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Introductory presentation on web analytics for CMG events
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An Introduction to
Web Analyticsfor Performance Analysts
and Capacity Planners
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and Capacity Planners
Anna LongFounder and Principal AnalystWeb AnalyticaSM
Agenda
• Introducing Web Analytics
• How Marketers Use Web Analytics
• How You Can Use Web Analytics
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1 - 2
• How You Can Use Web Analytics for Performance Management and Capacity Planning
Defining Web Analytics
“Web Analytics is the measurement, collection, analysis, and reporting of Internet data for the purposes of understanding and
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optimizing Web usage.”
-- Web Analytics Association Standards Committee, 2008
Today’sWeb AnalyticsTechnologies
1. Web server logging
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(Microsoft Internet Information Services,
Apache Web Server)
2. Page tagging
(Adobe SiteCatalyst,
Google Analytics)
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
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• 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!
Web Server Logging –A Log Record Example
204.243.130.5 - - [26/Feb/2001:15:34:52 -0600] "GET / HTTP/1.0" 200 8437
IP Address Timestamp
Status and Bytes
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"GET / HTTP/1.0" 200 8437 "http://xyz.com/crawler?category=dimensional+modeling" "Mozilla/4.5 [en] (Win98; I)"
Request
Status and Bytes
Referring Page
Example log record from Sweiger2002
Web Server Logging –Processing Complexities
• One page request generates multiple log records.
• The server writes activity to the log as it transmits
Web server log records are difficult to map accurately to user activity:
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• 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.
Web Server Logging –Making Sense of It All
Several characteristics of web server logging limit its usefulness for analyzing website user activity:
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• 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.
2. Webpage Tagging –How Does It Work?
User clicks a link to
request a webpage
The web analytics
server stores data for
subsequent analysis
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Web server delivers
requested webpage
with imbedded
tagging code
(usually a
JavaScript snippet)
JavaScript tag
execution creates
cookies and sends
logging info to a web
analytics server
Webpage Tagging –A JavaScript Tag Example
<script type="text/javascript">
var _gaq = _gaq || [];_gaq.push(['_setAccount', 'UA-12345-1']);_gaq.push(['_trackPageview']);
Account Number
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(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
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
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• 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!
Webpage Tagging –Making Sense of It All
• Tag execution can cause webpages to
User activity can be difficult to map accurately with web page tagging records:
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• Tag execution can cause webpages to hang.
• Users can disable cookies or JavaScript execution.
• Users can delete cookies.
How Marketers Use Web Analytics
• Developing visitor profiles
Leading marketing organizations have been very successful using web analytics for:
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• Developing visitor profiles
• Managing online marketing campaigns
• Improving conversion
Developing Visitor Profiles
• Segmenting the visitor population
Web analytics enables marketers to tailor offerings to particular visitor needs by:
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• Segmenting the visitor population
• Developing personas
• Analyzing RFM (Recency/Frequency/Monetary
Value)
ManagingOnline Marketing Campaigns
• Web analytics allows marketers to tag not only webpages but also the in-
Web analytics enables marketers to effectively track online campaign performance.
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• 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.
Improving Conversion
• Conversion is the event where the website visitor
becomes a customer.
Web analytics enables marketers to improve conversion.
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• 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.
Sample Conversion Funnel
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Sample Conversion Funnel(Part 1)
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Sample Conversion Funnel(Part 2)
How You Can Apply Web Analyticsfor Performance Management
and Capacity Planning (And Vice Versa)
• Advising On Implementation
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• Advising On Implementation
• Enhancing Your Performance Techniques
Advising on Implementation
• Placing JavaScript snippets
As a performance analyst or capacity planner, you may be asked to consult in areas such as:
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• Placing JavaScript snippets
• Selecting sampling strategies
• Bringing web analytics in-house
Placing JavaScript Snippets –No Optimal Solution
Snippet placement can cause problems:
• Placement anywhere can slow page
rendering if the analytics server is down.
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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.
Selecting Sampling Strategies –
Your Judgment Call
Performance, resource, or budget restrictions drive some organizations to data sampling. Several sampling approaches are:
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• Instrumenting a subset of the website
• Collecting a subset of tracked events
• Querying a subset during analysis
Several sampling approaches are:
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:
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• 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.
solution creates performance and capacity issues:
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:
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• Diagnosing problems
• Alerting for anomalies
• Creating benchmark workloads
• Developing forecasts
Diagnosing Problems
• When a performance problem cannot be reproduced in a testbed
Web analytics data can provide insights not available from other tools:
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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
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:
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• Start by setting up an alert ladder
• When alerted, use web analytics data to take
effective action
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.
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• 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.
Developing Forecasts
• Many of the features that make web analytics so
Historical perspectives from web analytics data and tools can help you develop better forecasts of future system demand.
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• 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.
Conclusions
• These tools should play an important role in IT management for any organization with a major web presence.
Web Analytics -- they’re not just for marketing any more!
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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.
Anna Long
Founder and Principal Analyst
Web AnalyticaSM
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linkedin.com/in/annamlong
126 Colchis Court
Cary, NC 27513
919 349-5725