v52_visualsite metrics dimensions and filters guide

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All rights reserved.

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Published by Omniture

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Visual Site

Metrics, Dimensions, and Filters Guide iii19972008. Omniture, Inc. All Rights Reserved.

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Data Subsetting. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11

Broken Session Filter. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11

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Traffic Profile Metrics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15

Traffic Profile Dimensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18

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Value Profile Metrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .22


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Table of Contents

Visual Site

Metrics, Dimensions, and Filters Guide iv19972008. Omniture, Inc. All Rights Reserved.

Value Profile Dimensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23

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Marketing Profile Dimensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23

Samples of Custom Marketing Profile Dimensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23

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Metrics, Dimensions, and Filters Guide 119972008. Omniture, Inc. All Rights Reserved.

The Visual Site Metrics, Dimensions, and Filters Guide is for users who want to define new metrics, derivativedimensions, or filters and provides a reference for the metrics and dimensions made available in many of thestandard Visual Site profiles. This guide includes the following topics:

Chapter 1,Numerical Answers on page 5

Chapter 2,Built-in Metrics, Dimensions, and Filters on page 9

Chapter 3,Baseline Metrics and Dimensions by Profile on page 13

For information about the hardware, software, and network requirements for all Omniture products, seetheMinimum System Requirements document as well as the Recommended System Requirementsdocument that is specific to your implementation.

For information about installing and administering Visual Server, Visual Load, Visual Transform,Visual Repeater, and Visual Servers Replication Service, see the Server Products Installation andAdministration Guide.

For information about installing, administering, and using other Omniture products, see the appropriateproduct guide.

For information about configuring a dataset, see the Dataset Configuration Guide.

For information about the metrics, dimensions, and filters available with other Omniture applications, seethe Metrics, Dimensions, and Filters Guide that is specific to that application.

This section summarizes the type conventions and symbols used in this guide.

Font Example Used for

Bold Open > File On-screen text, such as menu options,messages, prompts, and parameter and fieldnames

Fixed-width ipconfig Sample code, log fields, or text that you shouldtype

Bold Italic workspace Terminology defined by Omniture to help youunderstand products, features, and capabilities


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Introduction

The following conventions are used to indicate specific types of content included in this guide:

Omniture Technical Support can be reached at 202-595-0066 [email protected] to answer yourquestions regarding software performance or licensing issues. Please be prepared to provide the pertinentinformation about the Omniture application or product about which you are calling. Read the followinginstructions to determine what information to collect before contacting Omniture Technical Support.

Keyboard keys and key combinations

Italic userid Entries, arguments, or values that you must enterand are unique to you or your organization

A caution advises you that failure to take or avoid a specified action could result in loss of data ordegradation of system performance.

A note emphasizes or supplements important points of the main text. A note supplies informationthat may apply only in special cases.

A See Also note refers you to other books, guides, or resources that you can read to learn more abouta product feature or conceptual topic.

A tip helps you apply the techniques and procedures described in the text to your specific needs,suggests alternative methods of performing tasks, or further explains the benefits and uses of theproduct. A tip is not essential to the basic understanding of the product and its features.

(CONTINUED)

Font Example Used for
mailto:[email protected]:[email protected]


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Introduction

Before You Contact Technical Support

Before contacting Technical Support, you should have the following information available:

Computer make and model

Operating system name and version

Omniture software product name, version number, and build number (see To determine the version ofan Omniture software product on this page).

Web server type and version (for Visual Sensor installations only)

When experiencing difficulties or errors in attempting communication with a Visual Server computer, haveyour Visual Workstation log file and the Visual Workstation configuration file available when contactingTechnical Support (see To access the Visual Workstation log and configuration files on this page).

1 In Visual Workstation, on the tab, click the thumbnail toopen the workspace.

2 Within the window, right-click the icon for the Omniture product to display its name,version number, and build number.

Example:

Go to the following default directory paths to open and view the necessary log file and configuration file:

Visual Workstation installation directory\Trace\workstation.log

Visual Workstation installation directory\Workstation.cfg

Other Troubleshooting Information

You can send individual workspaces, visualizations, legends, and text annotations from Visual Workstation toOmniture Technical Support. To copy a window in your Visual Workstation workspace to a word processing ore-mail document to send to Omniture Technical Support, do the following:

1 Right-click the title bar or top border of the workspace, visualization, legend, or text annotation that youwant to capture and select (if capturing a workspace) or .

2 Click or one of the options.

3 Open a word processing or e-mail document and press to paste the screen capture of thewindow.

1 On the desktop of the machine on which Visual Workstation is installed, right-click andthen select .

2 Click the tab, and then select .

3 In the window, click to display the name of your graphics card.


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Introduction

Although we have reviewed, tested, and verified the information in this guide to the best of our abilities, youmay find that features do not behave as described or, simply, that we made a mistake. Please inform us of anyerrors you find, as well as any suggestions you have for improving this guide by writing [email protected].
mailto:[email protected]:[email protected]:[email protected]:[email protected]


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Metrics, dimensions, and filters provide a framework within which calculations are made about the dataprocessed into an Omniture dataset.

