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Metrics, Dimensions, and Filters



Contents

About Metrics, Dimensions, and Filters..........................................................................3

Expanding Metrics, Dimensions, and Filters............................................................................................................4

Dimension Types..............................................................................................................5

About Built-in Metrics, Dimensions, and Filters............................................................7

Built-in Metrics....................................................................................................................................................................7

Built-in Dimensions...........................................................................................................................................................7

Built-in Profile Filters.........................................................................................................................................................8

Baseline Profiles.............................................................................................................10

Traffic Profile Metrics................................... ................... .................... .................... ................... .................... .................11

Traffic Profile Dimensions................... .................... .................... ................... .................... ................... .................... ....13

Value Profile Metrics.......................................................................................................................................................16

Value Profile Dimensions..............................................................................................................................................16

Marketing Profile Dimensions....................................................................................................................................17

Third-Party Licenses.......................................................................................................18

Metrics, Dimensions, and FiltersLast updated 12/19/2013



About Metrics, Dimensions, and FiltersMetrics, dimensions, and filters provide a framework within which calculations are made about the data processed into a dataworkbench dataset.

The results of the calculations defined using this framework are shown in workspaces, dashboards, reports, or other outputs.

In short, any number that you see in or from an application is the 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 dimension breaks down the

data in the dataset into categories, and a filter describes a selected portion or subset of the data in the dataset.

When the Data Workbench Server processes data to create a dataset, dimensions of the data are created and then updated on

an ongoing basis as new data is read and processed by the server. Metrics and filters are calculated from these dimensions of

data.

Caution: If you redefine an internal metric, the system will behave unexpectedly because of the wrong value. Your reports

will not generate unless a metric reads 100%. It is recommended that you do not change metric definitions.

An Example

Imagine a dataset that contains information about all of the people in the world. This dataset contains, at a minimum, all of the

people in the world and their ages. A useful metric to calculate from this dataset would be Average Age. Evaluating this metric

would result in one number: the average age of the world’s population.

Adding a dimension to the dataset makes this information more useful and manageable. If the dataset also contains each person’s

country of residence, defining a Country dimension would provide a way to segment the people into groups for each country

in the world. Evaluating the Average Age metric over the Country dimension would result in a list of numbers, one for each

country, each representing the average age of the people in that country.

The application of a filter (or selection filter) in a metric formula can give more detailed information or allow the definition of

a new metric based on existing metrics and dimensions. Evaluating the Average Age metric with a filter of “where country equals

Sweden” results in one number: the average age of people in Sweden. A metric based on this filter could be Swedish Average

Age.

For example:

Swedish_Average_Age=Average_Age[country = ‘Sweden’]

How Metrics, Dimensions, and Filters Relate

In general, evaluating a metric over a dimension results in that metric being evaluated for each dimension element (or element).

In the example above, the Country dimension has an element for each country of the world. 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 numerical result for a specific

dimension element regardless of whether you evaluate that metric for the whole dimension or you define a filter corresponding

to that specific dimension element. Using the previous example, when looking 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 the dimension 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 saw in the above

example, using the expression [dimension=element] is an easy way to specify a filter.

3About Metrics, Dimensions, and Filters



It is just as easy to apply such a filter to define a new metric using an expression such as New_Metric=Metric[Filter] .

Such a filter can be used to define a new metric based on a specific dimension element. To use the above example,

Average_Age[Country='Sweden'] specifies a metric for the 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 of people in the rest of the world.

If the dataset with information about all of the people in world also includes a dimension Eye Color, the expressionSwedish_Average_Age[Eye_Color='green'] would result in the average age of Swedes with green eyes. You might

also obtain this same result without using an intermediate metric definition by applying a different filter:

Average_Age[Country='Sweden' AND Eye_Color='green']. In this case, the AND operator specifies a filter

expression using two other basic filter expressions.

Expanding Metrics, Dimensions, and Filters

Data workbench enables you to create new metrics, filters, and dimensions to expand the information available through anapplication or to easily customize the definitions in the application to meet your needs. The open-ended nature of metrics,dimensions, and filters enables you to answer more questions as you add new metrics and dimensions.

Newly defined metrics can be evaluated over existing dimensions, and, similarly, existing metrics can be evaluated 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 by constructing many levels of metrics.

For more information about the syntax used to manipulate metrics, dimensions, and filters, see language syntax .

4About Metrics, Dimensions, and Filters

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Dimension TypesSeveral types of dimensions are available in the data workbench server. As such, it is important to know the dimension typewhen using a dimension to create metrics, filters, or derived dimensions.

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

DescriptionDimension Types

A dimension type in which the number of elements in the dimension can be counted by the

system. Countable dimensions must be derived from other Countable dimensions. Countable

dimensions can be parents of other dimensions or children of other countable dimensions.

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

Countable

A dimension that has a one-to-many relationship with a parent countable dimension. A simple

dimension can be thought of as representing a property of elements of its parent dimension.

