3 Base E-Commerce Inline Service Elements

This chapter describes the elements in the Base E-Commerce Inline Service. It contains the following topics:

• Section 3.1, "Introduction to the Base E-Commerce Inline Service"

• Section 3.2, "Entity Logical Model"

• Section 3.3, "Choices Groups and Choices"

• Section 3.4, "Inline Service Advisors"

• Section 3.5, "Inline Service Informants"

• Section 3.6, "Inline Service Entities"

• Section 3.7, "Inline Service Functions"

3.1 Introduction to the Base E-Commerce Inline Service

The following diagram shows an overview of the stages of a typical E-Commerce application and its possible interactions with the Base E-Commerce Inline Service.

The Base E-Commerce Inline Service serves as a general E-Commerce framework for customers to adapt to their business processes.

The Base E-Commerce Inline Service provides pre-defined entities, choices, decisions, models, and integration points.

From an end user perspective, the Base E-Commerce Inline Service is designed on the assumption that customers will perform additional configuration and further customization to fulfill their business requirements.

Additional tasks would involve mapping the logical entity attributes to a customer's physical data sources and to develop the front-end environment for the presentation of any Oracle RTD recommendations.

For more information, see Chapter 4, "Configuring the Base E-Commerce Inline Service."

3.2 Entity Logical Model

The following diagram illustrates the overall general logical entity object model of the Base E-Commerce Inline Service.

For more information about the included Entities, see Section 3.6, "Inline Service Entities."

3.3 Choices Groups and Choices

This section presents an overview of the choice groups and choices, and their usage in the integration points.

This section contains the following topics:

• Section 3.3.1, "Offer-Oriented Choices"

• Section 3.3.2, "Interaction-Oriented Choices"

• Section 3.3.3, "Informants Usage with Offer-Oriented and Transaction-Oriented Choices"

For more information about how the choices and choice groups are used, see Section 3.4, "Inline Service Advisors."

3.3.1 Offer-Oriented Choices

Choices for offer-oriented use cases are structured as follows:

Offers and all other choice groups under it are comprised of dynamic choices. The choice data is either supplied as an Advisor's incoming parameter value (see Section 3.4, "Inline Service Advisors") or retrieved by Oracle RTD from external data sources.

Advisors for Offer-Oriented Choices

The offer-oriented choices are returned when invoking the following Advisors:

• Get Cross Sell Offers

• Get Upsell Offers

• Get Promotions

• Get Advertisements

• Get Offers

  • Updates current web interaction attributes and Web Pages for the session.

  • Identifies any given page a customer navigates to that needs to be tracked.

For more specific information about the Advisors, see Section 3.4, "Inline Service Advisors."

3.3.2 Interaction-Oriented Choices

Choice groups and choices for interaction-oriented usages are structured as follows. Note that the choices under each choice group can be reconfigured to suit the end users needs and serve as a template.

• Abandonment

  • Identifies if customers have abandoned their web session. This would be determined by the business based on their definitions of abandonment.

    Abandonment choice can be obtained by invoking the Advisor Get Abandonment Propensity, and its prediction model is updated by invoking the Advisor Close Session.

  • Returns likelihood of abandonment for a customer.

• Web Actions

  • Identifies key actions done by a customer that can later be applied to entity attributes or models, for example, Update Customer Profile, Register, Un-register. Chat request.

    Web Actions choice can be obtained by invoking the Advisor Get Likely Web Action, and its prediction model is updated by invoking the Informant Customer Action.

• Web Site Duration

  • Web Site Durations's prediction model is updated by invoking the Informant Close Session.

• Web Support Types

  • Web Support Types choice can be obtained by invoking the Advisor Get Web Support Types, and its prediction model is updated by invoking the Informant Web Support Feedback.

  • Returns likelihood for a customer to accept chat request or email support if offered.

3.3.3 Informants Usage with Offer-Oriented and Transaction-Oriented Choices

This section describes the following usages of the Base E-Commerce Inline Service Informants:

• How the Informants provide feedback and additional information to Oracle RTD for the offer-oriented use cases described in Section 3.3.1, "Offer-Oriented Choices"

• How the Informants are used for updating the choice groups described in Section 3.3.2, "Interaction-Oriented Choices"

For more specific information about the Informants, see Section 3.5, "Inline Service Informants."