The results of the calculations defined using this framework are shown in workspaces, dashboards, reports, orother output of Omniture applications. In short, any number that you see in or from an Omniture application isthe result of a query of a dataset that involves a metric, a dimension, and a filter.

At the most basic level, a metric describes what is being calculated from and about the dataset, a dimensionbreaks down the data in the dataset into categories, and a filter describes a selected portion or subset of thedata in the dataset.

When Visual Server processes data to create an Omniture dataset, dimensions of the data are created andthen updated on an ongoing basis as new data is read and processed by Visual Server. Metrics and filters arecalculated from these dimensions of data.

Imagine an Omniture dataset that contains information about all of the people in the world. This datasetcontains, at a minimum, all of the people in the world and their ages. A useful metric to calculate from thisdataset would be Average Age. Evaluating this metric would result in one number: the average age of theworlds population.

Adding a dimension to the dataset makes this information more useful and manageable. If the dataset alsocontains each persons country of residence, defining a Country dimension would provide a way to segmentthe people into groups for each country in the world. Evaluating the Average Age metric over the Countrydimension would result in a list of numbers, one for each country, each representing the average age of thepeople in that country.


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Numerical Answers

The application of a filter (or selection filter) in a metric formula can give more detailed information or allowthe definition of a new metric based on existing metrics and dimensions. Evaluating the Average Age metricwith a filter of where country equals Sweden results in one number: the average age of people in Sweden. Ametric based on this filter could be Swedish Average Age. For example:

Swedish_Average_Age=Average_Age[country = Sweden]

In general, evaluating a metric over a dimension results in that metric being evaluated for each dimensionelement (or element). In the example above, the Country dimension has an element for each country of theworld. Evaluating Average Age over Country would yield the average age for each of the elements (countries),including the element Sweden.

It is important to note that when you evaluate a metric over a dimension, you will receive the same numericalresult for a specific dimension element regardless of whether you evaluate that metric for the whole dimensionor you define a filter corresponding to that specific dimension element. Using the previous example, whenlooking for the average age of people in Sweden, either of the following methods would yield identical results:

Evaluate the Average Age metric over the Country dimension and then look at the number for thedimension element Sweden.

Evaluate the Average Age metric with a filter of people in Sweden (expressed asAverage_Age[Country='Sweden']).

Filters are syntactical expressions that reference one or more dimensions and dimension elements. As you sawin the above example, using the expression [dimension=element] is an easy way to specify a filter.

It is just as easy to apply such a filter to define a new metric using an expression such asNew_Metric=Metric[Filter]. Such a filter can be used to define a new metric based on a specificdimension element. To use the above example, Average_Age[Country='Sweden'] specifies a metric forthe average age of people in Sweden. If we were to give this metric a name, such as Swedish_Average_Age,we could use it in other calculations as a metric. For example, evaluating Swedish_Average_Age/

Average_Age would result in a single number: the ratio of the average age of people in Sweden to that ofpeople in the rest of the world.

If the dataset with information about all of the people in world also includes a dimension Eye Color, theexpression Swedish_Average_Age[Eye_Color='green'] would result in the average age of Swedeswith green eyes. You might also obtain this same result without using an intermediate metric definition byapplying a different filter: Average_Age[Country='Sweden' AND Eye_Color='green']. In thiscase, the AND operator specifies a filter expression using two other basic filter expressions.

Omniture enables you to create new metrics, filters, and dimensions to expand the information availablethrough an Omniture application or easily customize the definitions in the application to meet your needs. Theopen-ended nature of metrics, dimensions, and filters in Omniture applications enables you to answer morequestions as you add new metrics and dimensions.


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Numerical Answers

Newly defined metrics can be evaluated over existing dimensions, and, similarly, existing metrics can beevaluated over newly defined dimensions. Newly defined metrics also can be used as input in other metrics.Because metrics are built on the client side (that is, their construction does not require dataset processing),they have a minimal impact on system performance. You can increase your analysis capabilities byconstructing many levels of metrics.

For more information about the syntax used to manipulate metrics, dimensions, and filters, see Appendix B of

the Visual Workstation Guide.

Several types of dimensions are available in Visual Server. As such, it is important to know the dimension typewhen using a dimension to create metrics, filters, or derived dimensions.

Visual Server can create and maintain the following types of dimensions:

Countable A dimension type in which the number of elements in the dimension canbe counted by the system. Countable dimensions must be derived fromother Countable dimensions. Countable dimensions can be parents ofother dimensions or children of other countable dimensions.

Examples: Visitor, Session, Page View, Booking, and Order.