Example: Visitor Referrer is a simple dimension with a parent of the Visitor dimension. Each

Visitor can have only one Visitor Referrer (their first HTTP referrer), but many Visitors might

Simple

have the same Visitor Referrer. Therefore the Visitor Referrer is “one-to-many ” with the Visitor

dimension.

A dimension that has ordered, numerical values and a one-to-many relationship with a parent

countable dimension. A numeric dimension can be thought of as representing a numeric property

of elements of its parent dimension. Numeric dimensions are often used to define “sum” metrics.

Example: The numeric dimension Session Revenue defines the revenue, in dollars, for each

Session. Each Session has a single amount of revenue, but any number of Sessions might have

Numeric

the same revenue, so Session Revenue is “one-to-many ” with Session. A metric “Revenue” might

be defined as sum(Session_Revenue, Session), giving the total amount of revenue for

the selected Sessions.

A dimension that has a many-to-many relationship with a parent countable dimension. A

many-to-many dimension can be thought of as representing a “set” of values for each element

Many-to-Many

of its parent dimension. A many-to-many dimension is equivalent to an (anonymous) countable

dimension with its parent and a Simple dimension with a parent of the anonymous countable

dimension.

Example: The many-to-many dimension Search Phrase has a parent of Session. Each Session can

use zero or more Search Phrases, and a Search Phrase can be used in any number of Sessions.

A dimension that has a one-to-one relationship with a parent Countable dimension. The element

names of the denormal dimension can carry information about the corresponding elements of

Denormal

the parent dimension. A denormal dimension can be thought of as storing an arbitrary string

value for each element of the parent. Denormal dimensions can be used with Insight Server’s

segment export capability to output details about a subset or “segment” of a countable dimension.

In addition, denormal dimensions can be referenced in metric formulas and worksheet

visualizations and can be used (with certain restrictions) to define filters.

Example: The denormal dimension EMail Address has a parent of Visitor. Each Visitor has an

EMail Address, and each element of the EMail Address dimension is associated with a single

5Dimension Types



DescriptionDimension Types

Visitor. Even if two visitors have the same e-mail address, their addresses will be different elements

of the EMail Address dimension. A Segment Export can reference the EMail Address dimension

to output the EMail Address of each visitor in a Segment.

A dimension that enables you to create a set of periodic or absolute local time dimensions (such

as Day, Day of Week, Hour, Hour of Day, and so on) based on a timestamp field that you specify.

Time

When defining time dimensions, you also can choose a day other than Monday to be used as the

start of a week by specifying the Week Start Day parameter.

Example: The time dimension Session Time has parent of Session. Therefore, the dimension

defines a set of time dimensions (Day, Day of Week, Hour, Hour of Day, Month, and Week)

whose elements correspond to the times at which visitors’ sessions on the site began.

Derived dimensions, rather than being defined in the dataset configuration based on the data

being processed, are defined in the profile based on other dimensions or metrics. Many derived

dimensions are created automatically to drive different types of visualizations.

Example, when a user builds a site or process map, Insight Server silently creates a “Prefix”

dimension. Others, such as the reporting time dimensions, are defined by files in the Dimensions

directory of a profile.

Derived

6Dimension Types



About Built-in Metrics, Dimensions, and FiltersThis section provides detailed information about the built-in metrics, dimensions, and filters provided in data workbench.

Almost all metrics 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 log processing and transformation which are

defined by Insight Server’s log processing and transformation configuration files, respectively.

Note: The log processing phase does not mean that all event data comes from “ log files.” Although it sometimes does, event

data can come from another source, such as an ODBC data source. For more information about data sources, see the Dataset

Configuration Guide.

Built-in Metrics

Data workbench includes built-in metrics.

The following table lists the available built-in metrics for data workbench:

DescriptionBuilt-in Metric

The As Of time of the dataset in 100 nanoseconds intervals since January 1, 1600 00:00UTC. The As Of timestamp is the latest time in the dataset for which all data has definitely been processed.

As Of

The total amount of compressed data (in bytes) that has so far been processed during thelog processing phase.

Log Bytes Read

The total amount of compressed data (in bytes) in log files matching the configured logsources criteria and start and end date range of the dataset. If log processing is paused in

Log Bytes Total

the Log Processing Mode configuration file then Log Bytes Total will be the same as LogBytes Read.

The percentage completion of the log processing phase of Insight Server data processing.Log Processing Progress

The number of entries in the log files that were successfully decoded as a part of the logprocessing phase of Insight Server data processing.

Total Decoded Log Entries

The number of entries in the log files that after being decoded were accepted by the robotfilter and the log entry conditions and other filters that are applied as a part of the logprocessing phase of Insight Server data processing.

Total Filtered Log Entries

The number of entries in the log files that have so far been processed by the log processingphase of Insight Server data processing.