• Initiate Session

  • Updates current web interaction attributes for the session.

• Identify Customer

  • Updates customer related attributes for the session.

  • Provides Oracle RTD with customer id am profile information if a customer is identified while on the web site. In most cases, identification can be made upon user logon or by previously set cookies at the customer's browser.

• Page Turn

  • Updates current web interaction attributes am Web Pages for the session.

  • Identifies any given page a customer navigates to that needs to be tracked.

• Performed Search

  • Updates current web interaction attributes and Search Keywords for the session.

  • Identifies search words used by a customer.

• Customer Action

  • Updates current web interaction attributes and Web Action for the session.

  • Identifies key actions performed by a customer that can later be applied to entity attributes or models, for example, Update Customer Profile, Register, Un-register, Chat request.

• Added To Cart

  • Updates current web interaction attributes and Shopping Cart Items for the session.

• Offer Response

  • Creates prediction model entries and also captures shopping cart addition events.

  • Identifies if an offer (Upsell, Cross Sell, Promotion, or Ad) is clicked, added to a cart, or purchased by a web user or customer.

• Close Session

  • Creates analytical prediction model entries and triggers learning.

  • Formally closes out the Oracle RTD session.

3.4 Inline Service Advisors

For each Advisor listed in this section, a detailed breakdown is provided for the Integration Point, followed by:

• The Decision called by the Advisor

• The Choice Group used by the Decision

• As appropriate, the Model associated with the Choice Group

3.4.1 Decisioning Advisors

This section describes the following advisors:

• Get Upsell Offers

• Get Cross Sell Offers

• Get Promotions

• Get Advertisements

• Get Offers

3.4.1.1 Get Upsell Offers

The Advisor Get Upsell Offers determines the likelihood for a customer to accept an upsell offer.

Table 3-1 describes the parameters for the Advisor Get Upsell Offers.

Table 3-1 Advisor Get Upsell Offers

Parameter	Description
Advisor Name	Get Upsell Offers
Session Keys	Session / Current Web Interaction / Interaction Id
Request Data	Product Id (optional) Number of Offers Rank Offers (array, optional, to be ranked, as source for dynamic choice)
External System	Web E-Commerce
Order	0
Force session close	No
Decision	Select Upsell Offers
Group Decision	Select Upsell Offers
Default Choices	None
Logic	The supplied product id is assigned to Session / Supplied Product Id. This will be used by function: Select Product Id (for Cross Sell / Up Sell). If supplied, override the default number of choices returned by decision using the Number of Offers incoming parameter. If Rank Offer (string array) is supplied, set these into session as dynamic choice objects to be used by decision later.
Pre-condition	Base Product Id for Cross sell / Up sell must exist. Function: Select Product Id tries to find this Product Id from the following variables: 1 - Session / Supplied Product Id 2 - Session / Current Web Interaction / Current Viewed Product Id 3 - Session / Current Web Interaction / Last Added (into shopping cart) Product Id

Table 3-2 describes the parameters for the decision for the Advisor Get Upsell Offers.

Table 3-2 Decision for Advisor Get Upsell Offers

Parameter	Description
Decision Name	Select Upsell Offers
Select Choices From	Upsell Offers
Number of Choices to Select	5
Select at Random	No
Target Segments	Default
Priorities for Default Segment	Maximize Acceptance Likelihood 33% Maximize Revenue 33% Popularity 33%
Pre Selection Logic	None
Post Selection Logic	Generate learning entries for (int i = 0; i < choices.size(); i++) {choices.get(i).recordEvent("Presented");}

Table 3-3 describes the parameters for the choice group for the Advisor Get Upsell Offers.

Table 3-3 Choice Group for Advisor Get Upsell Offers

Parameter	Description
Choice Group Name	Upsell Offers (Choice Group)
Choice Attributes	Product Id Product Name Product Line Product Type Product Category Offer Type = "Up Sell" Likelihood
Scores	Maximize Acceptance Likelihood = Predicted by Upsell Purchase Model: Purchased Maximize Revenue = Dynamic Choice / Unit Price Popularity = Dynamic Choice / Popularity Rank
Choice Events	Presented (inherited from Offers) Interested (inherited from Offers) Added To Cart Purchased
Choice Eligibility	None
Group Attributes	Upsell Products – Type=Product (Array) – Loading: Get Up Sell Product List (Select Product Id())
Group Eligibility	None
Dynamic Choices	Choice Id is Product Id

Table 3-4 describes the parameters for the model for the Advisor Get Upsell Offers.

