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An Introduction to

Web Analytics

for Performance Analysts and Capacity Planners

Anna LongFounder and Principal AnalystWeb AnalyticaSM

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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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Defining Web Analytics

“Web Analytics is the measurement, collection, analysis, and reporting of Internet data for the purposes of understanding and optimizing Web usage.”

-- Digital Analytics Association Standards Committee, 2008

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Today’sWeb AnalyticsTechnologies

1. Web server logging (Microsoft Internet Information Services, Apache Web Server)

2. Page tagging (Adobe SiteCatalyst, Google Analytics)

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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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Web Server Logging – A Log Record Example

204.243.130.5 - - [26/Feb/2001:15:34:52 -0600] "GET / HTTP/1.0" 200 8437 "http://xyz.com/crawler?category=dimensional+modeling" "Mozilla/4.5 [en] (Win98; I)"

IP Address

Timestamp

Request

Status and Bytes

Referring Page

Example log record from Sweiger2002

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Web Server Logging – Processing Complexities

• 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.

Web server log records are difficult to map accurately to user activity:

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Web Server Logging –Making Sense of It All

• 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.

Several characteristics of web server logging limit its usefulness for analyzing website user activity:

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2. Webpage Tagging –How Does It Work?

User clicks a link to request a webpage

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

The web analytics server stores data for subsequent analysis

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Webpage Tagging –A JavaScript Tag Example

<script type="text/javascript">

  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>

Account Number

Example JavaScript Tag from Google2010e

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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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Webpage Tagging – Making Sense of It All

• Tag execution can cause webpages to hang.

• Users can disable cookies or JavaScript execution.

• Users can delete cookies.

User activity can be difficult to map accurately with web page tagging records:

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How Marketers Use Web Analytics

• Developing visitor profiles• Managing online marketing campaigns• Improving conversion

Leading marketing organizations have been very successful using web analytics for:

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Developing Visitor Profiles

• Segmenting the visitor population• Developing personas• Analyzing RFM (Recency/Frequency/Monetary

Value)

Web analytics enables marketers to tailor offerings to particular visitor needs by:

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ManagingOnline Marketing Campaigns

• 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.

Web analytics enables marketers to effectively track online campaign performance.

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Improving 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.

Web analytics enables marketers to improve conversion.

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Sample Conversion Funnel

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Sample Conversion Funnel(Part 1)

Sample Conversion Funnel(Part 2)

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How You Can Apply Web Analyticsfor Performance Management

and Capacity Planning (And Vice Versa)

• Advising On Implementation

• Enhancing Your Performance Techniques

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Advising on Implementation

• Placing JavaScript snippets• Selecting sampling strategies• Bringing web analytics in-house

As a performance analyst or capacity planner, you may be asked to consult in areas such as:

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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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Selecting Sampling Strategies – Your Judgment Call

• Instrumenting a subset of the website• Collecting a subset of tracked events• Querying a subset during analysis

Performance, resource, or budget restrictions drive some organizations to data sampling. Several sampling approaches are:

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Bringing Web Analytics In-House –To SAAS or Not to SAAS?

• 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.

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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Enhancing Your Performance Methods

• Diagnosing problems• Alerting for anomalies• Creating benchmark workloads• Developing forecasts

“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

• 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

Web analytics data can provide insights not available from other tools:

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Alerting For Anomalies

• Start by setting up an alert ladder• When alerted, use web analytics data to take

effective action

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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Creating Benchmark Workloads

• 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.

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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Developing Forecasts

• 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.

Historical perspectives from web analytics data and tools can help you develop better forecasts of future system demand.

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Conclusions

• 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.

Web Analytics -- they’re not just for marketing any more!

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Anna LongFounder and Principal Analyst

Web AnalyticaSM

anna.m.long@webanalytica.net

linkedin.com/in/annamlong

126 Colchis Court Cary, NC 27513

919 349-5725