Total Log Entries

The number of filtered log entries that have been incorporated into the Adobe dataset.Total Processed Log Entries

The percentage completion of the transformation phase of Insight Server data processing.Transformation Progress

The total amount of uncompressed data (in bytes) that has so far been processed duringthe log processing phase.

Uncompressed Log Bytes Read

Built-in Dimensions

Data workbench includes built-in dimensions.

The following table lists the available built-in dimensions for data workbench:

7About Built-in Metrics, Dimensions, and Filters

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DescriptionLevelDetailsName

Has a single element “” which relates to all elements of all dimensions.Evaluating a metric over None is like evaluating it over no dimension.

The Filter [None=“”] is equivalent to [True].

N/ADerivedNone

The element “1”, which also has ordinal value = 1, relates to all elements

of all dimensions. The One dimension is normally used to constructcounts by using this syntax:

sum(one,Countable_Dimension)

N/ANumericOne (Hidden)

Built-in Profile Filters

Profile filters constrain the scope of the data available from a dataset.

In addition to the log processing and transformation filters that can be applied before or during the creation of a dataset, other

profile filters are available that impact the scope of the data available for selection from a dataset. 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

Note: Additional filters can be created and applied through their presence in a profile’ s Filters directory.

Data Subsetting

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

Creating data subsets decreases the amount of time required to calculate exact answers to your queries. If the data subset that

you specify is small enough, Insight® can retrieve all needed data from Insight Server and answer questions about the subset

quickly and accurately. This is especially useful if you know that, for example, analyzing a day of data or sessions from a particular

referrer will require several hours.

Users can create data subsets themselves, or they can access data subsets defined in an inherited or working profile. When a

user creates a subset of the dataset (by selecting the desired data in Insight and then right-clicking in the workspace and clicking

Data > Subset), a Data Subset.filter file is created in the Filters folder within the User profile directory. This filter defines the

data subset that you have selected and saves the subset for future use.

Note: You can create multiple data subsets and can toggle them to view different portions of the data. Remember to turnoff Data Subsetting when you want to view all data. Otherwise, your metric values will not be representative of all data inthe dataset.

Broken Session Filter

The Broken Session Filter is a metric formula that can be easily modified to meet any filtering requirements. In the default Site

profiles, the Broken Session Filter is configured to include all visitors that have a “Visitorized 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 Adobe in the release package for the 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 Data > Broken Session Filter.

The Broken Session Filter can be referenced in filter expressions as Broken_Session_Filter, even if it is not enabled for the currentworkspace. See filter expressions for additional information.


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Baseline ProfilesA set of standard profiles for each application has been created to allow for one or more of the profiles to be installed at any given time.

These baseline profiles include the definitions of standard metrics, dimensions, filters, reports, workspaces, and dashboards.

Adobe continuously updates these profiles and makes them available to its licensees through its Software Support program.

Additionally, users of Adobe applications can define additional profiles and use them with or instead of the profiles providedby Adobe.

The profile management system allows the overriding of a profile’s configurations by higher level profiles. This feature should

be used by users or administrators who want to override any of the definitions incorporated in these profiles after they are

installed. Installing new releases of these profiles will overwrite any prior versions. As a result, any changes made to these profiles

directly would be overwritten when the new profiles are installed.

Profiles for vertical markets or specific types of companies or industries also may be available from Adobe ClientCare. The

following are descriptions of the baseline profiles:

• The Base profile includes configuration files that ship with Insight Server. The Base profile should not be modified by the useror Administrator. Any alterations made in the Base profile are subject to being overwritten when Adobe releases a next version

of Insight Server or other software application.• The Traffic profile includes a set of fundamental metrics, dimensions, and filters for web analytics. It also includes template

workspaces, reports, and dashboards that facilitate the analysis of, reporting on, and general understanding of overall Internetsite activity trends and patterns. This profile functions “out-of the box” with a baseline installation of Site.

• The Value profile includes a set of metrics and dimensions and template workspaces, reports, and dashboards associated withthe built-in Site business value and conversion model. This profile allows users to identify value events on the site and associatea monetary value to those events.

This profile expands your site analysis capabilities by providing a Business Value Model, an advanced method for 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 Site. Site uses these definitions to calculate the business value generated by each session, and

this information is used in turn to define metrics such 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 on average?)

After you have defined a Business Value Model in Site, you can use the Value metrics and dimensions in your analysis.

• The Marketing profile includes set of metrics and dimensions and template workspaces, reports, and dashboards associatedwith analysis of Internet marketing campaigns, including search analysis and extended referrer analysis.

Adobe also provides the following optional profiles to use:

• The IP Geo-location profile includes dimensions and layer files related to the analysis of visitors’ locations based on IPgeo-location data provided to Adobe by Quova, Inc., and incorporated into data workbench.

• The IP Geo-intelligence profile includes dimensions and layer files related to the analysis of visitor’s locations based on IPgeo-intelligence data provided to Adobe by Digital Envoy, Inc., and incorporated into data workbench.