Table 3-4 Model for the Advisor Get Upsell Offers

Parameter	Description
Model Name	Upsell Purchase Model (Choice Event Model)
Model Setting	Use for prediction, Randomize Likelihood, Default time window, Algorithm: Bayesian
Choice Group	Upsell Offers
Base Event	Presented
Positive Events	Purchased
Partitioning Attributes	None
Excluded Attributes	None
Learn Location	Offer Response Get Upsell Offers Get Offers
Temporary Data Storage	None

Dependencies:

• Informant - Initiate Session

• Informant - Identify Customer

• Informant - Page Turn

• Informant - Performed Search

• Informant - Customer Action

• Informant - Offer Response

• Informant - Added to Cart

• Informant - Close Session

• Choice Group - Offers

• Function - Select Product Id ( )

• Function - Get Up Sell Product List (Product Id)

3.4.1.2 Get Cross Sell Offers

The Advisor Get Cross Sell Offers determines the likelihood for a customer to accept a cross sell offer.

Table 3-5 describes the parameters for the Advisor Get Cross Sell Offers.

Table 3-5 Advisor Get Cross Sell Offers

Parameter	Description
Advisor Name	Get Cross Sell Offers
Session Keys	Session / Current Web Interaction / Interaction Id
Request Data	Product Id (optional) Number of Offers Rank Offers (array, optional, to be ranked, as source for dynamic choice)
External System	Web E-Commerce
Order	0
Force session close	No
Decision	Select Cross Sell Offers
Group Decision	Select Cross Sell Offers
Default Choices	None
Logic	The supplied product id is assigned to Session / Supplied Product Id. This will be used by function: Select Product Id (for Cross Sell / Up Sell). If supplied, override the default number of choices returned by decision using the Number of Offers incoming parameter. If Rank Offer (string array) is supplied, set these into session as dynamic choice objects to be used by decision later.
Pre-condition	Base Product Id for Cross sell / Up sell must exist. Function: Select Product Id tries to find this Product Id from the following variables: 1 - Session / Supplied Product Id 2 - Session / Current Web Interaction / Current Viewed Product Id 3 - Session / Current Web Interaction / Last Added (into shopping cart) Product Id

Table 3-6 describes the parameters for the decision for the Advisor Get Cross Sell Offers.

Table 3-6 Decision for Advisor Get Cross Sell Offers

Parameter	Description
Decision Name	Select Cross Sell Offers
Select Choices From	Cross Sell Offers
Number of Choices to Select	5
Select at Random	No
Target Segments	Default
Priorities for Default Segment	Maximize Acceptance Likelihood 33% Maximize Revenue 33% Popularity 33%
Pre Selection Logic	None
Post Selection Logic	Generate learning entries for (int i = 0; i < choices.size(); i++) {choices.get(i).recordEvent("Presented");}

Table 3-7 describes the parameters for the choice group for the Advisor Get Cross Sell Offers.

Table 3-7 Choice Group for Advisor Get Cross Sell Offers

Parameter	Description
Choice Group Name	Cross Sell Offers (Choice Group)
Choice Attributes	Product Id Product Name Product Line Product Type Product Category Offer Type = "Cross Sell" Likelihood
Scores	Maximize Acceptance Likelihood = Predicted by Cross Sell Purchase Model: Purchased Maximize Revenue = Dynamic Choice / Unit Price Popularity = Dynamic Choice / Popularity Rank
Choice Events	Presented (inherited from Offers) Interested (inherited from Offers) Added To Cart Purchased
Choice Eligibility	None
Group Attributes	Cross Sell Products - Type=Product (Array) - Loading: Get Cross Sell Product List (Select Product Id())
Group Eligibility	None
Dynamic Choices	Choice Id is Product Id

Table 3-8 describes the parameters for the model for the Advisor Get Cross Sell Offers.