Simple A dimension that has a one-to-many relationship with a parent countabledimension. A simple dimension can be thought of as representing aproperty of elements of its parent dimension.

Example: Visitor Referrer is a simple dimension with a parent of the Visitordimension. Each Visitor can have only one Visitor Referrer (their first HTTPreferrer), but many Visitors might have the same Visitor Referrer.Therefore the Visitor Referrer is one-to-many with the Visitor dimension.

Numeric A dimension that has ordered, numerical values and a one-to-manyrelationship with a parent countable dimension. A numeric dimension canbe thought of as representing a numeric property of elements of its parentdimension. Numeric dimensions are often used to define sum metrics.

Example: The numeric dimension Session Revenue defines the revenue, indollars, for each Session. Each Session has a single amount of revenue,but any number of Sessions might have the same revenue, so SessionRevenue is one-to-many with Session. A metric Revenue might bedefined as sum(Session_Revenue, Session), giving the total amountof revenue for the selected Sessions.


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This chapter provides detailed information about the built-in metrics, dimensions, and filters provided inVisual Site.

Almost all metrics in Visual Site are defined in the metrics directory of a profile. A few built-in metrics are

provided to convey technical information about the status of data processing through its two phases called logprocessing and transformation which are defined by Visual Servers log processing and transformationconfiguration files, respectively.

The following table lists the available built-in metrics.

The log processing phase does not mean that all event data comes from log files. Although itsometimes does, event data can come from another source, such as ODBC data sources. For moreinformation about data sources, see the Dataset Configuration Guide.

As Of The As Of time of the dataset in 100 nanoseconds intervals since January1, 1600 00:00 UTC. The As Of timestamp is the latest time in the datasetfor which all data has definitely been processed.

Log Bytes Read The total amount of compressed data (in bytes) that has so far beenprocessed during the log processing phase.


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Built-in Metrics, Dimensions, and Filters

The following dimensions are available in all Omniture datasets:

Log Bytes Total The total amount of compressed data (in bytes) in log files matching theconfigured log sources criteria and start and end date range of thedataset. If log processing is paused in the Log Processing Modeconfiguration file then Log Bytes Total will be the same as Log Bytes Read.

Log ProcessingProgress

The percentage completion of the log processing phase of Visual Serverdata processing.

Total Decoded LogEntries

The number of entries in the log files that were successfully decoded as apart of the log processing phase of Visual Server data processing.

Total Filtered LogEntries

The number of entries in the log files that after being decoded wereaccepted by the robot filter and the log entry conditions and other filtersthat are applied as a part of the log processing phase of Visual Serverdataprocessing.

Total Log Entries The number of entries in the log files that have so far been processed bythe log processing phase of Visual Server data processing.

Total Processed LogEntries

The number of filtered log entries that have been incorporated into theOmniture dataset.

TransformationProgress

The percentage completion of the transformation phase of Visual Serverdata processing.

Uncompressed LogBytes Read

The total amount of uncompressed data (in bytes) that has so far beenprocessed during the log processing phase.

Name Dimension Details Level Description

None Derived N/A Has a single element which relates to allelements of all dimensions. Evaluating ametric over None is like evaluating it over no

dimension. The Filter[None=] isequivalent to [True].

One (Hidden) Numeric/Derived N/A The element 1, which also has ordinalvalue = 1, relates to all elements of alldimensions. The One dimension is normallyused to construct counts by using the syntaxsum(one,Countable_Dimension).


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In addition to the log processing and transformation filters that can be applied before or during the creation ofa dataset, other profile filters are available that impact the scope of the data available for selection from adataset. This section describes only the latter type of special filters.

The following profile filters are available to the user after a dataset has been created: Data Subsetting Filter

Broken Session Filter

A data subset acts as a data filter by allowing you to select only the dimension elements of data that are ofinterest to you.

Creating data subsets decreases the amount of time required to calculate exact answers to your queries. If thedata subset that you specify is small enough, Visual Workstation can retrieve all needed data fromVisual Server and answer questions about the subset quickly and accurately. This is especially useful if youknow that, for example, analyzing a day of data or sessions from a particular referrer will require several hours.

User can create data subsets themselves, or they can access data subsets defined in an inherited or workingprofile. When a user creates a subset of the dataset (by selecting the desired data in Visual Workstation andthen right-clicking in the workspace and clicking ), a Data Subset.filter file is created in theFilters folder within the User profile directory. This filter defines the data subset that the user has selected andsaves the subset for future use.

The Broken Session Filter is a metric formula that can be easily modified to meet any filtering requirements. Inthe default Visual Site profiles, the Broken Session Filter is configured to include all visitors that have aVisitorized Flag that is set to 1. The value 1 indicates the presence of a tracking cookie for that visitor.

