Web Analytics

A New Statistical Domain?

Paul Askew

Royal Statistical Society

2010 International Conference 13-17 September 2010

Brighton, UK

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

1. Domain

• 8,722,474 UK web sites (Nominet Aug 2010)

• 81,632,634 Site management transactions (Aug 2010)

Large number of sites, and increasing

1. Domain

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

Large (public) sites with lots of activity

2. Data

home

Log File

html java

Service

A B AB C

track every click

2. Data

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

The scope of the data is increasing and complicating

2. Data

Overall

• Large volumes in real time

• Precise and accurate

• Consistent (ABCe)

Issues

• Exit time

• Cookies and Java

• Hotel problem

Data has some defining characteristics

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

Measures evolve from marketeers and web designers

3. Measures

4. Tools

a. DIY

b. Sector Specific

Google (+74)

Omniture

Technorati

etc…

c. Generic

SPSS,

SAS

etc…

…are maturing

4. Tools

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?

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…

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