Web analytics provides metrics for understanding website usage and optimizing the user experience. It involves measuring, collecting, analyzing, and reporting data from website visits. Common techniques are web server logging and page tagging with JavaScript. Marketers use web analytics to develop visitor profiles, manage online campaigns, and improve conversion rates. Performance analysts and capacity planners can advise on web analytics implementation and use insights from web analytics to enhance their work, such as diagnosing problems, creating alerts, developing benchmarks, and making forecasts.

1. An Introduction to
Web Analytics
for Performance Analysts
and Capacity Planners
Anna Long
Founder and Principal Analyst
Web AnalyticaSM
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2. Agenda
• Introducing Web Analytics
• How Marketers Use Web Analytics
• How You Can Use Web Analytics
for Performance Management
and Capacity Planning
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3. Defining Web Analytics
“Web Analytics is the measurement,
collection, analysis, and reporting of Internet
data for the purposes of understanding and
optimizing Web usage.”
-- Web Analytics Association Standards Committee, 2008
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4. Today’s
Web Analytics
Technologies
1. Web server logging
(Microsoft Internet Information Services,
Apache Web Server)
2. Page tagging
(Adobe SiteCatalyst,
Google Analytics)
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5. 1. Web Server Logging –
How Does it Work?
• Web servers such as Apache or Microsoft
IIS record activity as they receive and fulfill
requests.
• Web servers provide general-purpose
logging at a very detailed level.
• To prepare the data for analysis, the web
team must clean and organize log records
– a big job!
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6. Web Server Logging –
A Log Record Example
IP Address Timestamp
204.243.130.5 - - [26/Feb/2001:15:34:52 -0600]
"GET / HTTP/1.0" 200 8437 Status and Bytes
"http://xyz.com/crawler?category=dimensional
+modeling" "Mozilla/4.5 [en] (Win98; I)"
Request Referring Page
Example log record from Sweiger2002
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7. Web Server Logging –
Processing Complexities
Web server log records are difficult to map
accurately to user activity:
• One page request generates multiple log records.
• The server writes activity to the log as it transmits
each webpage component.
• The server interleaves records for different page
component requests as it completes each one.
• Hosting webpage components on multiple servers
requires combining the logs from all servers.
• Web 2.0 technologies such as AJAX (Asynchronous
JavaScript and XML) add further complexity.
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8. Web Server Logging –
Making Sense of It All
Several characteristics of web server logging
limit its usefulness for analyzing website user
activity:
• The granularity of recorded activity is frequently
non-optimal -- either too fine or too coarse.
• IP addresses do not always map to unique
visitors.
• Server logs lack visibility into client-side activity
and caching.
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9. 2. Webpage Tagging –
How Does It Work?
User clicks a link to The web analytics
request a webpage server stores data for
subsequent analysis
Web server delivers
requested webpage JavaScript tag
with imbedded execution creates
tagging code cookies and sends
(usually a logging info to a web
JavaScript snippet) analytics server
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10. Webpage Tagging –
A JavaScript Tag Example
<script type="text/javascript">
Account Number
var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-12345-1']);
_gaq.push(['_trackPageview']);
(function() {
var ga = document.createElement('script'); ga.type =
'text/javascript'; ga.async = true;
ga.src = ('https:' == document.location.protocol ?
'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
var s = document.getElementsByTagName('script')[0];
s.parentNode.insertBefore(ga, s);
})();
</script>
Example JavaScript Tag from Google2010e 10

11. Webpage Tagging –
Implementation Complexities
Several characteristics of web page tagging
complicate its successful application for
analyzing website user activity:
• Complex website architectures can be difficult
to tag for accurate data collection.
• Proper maintenance of high-volume tagging for
a major online property is another big job!
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12. Webpage Tagging –
Making Sense of It All
User activity can be difficult to map
accurately with web page tagging records:
• Tag execution can cause webpages to
hang.
• Users can disable cookies or JavaScript
execution.
• Users can delete cookies.
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13. How Marketers Use Web Analytics
Leading marketing organizations have been
very successful using web analytics for:
• Developing visitor profiles
• Managing online marketing campaigns
• Improving conversion
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14. Developing Visitor Profiles
Web analytics enables marketers to tailor
offerings to particular visitor needs by:
• Segmenting the visitor population
• Developing personas
• Analyzing RFM (Recency/Frequency/Monetary
Value)
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15. Managing
Online Marketing Campaigns
Web analytics enables marketers to effectively
track online campaign performance.
• Web analytics allows marketers to tag not only webpages but also the in-
bound links in online marketing material that send visitors to the website.
• This in-bound link-tracking enables marketers to examine in detail what
brings visitors to the website and what they do once they arrive.
• Marketers evaluate the in-bound and conversion data to determine the
effectiveness of their campaigns.
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16. Improving Conversion
Web analytics enables marketers to improve
conversion.
• Conversion is the event where the website visitor
becomes a customer.
• The multi-step process through which conversion
takes place is a conversion funnel.
• Conversion is a leaky funnel, meaning some people
abandon the process – some leak out each step along
the way.
• Marketers attempt to improve conversion by reducing
the leakage.
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17. Sample Conversion Funnel
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18. Sample Conversion Funnel
(Part 1)
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19. Sample Conversion Funnel
(Part 2)