Following is the text of the default Broken Session Filter.filter file provided by Omniture in the release packagefor the Visual Site profiles.

entity = derived_filter:formula = string: Visitorized_Flag="1"

model = ref: wdata/model

By default, workspaces have the Broken Session filter applied to both their selection and their benchmarks,and it can be toggled by right-clicking in the workspace and clicking .

The Broken Session Filter can be referenced in filter expressions as Broken_Session_Filter, even if it isnot enabled for the current workspace. For more information about filter expressions, see Appendix B of theVisual Workstation Guide.

Additional filters can be created and applied through their presence in a profiles Filters directory.

Users can create multiple data subsets and can toggle them to view different portions of the data.Remember to turn off Data Subsetting when you want to view all data; otherwise, your metric valueswill not be representative of all data in the dataset.


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To help users of Omniture applications benefit from their capabilities immediately, Omniture has created a setof standard profiles for each Omniture application. One or more of the profiles can be installed at any giventime. These profiles include the definitions of standard metrics, dimensions, filters, reports, workspaces, anddashboards. Omniture continuously updates these profiles and makes them available to its licensees throughits Software Support program. Additionally, users of Omniture applications can define additional profiles and

use them with or instead of the profiles provided by Omniture.Omnitures profile management system allows the overriding of a profiles configurations by higher levelprofiles. This feature should be used by users or administrators who want to override any of the definitionsincorporated in these profiles after they are installed. Installing new releases of these profiles will overwrite anyprior versions. As a result, any changes made to these profiles directly would be overwritten when the newprofiles are installed.

Profiles for vertical markets or specific types of companies or industries also may be available from OmnitureSoftware Support.

Following are descriptions of Omnitures baseline profiles:

includes configuration files that ship with Visual Server. The Base profile should not bemodified by the user or Administrator. Any alterations made in the Base profile are subject to being

overwritten when Omniture releases a next version of Visual Server or other software application.

includes a set of fundamental metrics, dimensions, and filters for web analytics. It alsoincludes template workspaces, reports, and dashboards that facilitate the analysis of, reporting on, andgeneral understanding of overall Internet site activity trends and patterns. This profile functions out-of thebox with a baseline installation of Visual Site.

includes a set of metrics and dimensions and template workspaces, reports, anddashboards associated with the built-in Visual Site business value and conversion model. This profileallows users to identify value events on the site and associate a monetary value to those events.


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Baseline Metrics and Dimensions by Profile

includes set of metrics and dimensions and template workspaces, reports, anddashboards associated with analysis of Internet marketing campaigns, including search analysis andextended referrer analysis.

Omniture also provides the following optional profiles for use with Visual Site:

includes dimensions for the analysis of geographic data collected from a site or

incorporated through the Visual Load

data integration capabilities. The Geography profile also includesgeographical imagery, layer files, and other configuration files related to the presentation and plotting ofgeographical information. The Geography profile requires a Visual Geography software applicationlicense.

includes dimensions and layer files related to the analysis of visitors locationsbased on IP geo-location data provided to Omniture by Quova, Inc., and incorporated into Visual Sitethrough a Visual Geography software application license.

includes dimensions and layer files related to the analysis of visitorslocations based on IP geo-intelligence data provided to Omniture by Digital Envoy, Inc., and incorporatedinto Visual Site through a Visual Geography software application license.

For information about the Geography, IP-Geo-location, and IP Geo-intelligence profiles, contact Omniture.

The following sections of this chapter describe the metrics and dimensions defined in each of the baselineprofiles.


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The Traffic profile contains the following metrics and dimensions for use by Visual Site users.

Metric Metric Formula and Level Description

Entries Formula: Page_Views[noshift(None,Page_View,

Session,-1)]

Level: Page View

The number of sessions that entered the site oneach page. This metric is evaluated over thePage dimension only.

Exit Rate Formula: Exits/Page_Views

Level: Page View

The percentage of sessions that exited the sitefrom each page. The Exit Rate metric can only

be evaluated over the page dimension.

Exits Formula: Page_Views[noshift(None,Page_View,

Session,1)]

Level: Page View

The number of sessions that exited the site fromeach page. This metric is evaluated over thePage dimension only.

LVCI90 Formula: (raw(Visitors) -((raw(Visitors) +

.69)^0.5 * 1.281551 -

1.2269))*(Visitors/

raw(Visitors))

Level: Visitor

A measure of the lowest number of possiblevisitors as reported by Visual Workstation.Mathematically, it specifies the lowest number ofvisitors with a 90% probability.

Page ViewDuration

Formula: sum(exact_page_duration,

page_view)*0.1/

Page_Views[any

Exact_Page_Duration]

Level: Page View

The average length of time (MM:SS) spent on aparticular page or group of pages. This metric isevaluated over the Page dimension only.

Page Viewsper Session

Formula: Page_Views/(Sessions by Page_View)

Level: Session

The average number of page views in eachsession that has page views.