For information about the IP-Geo-location and IP Geo-intelligence profiles, contact your Adobe support personnel. The following

sections describe the metrics and dimensions defined in each of the baseline profiles.

10Baseline Profiles



Traffic Profile Metrics

The Traffic profile contains the following metrics to identify visitor traffic.

DescriptionMetric Formula and LevelMetric

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

dimension only.

Formula: Page_Views[noshift(None,Page_View,

Session,-1)]

Level: Page View

Entries

The percentage of sessions that exited the site

from each page. The Exit Rate metric can only

be evaluated over the page dimension.

Formula: Exits/Page_Views

Level: Page View

Exit Rate

The number of sessions that exited the site from

each page. This metric is evaluated over the Page

dimension only.

Formula: Page_Views[no

shift(None,Page_View,

Session,1)]

Level: Page View

Exits

A measure of the lowest number of possible

visitors as reported by Insight. Mathematically,

Formula: (raw(Visitors) -

((raw(Visitors) + .69)^0.5 *

LVCI90

it specifies the lowest number of visitors with a

90% probability.

1.281551 -

1.2269))*(Visitors/raw(Visitors))

Level: Visitor

The average length of time (MM:SS) spent on

a particular page or group of pages. This metric

is evaluated over the Page dimension only.

Formula:sum (exact_page_duration,

page_view)*0.1/Page_Views[any

Exact_Page_Duration]

Page View Duration

Level: Page View

The average number of page views in each

session that has page views.Formula: Page_Views/ (Sessions by

Page_View)

Page Views per Session

Level: Session

The number of page views. A page view is a

request for a defined page (access to images and

other types of filtered content are not counted).

Formula: sum(One, Page_View)

Level: Page View

Page Views

The percentage of page views.Formula:

Page_Views/total(Page_Views)

Level: Page View

Pct of Page Views

The percentage of sessions.Formula: Sessions/total(Sessions)

Level: Session

Pct of Sessions

11Baseline Profiles




The percentage of visitors.Formula: Visitors/total(Visitors)

Level: Visitor

Pct of Visitors

The percentage of visitors that were referred to

this site from another site.Formula: Referred_Visitors/Visitors

Level: Visitor

Pct Referred Visitors

The number of sessions that were referred to

this site from another site.Formula: Sessions[Referrer<>

'None' and

Referrer<>'bookmarks']

Referred Sessions

Level: Session

The number of visitors that were referred to this

site from another site.Formula: Visitors[Visitor_

Referrer<>'None' and

Visitor_Referrer<>'book marks']

Referred Visitors

Level: Visitor

The percentage of sessions that are not the

visitors’ last sessions.Formula: Sessions[shift(None,Ses

sion,Visitor,1) = ""] / Sessions

Retention

Level: Session

The average length of time (MM:SS) a visitor

spends in a session.Formula: (sum

(Exact_Page_Duration,

Session Duration

Note: You can use this metric with the

Segment Export feature.

Session)*.1/Sessions)[Session_

Duration <= '01:00:00']

Level: Session

The number of sessions that had a page view.Formula: Sessions by Page_View

Sessions by Page View

Level: Session

A count of visitor sessions. A session is a period

of activity for one visitor of a web site.Formula: sum(One, Session)

Level: Session

Sessions

Individual sessions for each visitor are identified

using cookies, timeouts, and other heuristics.

A measure of confidence of the Sessions metric

as reported by data workbench. Mathematically,Formula: confidence(Sessions) *1.281551 / Sessions

SCI80

it is a +/- percentage specifying the range withinLevel: Visitor which the actual answer will lie 80% of the time.

As a rule-of-thumb, doubling the SCI80

percentage will give a range within which the

actual answer will lie 99% of the time.

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A measure of the highest number of possible

visitors as reported by Insight. Mathematically,Formula: (((raw(Visitors) +

.68)^0.5 * 1.281551 + 1.2269) +

UVCI90

it specifies the highest number of visitors with

a 90% probability.raw(Visitors))*(

Visitors/raw(Visitors))

Level: Visitor

A measure of confidence of the Visitors metric

as reported by Insight. Mathematically, it is a

Formula: ((raw(Visitors) +

.68)^0.5 * 1.281551 + 1.2269) /

raw(Visitors)

Level: Visitor

VCI80

+/- percentage specifying the range within

which the actual answer will lie 80% of the time.

As a rule-of-thumb, doubling the VCI80

percentage will give a range within which the

actual answer will lie 99% of the time.

The number of visitors that had a page view.Formula: Visitors by Page_View

Visitors by Page View

Level: Page View

The number of visitors that had a session.Formula: Visitors by Session

Visitors by Session

Level: Session

Traffic Profile Dimensions

The Traffic profile contains the following dimensions to help identify visitor actions.

The dimensions in the following table are defined in the transformation dataset include files in the Traffic\Dataset\Transformation

directory.