Table 3-8 Model for Advisor Get Cross Sell Offers

Parameter	Description
Model Name	Cross Sell Purchase Model (Choice Event Model)
Model Setting	Use for prediction, Randomize Likelihood, Default time window, Algorithm: Bayesian
Choice Group	Cross Sell Offers
Base Event	Presented
Positive Events	Purchased
Partitioning Attributes	None
Excluded Attributes	None
Learn Location	Offer Response Get Cross Sell Offers Get Offers
Temporary Data Storage	None

Dependencies:

• Informant - Initiate Session

• Informant - Identify Customer

• Informant - Page Turn

• Informant - Performed Search

• Informant - Customer Action

• Informant - Offer Response

• Informant - Added to Cart

• Informant - Close Session

• Choice Group - Offers

• Function - Select Product Id ( )

• Function - Get Cross Sell Product List (Product Id)

3.4.1.3 Get Promotions

The Advisor Get Promotions determines the likelihood for a customer to have an interest on a presented promotion.

Table 3-9 describes the parameters for the Advisor Get Promotions.

Table 3-9 Advisor Get Promotions

Parameter	Description
Advisor Name	Get Promotions
Session Keys	Session / Current Web Interaction / Interaction Id
Request Data	Number of Offers Rank Offers (array, optional, to be ranked, as source for dynamic choice)
External System	Web E-Commerce
Order	0
Force session close	No
Decision	Select Promotions
Group Decision	Select Promotions
Default Choices	None
Logic	If supplied, override the default number of choices returned by decision using the Number of Offers incoming parameter. If Rank Offer (string array) is supplied, set these into session as dynamic choice objects to be used by decision later.
Pre-condition	None

Table 3-10 describes the parameters for the decision for the Advisor Get Promotions.

Table 3-10 Decision for Advisor Promotions

Parameter	Description
Decision Name	Select Promotions
Select Choices From	Promotions
Number of Choices to Select	5
Select at Random	No
Target Segments	Default
Priorities for Default Segment	Maximize Acceptance Likelihood 100%
Pre Selection Logic	None
Post Selection Logic	Generate learning entries for (int i = 0; i < choices.size(); i++) {choices.get(i).recordEvent("Presented");}

Table 3-11 describes the parameters for the choice group for the Advisor Get Promotions.

Table 3-11 Choice Group for Advisor Promotions

Parameter	Description
Choice Group Name	Promotions (Choice Group)
Choice Attributes	Promotion Id Promotion Name Promotion Type Promotion Period Offer Type = "Promotion" Likelihood
Scores	Maximize Acceptance Likelihood = Predicted by Promotion Interest Model: Interested
Choice Events	Presented (inherited from Offers) Interested (inherited from Offers)
Choice Eligibility	None
Group Attributes	Promotion List - Type=Promotion (Array) - Data loading function: Get Promotion List ()
Group Eligibility	None
Dynamic Choices	Choice Id is Promotion Id

Table 3-12 describes the parameters for the model for the Advisor Get Promotions.

Table 3-12 Model for Advisor Get Promotions

Parameter	Description
Model Name	Promotion Interest Model (Choice Event Model)
Model Setting	Use for prediction, Randomize Likelihood, Default time window, Algorithm: Bayesian
Choice Group	Promotions
Base Event	Presented
Positive Events	Interested
Partitioning Attributes	None
Excluded Attributes	None
Learn Location	Offer Response Get Promotions Get Offers
Temporary Data Storage	None

Dependencies:

• Informant - Initiate Session

• Informant - Identify Customer

• Informant - Page Turn

• Informant - Performed Search

• Informant - Customer Action

• Informant - Offer Response

• Informant - Added to Cart

• Informant - Close Session

• Choice Group - Offers

3.4.1.4 Get Advertisements

The Advisor Get Advertisements determines the likelihood for a customer to have an interest on a presented advertisement.

Table 3-13 describes the parameters for the Advisor Get Advertisements.

Table 3-13 Advisor Get Advertisements

Parameter	Description
Advisor Name	Get Advertisements
Session Keys	Session / Current Web Interaction / Interaction Id
Request Data	Number of Offers Rank Offers (array, optional, to be ranked, as source for dynamic choice)
External System	Web E-Commerce
Order	0
Force session close	No
Decision	Select Advertisements
Group Decision	Select Advertisements
Default Choices	None
Logic	If supplied, override the default number of choices returned by decision using the Number of Offers incoming parameter. If Rank Offer (string array) is supplied, set these into session as dynamic choice objects to be used by decision later.
Pre-condition	None

Table 3-14 describes the parameters for the decision for the Advisor Get Advertisements.