Page Views Formula: sum(One,Page_View)

Level: Page View

The number of page views. A page view is arequest for a defined page (access to imagesand other types of filtered content are notcounted).


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Pct of PageViews

Formula: Page_Views/total(Page_Views)

Level: Page View

The percentage of page views.

Pct of Sessions Formula: Sessions/total(Sessions)

Level: Session

The percentage of sessions.

Pct of Visitors Formula: Visitors/total(Visitors)

Level: Visitor

The percentage of visitors.

Pct Referred

Visitors

Formula:

Referred_Visitors/Visitors

Level: Visitor

The percentage of visitors that were referred to

this site from another site.

ReferredSessions

Formula:Sessions[Referrer

'None' andReferrer'bookmarks']

Level: Session

The number of sessions that were referred to thissite from another site.

ReferredVisitors

Formula:Visitors[Visitor_

Referrer'None' andVisitor_Referrer'book

marks']

Level: Visitor

The number of visitors that were referred to thissite from another site.

Retention Formula:Sessions[shift(None,Ses

sion,Visitor,1) = ""] /

Sessions

Level: Session

The percentage of sessions that are not thevisitors last sessions.

SessionDuration

Formula: (sum(Exact_Page_Duration,

Session)*.1/

Sessions)[Session_

Duration


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Sessions byPage View

Formula: Sessions byPage_View

Level: Session

The number of sessions that had a page view.

Sessions Formula: sum(One,Session)

Level: Session

A count of visitor sessions. A session is a periodof activity for one visitor of a web site. Individualsessions for each visitor are identified usingcookies, timeouts, and other heuristics.

SCI80 Formula:confidence(Sessions) *

1.281551 / Sessions

A measure of confidence of the Sessions metricas reported by Visual Workstation.Mathematically, it is a +/- percentage specifyingthe range within which the actual answer will lie80% of the time. As a rule-of-thumb, doubling

the SCI80 percentage will give a range withinwhich the actual answer will lie 99% of the time.

UVCI90 Formula: (((raw(Visitors)+ .68)^0.5 * 1.281551 +

1.2269) +

raw(Visitors))*(

Visitors/raw(Visitors))

Level: Visitor

A measure of the highest number of possiblevisitors as reported by Visual Workstation.Mathematically, it specifies the highest numberof visitors with a 90% probability.

VCI80 Formula: ((raw(Visitors)+ .68)^0.5 * 1.281551 +

1.2269) / raw(Visitors)

Level: Visitor

A measure of confidence of the Visitors metric asreported by Visual Workstation. Mathematically,

it is a +/- percentage specifying the range withinwhich the actual answer will lie 80% of the time.As a rule-of-thumb, doubling the VCI80percentage will give a range within which theactual answer will lie 99% of the time.

Visitors byPage View

Formula: Visitors byPage_View

Level: Page View

The number of visitors that had a page view.

Visitors bySession

Formula: Visitors bySession

Level: Session

The number of visitors that had a session.

Visitors Formula: sum(One,Visitor)

Level: Visitor

A count of visitors, often based on a persistentcookie. A visitor count tells you how manydifferent unique browsers there are in youraudience if cookies are used. Each visitor canhave multiple sessions with multiple page views.

Metric Metric Formula and Level Description


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The dimensions in the following table are defined in the transformation dataset include files in theTraffic\Dataset\Transformation directory:

NameDimensionDetails

Level Description

Day Simple Session The day of the first log entry of a session.

Day of Week Simple Session The day of week of the first log entry of asession.

Exact PageDuration (Hidden)

Numeric Page View The duration in milliseconds of page view asmeasured by subtracting the time of the nextpage view from the time of that page view.

The exact duration of the last page view in asession is always 0.

Hour Simple Session The hour of the first log entry of a session.

Hour of Day Simple Session The hour of day of the first log entry of asession.

Month Simple Session The month of the first log entry of a session.

Page View Countable Session A log entry or Event Data Record satisfyingthe Page View Condition.

Referrer Simple Session The second level domain of the referrer of the first log entry of the session (or None if itis an internal referrer domain).

Session Countable Visitor A period of related contiguous activity by aVisitor. It is delimited by a 30-minute periodof inactivity and an external referrer domainor a maximum 48-hour Session Duration.Both of those timeouts and the set ofdomains that are considered internal can beconfigured in Transformation.cfg.

URI Simple Page View The URI stem of a page view. The URIdimension can be redefined using theReplaceURI, PrependURI, and AppendURItransformations.


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The dimensions in the following table are defined in the Dimensions directory of the Traffic profile:

Visitor Countable N/A A unique value of x-trackingid. Usually

corresponds to a unique browser if persistentcookies are used. The x-trackingid can beotherwise based on IP number or some otherunique identifier such as x.509 commonname.

Week Simple Session The week of the first log entry of a session.

Dimension Dimension Type and Level Description

Browser Type: Simple

Level: Visitor

The type of user agent used by the visitor,including the version number (for example,MSIE 6.0.)

