Technology Exploitation

and the Bottom Line

An Introduction to Web Analytics for Performance Analysts and Capacity Planners

Anna Long Web AnalyticaSM

1 - 2

Agenda

Web Analytics Definition Current Web Analytics Technologies Web Analytics Applied to Marketing Applying Web Analytics to Performance

Management and Capacity Planning

Defining Web Analytics

The Web Analytics Association (WAA) Definition:

Web Analytics is the measurement, collection, analysis and reporting of Internet data for the purposes of understanding and optimizing Web usage. [“Web Analytics Definitions” – WAA Standards Committee, 2008]

Current Web Analytics Technologies

Major technologies in use today: Web server logging ( such as Microsoft IIS logging, Apache

Access logging) Page tagging (such as Adobe SiteCatalyst, Google Analytics)

Other technologies in use: Network Appliances (such as Pion Systems by Atomic Labs) Tag Management Systems (such as Ensighten Manage)

Web Server Logging – How Does it Work?

Web Servers such as Apache or Microsoft IIS record activity as requests are made and served.

Web servers provide general-purpose logging at a very detailed level.

Data must be cleaned and organized to make it usable for web analytics.

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

Web Server Logging – Processing Complexities

One page request generates multiple log records Log records may be ordered by completion time, not

initiation time Records for different page requests can be interleaved in log Request for page components may be completed by multiple

servers Web 2.0 technologies such as AJAX (Asynchronous

JavaScript and XML) add further complexity

User activity can be difficult to map accurately with web server log records:

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.

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

Web Page Tagging –How Does It Work?

User clicks on a link on a search engine results webpage

Web server delivers requested webpage with tagging code (usually a JavaScript snippet)

JavaScript tag execution creates cookies and sends logging info to a web analytics server

Logged data is stored in a web analytics server and retrieved for dashboards and reporting queries

Web Page 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

Web Page Tagging –Implementation Complexities

Several characteristics of web page tagging complicate its successful application for analyzing website user activity: Complex architectures (such across multiple

subdomains or third-party ecommerce subsystems) can be difficult to tag for accurate data collection

Proper maintenance of high-volume tagging for a major online property can be overwhelming (especially when considering tagging of webpages and in-bound links)

Web Page Tagging – Making Sense of It All

Tag execution can cause webpages to hang (using asynchronous snippets in place of synchronous snippets can help)

Users can disable JavaScript execution (their visits will be invisible to tag monitoring)

Users can delete cookies (their visits will be incorrectly categorized)

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

How Web Analytics is Used in Marketing

developing customer profiles managing online marketing campaigns improving conversion

Even though web analytics technologies have drawbacks, they still provide useful results. For example, marketing groups have been very successful using analytics for these activities:

Customer Profiling

Segmentation of the customer population Persona development RFM (Recency/Frequency/Monetary Value) Analysis

Web analytics can support the activities of customer profiling, which enable marketing to tailor offerings to particular customer needs.

Measuring Response for Online Marketing Campaigns

Each in-bound “call to action” link can be uniquely tagged. Search engine advertising programs such as Google

AdWords add extensive in-bound link tagging to identify the characteristics of the visit and visitor

Analytics software collects this data, which the web analyst process and analyzes with the following aims:

Identify which campaigns are most and least successful Determine which aspects of successful campaigns to replicate Determine whether to revise less successful campaigns or pull the

plug

Online marketing makes extensive use of web analytics.

Improving Conversion

Conversion is the event where a website visitor becomes a customer.

The process through which conversion takes place is called a “conversion funnel”.

The conversion process is viewed as a leaky funnel, meaning some people abandon the process, i.e., they “leak out” at each step along the way.

Marketers attempt to improve conversion by reducing the leakage.

Improving conversion is a major goal of online marketing.

Sample Conversion Funnel(Part 1)

Sample Conversion Funnel(Part 2)

Conversion FunnelAnother View

Graphic courtesy of WAA colleague Bob Russotti

Web Analytics andPerformance Management /

Capacity Planning

Managing the impact of web analytics on performance and capacity requirements

Applying web analytics to enrich performance and capacity planning activities

As a performance analyst or capacity planner, your involvement with web analytics can fall into two categories:

Web Analytics –How It Can Impact Performance

Placement of JavaScript snippets Planning for in-house analytics data

collection/storage Selecting sampling strategies

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

Placing JavaScript Snippets – No Single Optimal Solution

Snippet placement can cause problems no matter where in the page code it is placed:

Placement anywhere on a webpage can slow rendering if the analytics server is down.

Placement at the bottom of webpage code can cause data to be lost when visitor leaves a page before the snippet executes.

Placement at the top of webpage code can cause passing of custom variables to fail.

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

Plan for storage if bringing collected data in-house (Google recommendation: minimum of 10 GB for each million pageviews (but plan for much more))

Architect/plan for servers and connectivity if bringing collection servers in-house

Most major web analytics tools offer a SAAS version, but some organizations choose to keep their web analytics data or the entire collection process in-house. With in-house, there are performance/capacity challenges to address:

Sampling All That Data – Your Judgment Call

Instrumenting a subset of the website (not recommended)

Collecting a subset of tracked events Querying a subset during analysis (if must sample

this approach is most desireable)

To stay within performance, resource, or budget restrictions, some organizations resort to data sampling. Several sampling approaches are commonly applied:

We’re From Web Analytics – We’re Here to Help!

Diagnosing problems Alerting for anomalies Developing benchmark workloads Developing forecasts

While web analytics can add complexity to performance and capacity management processes, it can also provide insights to enhance performance and capacity planning activities:

Diagnosing Performance 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 performance problem is caused by a particular mix of configuration/user characteristics not readily isolated by other tools

When traditional performance monitoring/testing tools fall short in tackling web-based problems, web analytics data can provide insights not available from other tools. For instance:

Alerting For Anomalies

Start by setting up an alert “ladder” in your web analytics tool

If receiving alerts, you can dig into the web analytics data to learn characteristics of the activity spike: Peak referrers Peak geographic regions Time zone rolling

Web analytics tools can be configured to support proactive performance management by alerting for situations that could build into performance problems.

For example, managing demand when a video goes viral:

Developing Benchmark Workloads

Ecommerce system example: one million purchases per day does not equate to 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.

Web analytics data can provide key insights to make simulated workloads a more accurate representation of operational demand.

Developing Forecasts

Many of the features that make web analytics so useful for benchmark development also apply for forecasting.

Caution: need to remember that data from page tagging undercounts the volume of activity. Use it for revealing trends and identifying customer segments. Augment that trend analysis with analysis of web server log data to estimate volumes.

The historical perspective gained from web analytics data and tools can help you develop better forecasts of future system demand.

Conclusions

Web analytics tools play an important role in the information technology architecture of virtually 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.

Web analytics 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!