Web analytics is the measurement, collection, analysis and reporting of internet data for purposes of understanding and optimizing web usage. Web analytics is not just a tool for measuring web traffic but can be used as a tool for business and market research, and to assess and improve the effectiveness of a web site. In this presentation I describe a four step web analytics approach that every organization need to follow for a structured way to measure your online success.

1. Web Analytics
How to measure online success
Tim Stierman

2. Web analytics is the measurement, collection, analysis and reporting
of internet data for purposes of understanding and optimizing web
usage.
• Collecting (online) data
• Measuring
• Analyzing
• Reporting
• Continuously!
Web analytics?
Marketing without analyzing the results is like shooting an arrow in the dark. You will
never know if you hit the right target”

3. • Web analytics must be part of every online
business, but it is not. Why?!?!
– Not the right tools
– Not the right implementation
– Not enough resources
– No analytical knowledge
– Not ready for (online) change
• Integrate web analytics in the whole
organization
Be a web analytics company

4. • ROI of your investment!
• Effective marketing campaigns
• Conversion optimization
• Information about your unprofitable activities
• Insights about your most important
customers, sources, products and content
What's in it for me?

5. How mature is your organization?
The proposed model presents five maturity states:
1. Analytically impaired
2. Analytically initiated
3. Analytically operational
4. Analytically integrated
5. Analytical competitor
The six key process areas:
1. Management
2. Objectives (KPI) definition
3. Scoping
4. The Analytics Team and Expertise
5. Improvement Process and Analysis Methodology
6. Technology and Data Integration

6. 1. Determine your KPIs
2. Measure what
you need to measure
3. Start with good reporting
4. Optimization process
Analytical plan of approach
Reporting
Analyse
Concepts
Optimization
Online KPI’s
Analytics
implementation
Analytics
Checklist

7. • Key performance indicators (KPIs):
organizations use KPIs to evaluate their success on business
objectives
• KPIs need to be SMART
• Business objectives contains at least one KPI
• Determine your current KPI position and your KPI target
• Think about the strategy that will help you achieve your KPI
targets
• Put your KPIs in a organized model:
– Digital performance model
– KPI E-Commerce Model
1) Determine you KPIs

8. Business Objective 1 Business Objective 2 Business Objective 3
Digital Performance Model
Determine your online KPIs
Strategy:
KPI:
Target:
Current:
Tools:
Segments:
Strategy:
KPI:
Target:
Current:
Tools:
Segments:
Strategy:
KPI:
Target:
Current:
Tools:
Segments:
Reporting

9. KPI E-Commerce Model

10. 2) Analytic implementation
• Choosing the right analytical tools
• Correct implementation of the code
• Can you measure your KPIs?
• Set your online goals
• Do you have access to all relevant data?
Note: use the Google Analytics checklist to see what you are measuring and
what you could measure

11. Google Analytics Checklist Yes No N/A
Tracking Code
Asynch Code
Universal Analytics
E-Commerce Tracking
App Analytics
Social Media Analytics
Data Aggregation
Account settings
IP-Filter
Site Search
Link Google AdWords
Link Google Webmastertools
Goal Measurements
Funnel Visualisation
Advanced Tracking
Goals & funnel
Event Tracking
Campaign Tags
Custom variable (for segments)
Content Experiments (A/B Testing)
Campaign Tags
404-tracking
App crash measurements
Reporting
Automatic Reporting
Dashboards
Custom reports
Advanced segment reporting

12. • Decide which decision making units (DMUs)
need web analytical reports
• Which metrics are important per DMU
• Web analytic reporting
– Automatic reporting vs customized reports
– Only metrics vs management reports
– Dashboards
– Business reporting (including offline data)
3) Reporting

13. 4) Optimization process
• Identify bottlenecks and opportunities in your reports
• Translate improvements into optimization concepts
• Create hypothesis
• Run tests
– A/B
– Multivariate
– Usability
– Lab research
• Measure the success
• Implement the concept
Reporting
Analyse
Concept
Optimization

14. Future of web analytics
• Now we measuring what has happened
• In the nearby future we are predicting what will
happen
– Will these products sell
– Which content need to optimized
– Calculate faster the (future) ROI of your campaigns
– Predict online behavior of customers
• Predictive analytics: knowing where you will
lose money instead of knowing where you have
lost money

15. Questions?
tim.stierman@liones.nl
www.liones.nl
@timstierman
@LionesNL
http://nl.linkedin.com/in/timstierman/
Don’t hesitate to contact me!