DescriptionLevelTypeName

The day of the first log entry of the session.SessionSimpleDay

The day of week of the first log entry of a

session.

SessionSimpleDay of Week

The duration in milliseconds of page view as

measured by subtracting the time of the next

Page View NumericExact Page Duration

(Hidden)

page view from the time of that page view.

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

The hour of the first log entry of a session.SessionSimpleHour

The hour of day of the first log entry of a

session.

SessionSimpleHour of Day

The month of the first log entry of a session.SessionSimpleMonth

13Baseline Profiles



DescriptionLevelTypeName

A log entry or “Event Data Record” satisfying

the Page View Condition.

SessionCountablePage View

The second level domain of the referrer of

the first log entry of the session (or None if

it is an internal referrer domain).

SessionSimpleReferrer

A period of related contiguous activity by a

Visitor. It is delimited by a 30-minute period

VisitorCountableSession

of inactivity and an external referrer domain

or a maximum 48-hour Session Duration.

Both of those timeouts and the set of domains

that are considered internal can be configured

in the Transformation.cfg file.

The URI stem of a page view. The URI

dimension can be redefined using the

Page View SimpleURI

ReplaceURI, PrependURI, and AppendURItransformations.

A unique value of x-trackingid. Usually

corresponds to a unique browser if persistent

N/ACountableVisitor

cookies are used. The x-trackingid can be

otherwise based on IP number or some other

unique identifier such as x.509 common

name.

The week of the first log entry of a session.SessionSimpleWeek

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

DescriptionLevelTypeDimension

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

VisitorSimpleBrowser

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

VisitorSimpleBrowser Type

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

Session

FIRST ROW

SimpleSearch Engine

The URI of the next URI after the currently selected URI. This derived dimension is used

Page View Derived (ShiftDim based on URIdimension)

Next URI

to conduct analysis about what visitors donext after any given URI.

The type of visitor: one-time or repeat.One-time visitors have had only one session

VisitorDerived (SegmentDim based onRepeat Visitors and One-timeVisitors metrics)

Onetime vs Repeat

on the site, while repeat visitors have hadmore than one session.

14Baseline Profiles




The name of each page visited during asession. Initially, each page’s name is the same

Page View Derived (RenameDim based onURI dimension)

Page

as the URI but can be changed for easierinterpretation.

The second level domain name of the web

site that first referred a session to the site (assupplied by the visitor’s browser.)

SessionInherited from the built-in

Referrer dimension

Referrer

The first search phrase in a visitor’s sessionas passed on by a search engine when a visitorhas searched from a named search engine.

Session

FIRST ROW

SimpleSearch Phrase

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

SessionMany-to-Many Search Term

The duration of a session in 30-secondincrements.

SessionDerived (MetricDim based onExact Page Duration metric)

Session Duration

The number of times a visitor has visited the

site. For example, first-time visitors have a

SessionSimpleSession Number

Session Number of “1”, second-time visitorshave a Session Number of “2”, etc.

The number of page views in a session. Forexample, selecting “3” in the Session Page

SessionDerived (MetricDim based onPage Views metric)

Session Page Views

Views dimension would select all sessionswith exactly 3 page views.

The second level domain name of the firstweb site that is a named search engine that

SessionSimpleSearch Engine

referred a visitor to the site during a session(as supplied by the visitor’s browser.)

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

SessionSimpleTime Dimensions

Dimensions including Days Ago, Days of LastMonth, Days of Last Week, Days of This

SessionDerived (LastN and Renamedimensions based on built-intime dimensions)

Time ReportingDimensions

Month, Days of This Week, Hours of Today,Hours of Yesterday, Last 12 Months, Last 2Months, Last 2 Weeks, Last 24 Hours, Last 3Months, Last 4 Weeks, Last 6 Months, Last 7Days, Last 7 Days and Today, Last 8 Weeks,Last 9 Months, Last Month, Last Week,Months Ago, This Month, This Week, This

and Last 14 Days, This and Last 6 Months,This and Last 8 Weeks, Today, Today Reporting, Today and Last 30 Days, WeeksAgo and Yesterday provide a convenient way to build a Workspace or Report which alwaysshows a portion of data in the Dataset. Eachis based upon when a session began.

15Baseline Profiles




The URI of each page viewed.Page View Inherited from the built-inDimension URI

URI

The number of page views to date for a visitor. For example, selecting “3” in the

VisitorDerived (MetricDim based onPage Views metric)

Visitor Page Views

Visitor Page Views dimension would select

all visitors with exactly 3 page views acrossall of their sessions.

The second level domain name of the website that first referred a Visitor to the site for

VisitorInherited from the built-indimension Referrer

Visitor Referrer

their first session (as supplied by the visitor’sbrowser).

Value Profile Metrics

DescriptionLevelFormulaMetric

The percentage of sessions which generated business value

(as defined by the Business Value Model).

SessionSessions[not

Session_Value=#0]/Sessions

Conversion

The percentage of overall value that was generated from

the selected set of sessions.

