATC Deployment AdWords Site Search Tracking File Download Tracking Outbound Link Tracking Form Completion Tracking Video Tracking Error Page Tracking Transaction Tracking Event Tracking Goal Setup Funnel Setup Visitor Segmentation CampaignTracking 1 in 5 sites have a PII issue PII is a big problem... still
  • 21. 21 PII most often found in URLs and page titles... Usually by accident...
  • 22. 22 Other places for PII - CD, events, ecomm fields... Can also be deliberate...
  • 23. 23 Where does PII come from...? Also login areas via <title> tags e.g. "Welcome back Brian@..." Collected mostly via form fields...
  • 24. Audit Scorecard Item Account Setup & Governance GATC Deployment AdWords Site Search Tracking File Download Tracking Outbound Link Tracking Form Completion Tracking Video Tracking Error Page Tracking Transaction Tracking Event Tracking Goal Setup Funnel Setup Visitor Segmentation CampaignTracking 24 RESULTS 3 Examples of Transaction Tracking failures: • Significant difference from backend data e.g. revenue, transactions • Odd values e.g. negative tax, shipping mix ups • Repeated transaction IDs • Discounting accounted differently • Currency mixing 25% get these correct
  • 25. Audit Scorecard Item Account Setup & Governance GATC Deployment AdWords Site Search Tracking File Download Tracking Outbound Link Tracking Form Completion Tracking Video Tracking Error Page Tracking Transaction Tracking Event Tracking Goal Setup Funnel Setup Visitor Segmentation CampaignTracking 25 What we have found by auditing... Examples of failures: • Limited use of campaign tracking • Confused use of campaign tracking parameters • Duplicate use of parameters e.g. Email v e-mail v email marketing • Using campaign tracking internallyOnly 18% get this correct
  • 26. 26 Overall results 24% 54% 50% 20% 34% 19% 24% 8% 50% 26% 25% 18% 8% 7% 18% Percentage Correct Item Account Setup & Governance GATC Deployment AdWords Site Search Tracking File Download Tracking Outbound Link Tracking Form Completion Tracking Video Tracking Error Page Tracking Transaction Tracking Event Tracking Goal Setup Funnel Setup Visitor Segmentation CampaignTracking 44% 32% 25% 30% 5% 10% 16% 23% 3% 19% 36% 39% 18% 8% 47% 32% 14% 25% 50% 61% 71% 60% 69% 46% 55% 39% 43% 73% 85% 35% Percentage Amber Percentage Wrong/missing
  • 27. 27 Advanced web metrics is about doing the basics really well and applying it in a clever way My key learning during this time...
  • 28. 28 Take control of your data with automation It doesn't have to be like this...
  • 29. 29 Automated, Deep-Dive, Comprehensive Auditing... verified-data.com DISCOVERY - looks for content, simulates visitor action, then listens for tracking signals. STRESS TESTS - with artificial intelligence performed on your Google Analytics account. Verified Data's unique HYBRID method:
  • 30. 30 Further details of study: verified-data.com/study Take the survey at www.menti.com and use code 918 302

Hinweis der Redaktion

  1. 40 mins total time (allow 10 mins for Q&A)
  2. Duplicate = duplicate tracking pixels Missing = missing tracking pixels or visitor interactions (events) Inaccurate = data pollution (e.g. robots, testing, staff users) Incorrect = misconfiguration (e.g. wrong filters, segmentation, linking Adwords, ecomm variables)
  3. Think about your own company website...
  4. https://www.bluesheep.com/blog/what-is-the-cost-of-poor-quality-data-0 https://www.siriusdecisions.com/Research-Articles/T/TheImpactofBadDataonDemandCreation https://hbr.org/2013/12/datas-credibility-problem https://www.brighttalk.com/webcast/11135/152235/the-high-cost-of-bad-data-and-what-you-can-do-about-it
  5. Remove the human frailties and run in almost real-time... https://pixabay.com/en/fruit-isolated-apple-orange-fruits-2615309/