Browser Type Type: Simple

Level: Visitor

The type of user agent used by the visitor(for example, MSIE).

Search Engine Type: Simple

Level: Session

Operation: FIRST ROW

The first search engine in a visitors sessionwhen a visitor has searched from a namedsearch engine.

Next URI Type: Derived (ShiftDim basedon URI dimension)

Level: Page View

The URI of the next URI after the currentlyselected URI. This derived dimension is usedto conduct analysis about what visitors donext after any given URI.

Onetime vs Repeat Type: Derived (SegmentDimbased on Repeat Visitors andOne-time Visitors metrics)

Level: Visitor

The type of visitor: one-time or repeat.One-time visitors have had only one sessionon the site, while repeat visitors have hadmore than one session.

Page Type: Derived (RenameDimbased on URI dimension)

Level: Page View

The name of each page visited during asession. Initially, each pages name is thesame as the URI but can be changed foreasier interpretation.

NameDimensionDetails

Level Description


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Referrer Type: Inherited from the built-inReferrer dimension

Level: Session

The second level domain name of the website that first referred a session to the site (as

supplied by the visitors browser.)

Search Phrase Type: Simple

Level: Session


The first search phrase in a visitors sessionas passed on by a search engine when avisitor has searched from a named searchengine.

Search Term Type: Many-to-Many

Level: Session

Each search term as passed on by a searchengine when a visitor has a search referrerclickthrough from a named search engine.

Session Duration Type: Derived (MetricDim

based on Exact Page Durationmetric)

Level: Session

The duration of a session in 30-second

increments.

Session Number Type: Simple

Level: Session

The number of times a visitor has visited thesite. For example, first-time visitors have aSession Number of 1, second-time visitorshave a Session Number of 2, etc.

Session PageViews

Type: Derived (MetricDimbased on Page Views metric)

Level: Session

The number of page views in a session.For example, selecting 3 in the SessionPage Views dimension would select all

sessions with exactly 3 page views.

Search Engine Type: Simple

Level: Session

The second level domain name of the firstweb site that is a named search engine thatreferred a visitor to the site during a session(as supplied by the visitors browser.)

Time Dimensions Type: Simple

Level: Session

The hour, day, hour of day, week, day ofweek, month, quarter or year in which aSession began.



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Visual Site expands your site analysis capabilities by providing a Business Value Modelan advanced methodfor measuring and tracking the amount of value generated by your site. Value events and their relative value

are defined through a simple drag and drop interface within Visual Site. Visual Site uses these definitions tocalculate the business value generated by each session, and this information is used in turn to define metricssuch as value, value events, conversion, and so on. These metrics enables you to answer questions such as:

What is the most profitable path through the site?

What referrer or campaign has generated the most value?

What is the average number of purchases on the site per day? (How many value events occur per day onaverage?)

Time ReportingDimensions

Type: Derived (LastN andRename dimensions based on

built-in time dimensions)Level: Session

Dimensions including Days Ago, Days ofLast Month, Days of Last Week, Days of

This Month, Days of This Week, Hours ofToday, Hours of Yesterday, Last 12 Months,Last 2 Months, Last 2 Weeks, Last 24Hours, Last 3 Months, Last 4 Weeks, Last 6Months, Last 7 Days, Last 7 Days andToday, Last 8 Weeks, Last 9 Months, LastMonth, Last Week, Months Ago, ThisMonth, This Week, This and Last 14 Days,This and Last 6 Months, This and Last 8Weeks, Today, Today Reporting, Today andLast 30 Days, Weeks Ago and Yesterdayprovide a convenient way to build aWorkspace or Report which always shows a

portion of data in the Dataset. Each is basedupon when a session began.

URI Type: Inherited from the built-inDimension URI

Level: Page View

The URI of each page viewed.

Visitor Page Views Type: Derived (MetricDimbased on Page Views metric)

Level: Visitor

The number of page views to date for avisitor. For example, selecting 3 in theVisitor Page Views dimension would selectall visitors with exactly 3 page views acrossall of their sessions.

Visitor Referrer Type: Inherited from the built-indimension Referrer

Level: Visitor

The second level domain name of the website that first referred a Visitor to the site fortheir first session (as supplied by the visitorsbrowser).



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After you have defined a Business Value Model in Visual Site, you can use the following configured businessmetrics and dimensions in your analysis.

Metric Dimension Type and Level Description

Conversion Formula: Sessions[notSession_Value=#0]/

Sessions

Level: Session

The percentage of sessions which generatedbusiness value (as defined by the Business ValueModel).

Pct of Value Formula: Value/total(Value)

Level: Session

The percentage of overall value that wasgenerated from the selected set of sessions.

Value Formula:sum(Session_Value,

Session)*0.01

Level: Session

The total business value generated, in dollars (asdefined by the Business Value Model).