SessionValue/total(Value)Pct of Value

The total business value generated, in dollars (as defined

by the Business Value Model).

Sessionsum(Session_Value,

Session)*0.01

Value

The count of sessions that generated business value (as

defined by the Business Value Model).

SessionSessions[not

Session_Value=#0]

Value Events

The average number of sessions for each visitor thatgenerated business value (as defined by the Business Value

Model).

Visitor(Value_Events/Visitors)by Visitor

Value Events perVisitor

The average business value generated, in dollars, by each

visitor.

Visitor(Value/Visitors) by

Visitor

Value per Visitor

Value Profile Dimensions


The value of the session as defined by the Business

Value Model.

VisitorDerived (MetricDim

based on Value

metric)

Session Value

The total value that a visitor has generated in all

their sessions. The default increment used for each

segment of value is $50, but can be changed.

VisitorDerived (MetricDim

based on Value

metric)

Value Segment

16Baseline Profiles



Marketing Profile Dimensions

The Campaign dimension is defined in the Site Marketing profile to provide campaign analysis capabilities.


The campaign identifierextracted from a value in the

visitor’s first request.

SessionFIRST ROW operation

Renamed SimpleCampaign

Samples of Custom Marketing Profile Dimensions

You can incorporate additional dimensions of data for further analysis. These dimensions are added by incorporating additional

information into the stream of data that is collected for analysis. For example, the following table contains some of the custom

marketing dimensions that have been added in deployments for customers in various industries:

DescriptionDimension (Custom)

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

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

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

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

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

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

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

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

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

17Baseline Profiles



Third-Party Licenses

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/orother 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 ̀ ÀS IS'' AND ANY

EXPRESSED OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF

MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE

APACHE SOFTWARE FOUNDATION OR ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,

SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENTOF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER

CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (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 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. 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 OpenSSL Toolkit (http://www.openssl.org/).” 4. The

names “OpenSSL Toolkit” and “OpenSSL Project” must not be used to endorse or promote products derived from this software

without prior written permission. For written permission, please contact [email protected] 5. Products derived from

this software may not be called “OpenSSL” nor may “OpenSSL” appear in their names without prior written permission of the

OpenSSL Project. 6. Redistributions of any form whatsoever must retain the following acknowledgment: “This product includes

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

PROVIDED BY THE OpenSSL PROJECT `ÀS IS'' AND ANY EXPRESSED OR IMPLIED WARRANTIES, INCLUDING,

BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR

PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE OpenSSL PROJECT OR ITS CONTRIBUTORS BE LIABLE FOR

ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;

OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,

STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE

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

This product includes cryptographic software written by Eric Young ([email protected]). Copyright (C) 1995-1998 Eric Young

([email protected]) All rights reserved. This package is an SSL implementation written by Eric Young ([email protected]).

18 Third-Party Licenses



The implementation was written so as to conform with Netscape’s SSL. This library is free for commercial and non-commercial

use as long as the following conditions are adhered to. The following conditions apply to all code found in this distribution, 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]). 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 should be given

attribution as the author of the parts of the library used. This can be in the form of a textual message at program startup or in

documentation (online or textual) provided with the package. 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

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. 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 ̀ ÀS IS'' AND

ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF

MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE

AUTHOR OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR

CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR

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

THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR

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

OF SUCH DAMAGE.

Liblzf: This software uses, in a modified form, the LZF compression library. Copyright (c) 2000 Marc 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 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 name of the

author may not be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE AUTHOR `ÀS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES,INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A

PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT,

INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED

TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS

INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT

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

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

PCRE: Copyright (c) 1997-2001 University of Cambridge. Permission is granted to anyone to use this software for any purpose

on any computer system, and to redistribute it freely, subject to the following restrictions: 1. This software is distributed in the

hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY

or FITNESS FOR A PARTICULAR PURPOSE. 2. The origin of this software must not be misrepresented, either by explicit

claim or by omission. In practice, this means that if you use PCRE in software which you distribute to others, commercially or

otherwise, you must put a sentence like this “Regular expression support is provided by the PCRE library package, which is open

source software, written by Philip Hazel, and copyright by the University of Cambridge, England.” Somewhere reasonably visible

in your documentation and in any relevant files or online help data or similar. A reference to the ftp site for the source, that is,

to ftp://ftp.csx.cam.ac.uk/pub/software/programming/pcre/ should also be given in the documentation. 3. Altered versions must

be plainly marked as such, and must not be misrepresented as being the original software.