20. How You Can Apply Web Analytics
for Performance Management
and Capacity Planning
(And Vice Versa)
• Advising On Implementation
• Enhancing Your Performance Techniques
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21. Advising on Implementation
As a performance analyst or capacity
planner, you may be asked to consult in
areas such as:
• Placing JavaScript snippets
• Selecting sampling strategies
• Bringing web analytics in-house
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22. Placing JavaScript Snippets –
No Optimal Solution
Snippet placement can cause problems:
• Placement anywhere can slow page
rendering if the analytics server is down.
• Placement at the bottom can cause data to
be lost when visitor leaves a page before
the snippet executes.
• Placement at the top can cause passing of
custom variables to fail.
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23. Selecting Sampling Strategies –
Your Judgment Call
Performance, resource, or budget restrictions
drive some organizations to data sampling.
Several sampling approaches are:
• Instrumenting a subset of the website
• Collecting a subset of tracked events
• Querying a subset during analysis
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24. Bringing Web Analytics In-House –
To SAAS or Not to SAAS?
Organizations may use a SAAS architecture or
keep their web analytics in-house. An in-house
solution creates performance and capacity issues:
• Bringing data storage in-house: must plan for
sufficient in-house storage of collected data.
• Bringing data collection, storage, and processing
in-house: must plan for sufficient servers and
connectivity to support in-house collection and
analysis.
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25. Enhancing Your Performance Methods
“We’re From Web Analytics – We’re Here to Help!”
Seriously, web analytics can provide insights to
enhance performance and capacity planning activities:
• Diagnosing problems
• Alerting for anomalies
• Creating benchmark workloads
• Developing forecasts
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26. Diagnosing Problems
Web analytics data can provide insights not
available from other tools:
• When a performance problem cannot be reproduced in
a testbed
• When performance monitors do not have the
granularity or reach to see into a web application
• When a mix of configuration and user characteristics
causes a performance problem that other tools cannot
isolate
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27. Alerting For Anomalies
Web analytics tools can support proactive performance
management by alerting for situations that could grow
into performance problems.
For example, managing demand when a video goes viral:
• Start by setting up an alert ladder
• When alerted, use web analytics data to take
effective action
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28. Creating Benchmark Workloads
Web analytics data can make simulated workloads a
more accurate representation of operational demand.
Ecommerce system example: one million purchases
per day don’t equal one million visitors per day.
• Web analytics data can reveal conversion funnel
patterns of ecommerce to help you produce a more
realistic visitor pattern.
• Web analytics data can also identify customer
segments so each can be represented with its own
unique characteristics.
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29. Developing Forecasts
Historical perspectives from web analytics data
and tools can help you develop better forecasts
of future system demand.
• Many of the features that make web analytics so
useful for benchmark development also apply to
forecasting.
• Because page tagging undercounts the volume of
activity, use it for revealing trends and identifying
customer segments. Augment that trend analysis
with evaluation of web server log data to estimate
volumes.
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30. Conclusions
Web Analytics -- they’re not just for marketing any more!
• These tools should play an important role in IT
management for any organization with a major web
presence.
• While web analytics tools traditionally support
marketing, they can also be applied much more
widely to manage resources.
• These tools can support the work of performance
analysts and capacity planners, enhancing their work
products and making their projects more successful.
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31. Anna Long
Founder and Principal Analyst
Web AnalyticaSM
anna.m.long@webanalytica.net
linkedin.com/in/annamlong
126 Colchis Court
Cary, NC 27513
919 349-5725
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