Value Events Formula: Sessions[notSession_Value=#0]

Level: Session

The count of sessions that generated businessvalue (as defined by the Business Value Model).

Value Eventsper Visitor

Formula: (Value_Events/Visitors) by Visitor

Level: Visitor

The average number of sessions for each visitorthat generated business value (as defined by the

Business Value Model).

Value perSession

Formula: Value/Sessions

Level: Session

The average business value generated, indollars, by each session (as defined by theBusiness Value Model).

Value perVisitor

Formula: (Value/Visitors)by Visitor

Level: Visitor

The average business value generated, indollars, by each visitor.


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The Campaign dimension is defined in the Visual Site Marketing profile to provide campaign analysiscapabilities.

The Campaign dimension is defined in the Visual Site Marketing profile to provide campaign analysiscapabilities.

Samples of Custom Marketing Profile Dimensions

Visual Site can incorporate additional dimensions of data for further analysis. These dimensions are added byincorporating additional information into the stream of data that is collected for analysis with Visual Site. Forexample, the following table contains some of the custom marketing dimensions that have been added in

deployments of Visual Site for customers in various industries:


Session Value Type: Derived (ModelDimbased on URI)

Level: Session

The value of the session as defined by theBusiness Value Model.

ValueSegment

Type: Derived (MetricDimbased on Value metric)

Level: Visitor

The total value that a visitor has generated in alltheir sessions. The default increment used foreach segment of value is $50, but can bechanged.


Campaign Type: Renamed Simple

Level: Session


The campaign identifier extracted from a valuein the visitors first request.

Dimension (Custom) Description

Email Campaign Date Parses the campaign date (first value) from email campaign querystrings.


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Email Campaign Detail Collects the value string attached to the email campaign querystring variable.

Email Campaign Segment Parses the campaign segment (third value) from email campaignquery strings.

Email Campaign Type Parses the campaign type (second value) from email campaignquery strings.

Marketing Campaign Detail Collects the value string attached to marketing campaign querystring variables.

Marketing Campaign Owner Parses the campaign owner (fourth value) from marketingcampaign query strings.

Marketing Campaign Source Parses the campaign source (first value) from marketingcampaign query strings.

Marketing Campaign Type Parses the campaign type (second value) from marketingcampaign query strings.

PPC Campaign Detail Collects the value string attached to the ppc query string variable.

Dimension (Custom) Description


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Apache Xerces: This product includes software developed by the Apache Software Foundation

(http://www.apache.org/). Copyright (c) 2002 The Apache Software Foundation, all rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted

provided that the following conditions are met: 1. Redistributions of source code must retain the

above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in

binary form must reproduce the above copyright notice, this list of conditions and the following

disclaimer in the documentation and/or other materials provided with the distribution. 3. The end-

user documentation included with the redistribution, if any, must include the following

acknowledgment: This product includes software developed by the Apache Software Foundation

(http://www.apache.org/). Alternately, this acknowledgment may appear in the software itself, if

and wherever such third-party acknowledgments normally appear. 4. The names Xerces and

Apache Software Foundation must not be used to endorse or promote products derived from this

software without prior written permission. For written permission, please contact apache

@apache.org. 5. Products derived from this software may not be called Apache, nor may Apache

appear in their name, without prior written permission of the Apache Software Foundation. THIS

SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED WARRANTIES,

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LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND

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(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF

THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

OpenSSL Toolkit: This product includes software developed by the OpenSSL Project for use in the

OpenSSL Toolkit (http://www.openssl.org/) . Copyright (c) 1998-2002 The OpenSSL Project. All

rights reserved. Redistribution and use in source and binary forms, with or without modification,

are permitted provided that the following conditions are met: 1. Redistributions of source code must

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Redistributions in binary form must reproduce the above copyright notice, this list of conditions and

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3. All advertising materials mentioning features or use of this software must display the following

acknowledgment: This product includes software developed by the OpenSSL Project for use in the

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Project must not be used to endorse or promote products derived from this software without prior

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OpenSSL Project for use in the OpenSSL Toolkit (http://www.openssl.org /). THIS SOFTWARE IS

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Third-Party Licenses




This product includes cryptographic software written by Eric Young ([email protected]). Copyright

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distribut ion, be it the RC4, RSA, lhash, DES, etc., code; not just the SSL code. The SSL

documentation included with this distribution is covered by the same copyright terms except that

the holder is Tim Hudson ([email protected] om). Copyright remains Eric Young's, and as such any

Copyright notices in the code are not to be removed. If this package is used in a product, Eric Young

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a textual message at program startup or in documentation (online or textual) provided with the

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binary form must reproduce the above copyright notice, this list of conditions and the following

disclaimer in the documentation and/or other materials provided with the distribut ion. 3. All

advertising materials mentioning features or use of this software must display the following

acknowledgement: This product includes cryptographic software written by Eric Young([email protected]) The word 'cryptographic' can be left out if the routines from the library being

used are not cryptographic related. 4. This product includes software written by Tim Hudson

([email protected]). THIS SOFTWARE IS PROVIDED BY ERIC YOUNG ``AS IS'' AND ANY

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DISCLAIMED. IN NO EVENT SHALL THE AUTHOR OR CONTRIBUTORS BE LIABLE FOR ANY

DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES






Liblzf: This software uses, in a modified form, the LZF compression library. Copyright (c) 2000Marc Alexander Lehmann [email protected]. Redistribution and use in source and binary forms, with or

without modification, are permitted provided that the following conditions are met: 1.