Truerand: Truerand is based on code by D. P. Mitchell. Truerand was modified by Matt Blaze 7/95, 11/96. Truerand is Version

2.1. This is completely unsupported software. The authors of this software are Don Mitchell and Matt Blaze. Copyright (c) 1995,

1996 by AT&T. Permission to use, copy, and modify this software without fee is hereby granted, provided that this entire notice

is included in all copies of any software which is or includes a copy or modification of this software and in all copies of the

supporting documentation for such software. This software may be subject to United States export controls. THIS SOFTWARE

IS BEING PROVIDED “AS IS”, WITHOUT ANY EXPRESS OR IMPLIED WARRANTY. IN PARTICULAR, NEITHER THE

AUTHORS NOR AT&T MAKE ANY REPRESENTATION OR WARRANTY OF ANY KIND CONCERNING THE

MERCHANTABILITY OF THIS SOFTWARE OR ITS FITNESS FOR ANY PARTICULAR PURPOSE.

libJPEG: The authors make NO WARRANTY or representation, either express or implied, with 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 accuracy. This software is copyright (C) 1991-1998, Thomas G. Lane. All Rights Reserved

except as specified below. Permission is hereby granted to use, copy, modify, and distribute this software (or portions thereof)

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changes to the original files must be clearly indicated in accompanying documentation. (2) If only executable code is distributed,

then the accompanying documentation must state that “this software is based in part on the work of the Independent JPEG

Group”. (3) Permission for use of this software is granted only if the user accepts full responsibility for any undesirable

consequences; the authors accept NO LIABILITY for damages of any kind. These conditions apply to any software derived fromor based on the IJG code, not just to the unmodified library. If you use our work, you ought to acknowledge us. Permission is

NOT granted for the use of any IJG author's name or company name in advertising or publicity relating to this software or

products derived from it. This software may be referred to only as “the Independent JPEG Group's software”. We specifically

permit and encourage the use of this software as the basis of commercial products, provided that all warranty or liability claims

are assumed by the product vendor.

libtiff 3.5.7: Copyright (c) 1988-1997 Sam Leffler. Copyright (c) 1991-1997 Silicon Graphics, Inc. Permission to use, copy, modify,

distribute, and sell this software and its documentation for any purpose is hereby granted without fee, provided that: (i) the

above copyright notices and this permission notice appear in all copies of the software and related documentation, and (ii) the

names of Sam Leffler and Silicon Graphics may not be used in any advertising or publicity relating to the software without the

specific, prior written permission of Sam Leffler and Silicon Graphics. THE SOFTWARE IS PROVIDED “AS-IS” AND WITHOUT

WARRANTY OF ANY KIND, EXPRESS, IMPLIED OR OTHERWISE, INCLUDING WITHOUT LIMITATION, ANY

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LEFFLER OR SILICON GRAPHICS BE LIABLE FOR ANY SPECIAL, INCIDENTAL, INDIRECT OR CONSEQUENTIAL

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WHETHER OR NOT ADVISED OF THE POSSIBILITY OF DAMAGE, AND ON ANY THEORY OF LIABILITY, ARISING

OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.

Bzip: This program, “bzip2” and associated library “libbzip2”, are copyright (C) 1996-2002 Julian R Seward. 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. 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 isnot required. 3. Altered source versions must be plainly marked as such, and must not be misrepresented as being the original

software. 4. The name of the author may not be used to endorse or promote products derived from this software without specific

prior written permission. THIS SOFTWARE IS PROVIDED BY THE AUTHOR ̀ ÀS IS'' AND ANY EXPRESS OR IMPLIED

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FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR

ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,

BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;




OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,

STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE

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

UK. [email protected]. bzip2/libbzip2 version 1.0.2 of 30 December 2001

Libpng: COPYRIGHT NOTICE, DISCLAIMER, and LICENSE: Libpng versions 1.0.7, July 1, 2000, through 1.2.3, May 21, 2002,

are Copyright (c) 2000-2002 Glenn Randers-Pehrson, and are distributed according to the same disclaimer and license as

libpng-1.0.6 with the following individuals added to the list of Contributing Authors, Simon-Pierre Cadieux, Eric S. Raymondand Gilles Vollant. There is no warranty against interference with your enjoyment of the library or against infringement. There

is no warranty that our efforts or the library will fulfill any of your particular purposes or needs. This library is provided with

all faults, and the entire risk of satisfactory quality, performance, accuracy, and effort is with the user. Libpng versions 0.97,

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according to the same disclaimer and license as libpng-0.96, with the following individuals added to the list of Contributing

Authors: Tom Lane, Glenn Randers-Pehrson, and Willem van Schaik. Libpng versions 0.89, June 1996, through 0.96, May 1997,

are Copyright (c) 1996, 1997 Andreas Dilger Distributed according to the same disclaimer and license as libpng-0.88, with the

following individuals added to the list of Contributing Authors: John Bowler, Kevin Bracey, Sam Bushell, Magnus Holmgren,

Greg Roelofs, and Tom Tanner. Libpng versions 0.5, May 1995, through 0.88, January 1996, are Copyright (c) 1995, 1996 Guy

Eric Schalnat, Group 42, Inc. For the purposes of this copyright and license, “Contributing Authors” is defined as the following

set of individuals: Andreas Dilger, Dave Martindale, Guy Eric Schalnat, Paul Schmidt and Tim Wegner. The PNG ReferenceLibrary is supplied “AS IS”. The Contributing Authors and Group 42, Inc. disclaim all warranties, expressed or implied, including,

without limitation, the warranties of merchantability and of fitness for any purpose. The Contributing Authors and Group 42,

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use of the PNG Reference Library, even if advised of the possibility of such damage. Permission is hereby granted to use, copy,

modify, and distribute this source code or portions hereof, for any purpose, without fee, subject to the following restrictions: 1.

