The document discusses web analytics, focusing on the measurement, collection, analysis, and reporting of internet data to optimize web usage. It examines the increasing complexity and opportunities in this evolving field, emphasizing the importance of tools, data characteristics, and statistical measures. The paper concludes with a vision for the future role of statisticians in a data-driven society.

1. Web Analytics
A New Statistical Domain?
Paul Askew
Royal Statistical Society
2010 International Conference
13-17 September 2010
Brighton, UK

2. Introduction
Web analytics:
Measurement, collection, analysis and reporting of
internet data for understanding and optimising web
usage. (WAA). …. reporting of metrics
1. Domain
2. Data
3. Measures
4. Tools
5. Opportunities

3. 1. Domain
Large number of sites, and increasing
• 8,722,474 UK web sites (Nominet Aug 2010)
• 81,632,634 Site management transactions (Aug 2010)

4. 1. Domain
Large (public) sites with lots of activity
No. 10 (Aug 2010)
• 498,871 unique visitors
• 721,767 visits
• 2,135,427 page views
Direct.gov.uk (Aug 2010)
• 15,107,447 visits for 52,687,308 page views
BBC Radio (July 2010)
• 3,477,571 visits for 21,071,588 listening hours

5. 2. Data
home Service
track
every Log html
click File java
A AB B C

6. 2. Data
The scope of the data is increasing and complicating
Phase 1: Visits
Phase 2: Characteristics
• Browser
• Source (incl. search engine, ‘spiders’)
• Date/time, entry/exit pages, duration
Phase 3: Engagement
• Dynamic content
• Blogs and forums – sentiment
• Social Media – networks

7. 2. Data
Data has some defining characteristics
Overall
• Large volumes in real time
• Precise and accurate
• Consistent (ABCe)
Issues
• Exit time
• Cookies and Java
• Hotel problem

8. 3. Measures
Measures evolve from marketeers and web designers
1. Measure of activity
• Unique visitors
2. Measures of effectiveness
• Bounce rate, conversion rate
3. Measures of relationship
• More process than event based (sequence detection)
• Frequency....loyalty
• Propensity….days and visits to action

9. 4. Tools
…are maturing
a. DIY
b. Sector Specific
Google (+74)
Omniture
Technorati
etc…
c. Generic
SPSS,
SAS
etc…

10. 4. Tools

11. 5. Opportunities
1. Public good
• Online services and user interface/experience
• Age of austerity – tougher decisions, tighter evidence
2. Focus on messages from the data
• 90/10 Rule, insufficient expert capacity
• Value of narrative commentary (eg UKSA)
3. Real time vs Strategic analysis
• News vs trends
4. Statistical Opportunity
• Data volumes, issues, new techniques?

12. 5. Opportunities
5. Experimentation and geolocation
6. Visualisation
7. Multiple data sources
8. Free data and free tools
9. Role for Meta-Meta- Data (‘sweater’ data?)
10. Interesting and challenging…

13. 5. Opportunities
“A new era is dawning for what you might call the
datarati….The sexy job in the next 10 years will be
statisticians” (Google, Jan 2009)
“A society in which our lives and choices are enriched
by and understanding of statistics” or “Understand
the society and world we live in, and get the most out
of our lives.” (Getstats, Sept 2010)
Do let me know how you get on with web analytics
pauljaskew@gmail.com