Redistributions of source code must retain the above copyright notice, this list of conditions and the

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ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE

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PCRE: Copyright (c) 1997-2001 University of Cambridge. Permission is granted to anyone to use

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misrepresented, either by explicit claim or by omission. In practice, this means that if you use PCRE

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Truerand: Truerand is based on code by D. P. Mitchell. Truerand was modified by Matt Blaze 7/95,

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respect to this software, its quality, accuracy, merchantability, or fitness for a particular purpose.This software is provided AS IS, and you, its user, assume the entire risk as to its quality and

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Permission to use, copy, modify, distribute, and sell this software and its documentation for any

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Bzip: This program, bzip2 and associated library libbzip2, are copyright (C) 1996-2002 Julian R

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disclaimer. 2. The origin of this software must not be misrepresented; you must not claim that you

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THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Julian Seward,

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and located in the People's Republic of China ("Licensor") grants the following rights and licenses to

Omniture, Inc. f/k/a Omniture, Inc. ("Omniture"): Licensor, as the sole owner of the rights and title

to the source code of "HTML Snapshot," hereby grants Omniture a perpetual royalty-free, non-exclusive license to use the source code and object code of Licensor's "HTML Snapshot" software

product. Licensor grants Omniture the right to use the licensed source code of "HTML Snapshot":

(1) to create derivative works thereof and therefrom and to modify it as needed; (2) in combination

with Omniture' other proprietary source code; and (3) to redistribute, sub-license or otherwise make

available to, or permit the use of, such licensed source code and object code to those third parties

which license Omniture proprietary software applications. Licensor grants no other rights in the

source code of "HTML Snapshot" except the rights expressly granted hereunder. Licensor retains all

rights, title and ownership of the source code of "HTML Snapshot." Licensor authorizes Omniture to

deposit the source code of "HTML Snapshot" with an independent third party software escrow agent

along with the source code of its own proprietary software applications upon the request of

Omniture' customers who have licensed its proprietary software applications . Notwithstanding the

foregoing, in the event the source code of "HTML Snapshot" by such independent third party escrow

agent is released to a licensee of Omniture, such third party customer shall be contractually

restricted from using the source code of "HTML Snapshot" for the purposes of creating anyderivative works therefrom or from distributing such source code to any third parties. Licensor

prohibits Omniture from using the licensed source code of "HTML Snapshot" to release a product

that is competitive with "HTML Snapshot." Licensor is providing the source code license of "HTML

Snapshot" "AS IS." LICENSOR EXPRESSLY DISCLAIMS ANY WARRANTY, WHETHER EXPRESS

OR IMPLIED. OMNITURE USE OF THE SOURCE CODE LICENSE OF "HTML SNAPSHOT"

SHALL BE AT ITS OWN RISK. LICENSOR AND ITS EMPLOYEES, AGENTS AND

REPRESENTATIVES EXPRESSLY DISCLAIM ANY LIABILITY FOR LOSS OF DATA, DAMAGES,

LOSS OF PROFITS OR ANY OTHER KIND OF LOSS ARISING FROM OR RELATING TO

OMNITURE USE OF THE SOURCE CODE LICENSE OF "HTML SNAPSHOT."

MD5: Copyright (C) 1999, 2000, 2002 Aladdin Enterprises. All rights reserved. This software is

provided 'as-is', without any express or implied warranty. In no event will the authors be held liable

for any damages arising from the use of this software. Permission is granted to anyone to use this

software for any purpose, including commercial applications, and to alter it and redistribute itfreely, subject to the following restrictions: 1. The origin of this software must not be

misrepresented; you must not claim that you wrote the original software. If you use this software in

a product, an acknowledgment in the product documentation would be appreciated but is not

required. 2. Altered source versions must be plainly marked as such, and must not be

misrepresented as being the original software. 3. This notice may not be removed or altered from

any source distribution.

StdString: COPYRIGHT: 1999 Joseph M. O'Leary. This code is free. Use it anywhere you want.

Rewrite it, restructure it, whatever. Please don't blame me if it makes your $30 billion dollar

satellite explode in orbit. If you redistribute it in any form, I'd appreciate it if you would leave this

notice here.

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