The origin of this source code must not be misrepresented. 2. Altered versions must be plainly marked as such and must not be

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

source distribution. The Contributing Authors and Group 42, Inc. specifically permit, without fee, and encourage the use of

this source code as a component to supporting the PNG file format in commercial products. If you use this source code in a

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STLPort: Boris Fomitchev grants End User a non-exclusive, non-transferable, royalty-free license to use STLport and its

documentation without fee. By downloading, using, or copying STLport or any portion thereof, End User agrees to abide by

the intellectual property laws and all other applicable laws of the United States of America, and to all of the terms and conditions

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documentation unchanged: Copyright 1999, 2000 Boris Fomitchev. This material is provided “as is”, with absolutely no warranty

expressed or implied. Any use is at your own risk. Permission to use or copy this software for any purpose is hereby granted

without fee provided the above notices are retained on all copies. Permission to modify the code and to distribute modified code

is granted, provided the above notices are retained, and a notice that the code was modified is included with the above copyright

notice. The End User may distribute binaries compiled with STLport (whether original or modified) without any royalties or

restrictions. The End User may distribute original or modified STLport sources, provided that: The conditions indicated in the

above permission notice are met; The following copyright notices are retained when present, and conditions provided in

accompanying permission notices are met: Copyright 1994 Hewlett-Packard Company; Copyright 1996,97 Silicon Graphics

Computer Systems, Inc.; Copyright 1997 Moscow Center for SPARC Technology; Permission to use, copy, modify, distribute

and sell this software and its documentation for any purpose is hereby granted without fee, provided that the above copyright

notice appear in all copies and that both that copyright notice and this permission notice appear in supporting documentation.

Hewlett-Packard Company makes no representations about the suitability of this software for any purpose. It is provided “as

is” without express or implied warranty. Permission to use, copy, modify, distribute and sell this software and its documentation

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copyright notice and this permission notice appear in supporting documentation. Silicon Graphics makes no representations

about the suitability of this software for any purpose. It is provided “as is” without express or implied warranty. Permission to

use, copy, modify, distribute and sell this software and its documentation for any purpose is hereby granted without fee, provided

that the above copyright notice appear in all copies and that both that copyright notice and this permission notice appear in

supporting documentation. Moscow Center for SPARC Technology makes no representations about the suitability of this

software for any purpose. It is provided “as is” without express or implied warranty.

Zlib: (c) 1995-2002 Jean-loup Gailly and Mark Adler. 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 it freely, 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.

GDAL Library: (c) 2000 Frank Warmerdam. Permission is hereby granted, free of charge, to any person obtaining a copy of this

software and associated documentation files (the “Software”), to deal in the Software without restriction, including without

limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit

persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this

permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED “AS

IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE

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EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER

LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN

CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

NetRatings, Inc.: Adobe, Inc., grants End User a limited, non-exclusive sublicense under the “NetRatings Patents” solely for the

use by End User of the licensed Software Applications. End User expressly acknowledges and agrees that the sublicense granted

under this Agreement does not permit the End User to aggregate “Video Stream Data” (as defined below) from multiple sources

for resale or distribution to third parties. “Video Stream Data” is defined as audience measurement data relating to the exposure

to, or viewership of, video streams (including, without limitation, television and/or IPTV content, sports content, news content,movies and commercials). For purposes of this license, “NetRatings Patents” shall mean the following Patent/Publication

Numbers: US Patents - 5,675,510; 6,115,680; 6,108,637; US20040078292; 5,796,952; 6,138,155; 6,643,696; 6,763,386; US

20050114511; and US 20040221033; Australia: AU701813; AU735285; and AU727170; Brazil - BR9609217 and BR9808033;

Canada - CA2223919; CA2246746; and CA2284530; EP - EP0843946; EP0870234; EP1130526; EP1168196; and EP1010116;

Japan - JP03317705 and JP2000514942; Mexico - MX193614; Norway - NO09705728; WO - WO9641495; WO9810349; and

WO9843380; China - CN1174316; CN1547123; CN1547124; CN1209891; and CN1251669; Denmark -DK870234; Germany -

DE69720186; Spain ES2195170; Israel - IL131871; Korea - KR341110; and New Zealand - NZ337756.

HTML Snapshot: Effective this 14 day of January, 2005, Guangming Software, an entity formed and located in the People's

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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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