Table 3-14 Decision for Advisor Get Advertisements

Parameter	Description
Decision Name	Select Advertisements
Select Choices From	Advertisements
Number of Choices to Select	5
Select at Random	No
Target Segments	Default
Priorities for Default Segment	Maximize Acceptance Likelihood 100%
Pre Selection Logic	None
Post Selection Logic	Generate learning entries for (int i = 0; i < choices.size(); i++) {choices.get(i).recordEvent("Presented");}

Table 3-15 describes the parameters for the choice group for the Advisor Get Advertisements.

Table 3-15 Choice Group for Advisor Get Advertisements

Parameter	Description
Choice Group Name	Advertisements (Choice Group)
Choice Attributes	Ad Id Ad Name Ad Type Ad Category Offer Type = "Ad" Likelihood
Scores	Maximize Acceptance Likelihood = Predicted by Advertisement Interest Model: Interested
Choice Events	Presented (inherited from Offers) Interested (inherited from Offers)
Choice Eligibility	None
Group Attributes	Ad List - Type=Ad (Array) - Data loading function: Get Ad List ()
Group Eligibility	None
Dynamic Choices	Choice Id is Ad Id

Table 3-16 describes the parameters for the model for the Advisor Get Advertisements.

Table 3-16 Model for Advisor Get Advertisements

Parameter	Description
Model Name	Advertisement Interest Model (Choice Event Model)
Model Setting	Use for prediction, Randomize Likelihood, Default time window, Algorithm: Bayesian
Choice Group	Promotions
Base Event	Presented
Positive Events	Interested
Partitioning Attributes	None
Excluded Attributes	None
Learn Location	Offer Response Get Advertisements Get Offers
Temporary Data Storage	None

Dependencies:

• Informant - Initiate Session

• Informant - Identify Customer

• Informant - Page Turn

• Informant - Performed Search

• Informant - Customer Action

• Informant - Offer Response

• Informant - Added to Cart

• Informant - Close Session

• Choice Group - Offers

3.4.1.5 Get Offers

The Advisor Get Offers determines the likelihood for a customer to accept an offer.

The Advisor Get Offers returns a mix of offers:

• Upsell Offers

• Cross Sell Offers

• Promotions

• Advertisements

Table 3-17 describes the parameters for the Advisor Get Offers.

Table 3-17 Advisor Get Offers

Parameter	Description
Advisor Name	Get Offers
Session Keys	Session / Current Web Interaction / Interaction Id
Request Data	Product Id (optional) Number of Offers Rank Offers (array, optional, to be ranked, as source for dynamic choice)
External System	Web E-Commerce
Order	0
Force session close	No
Decision	Select Offers
Group Decision	Select Offers
Default Choices	None
Logic	The supplied product id is assigned to Session / Supplied Product Id. This will be used by function: Select Product Id (for Cross Sell / Up Sell). If supplied, override the default number of choices returned by decision using the Number of Offers incoming parameter. If Rank Offer (string array) is supplied, set these into session as dynamic choice objects to be used by decision later.
Pre-condition	Base Product Id for Cross sell / Up sell must exist. Function: Select Product Id tries to find this Product Id from the following variables: 1 - Session / Supplied Product Id 2 - Session / Current Web Interaction / Current Viewed Product Id 3 - Session / Current Web Interaction / Last Added (into shopping cart) Product Id

Table 3-18 describes the parameters for the decision for the Advisor Get Offers.

Table 3-18 Decision for Advisor Get Offers

Parameter	Description
Decision Name	Select Offers
Select Choices From	Offers
Number of Choices to Select	5
Select at Random	No
Target Segments	Default
Priorities for Default Segment	Maximize Acceptance Likelihood 100%
Pre Selection Logic	None
Post Selection Logic	Generate learning entries for (int i = 0; i < choices.size(); i++) {choices.get(i).recordEvent("presented");}

Table 3-19 describes the parameters for the choice group for the Advisor Get Offers.

Table 3-19 Choice Group for Advisor Get Offers

Parameter	Description
Choice Group Name	Offers (Choice Group)
Choice Attributes	Offer Type Likelihood
Scores	Maximize Acceptance Likelihood
Choice Events	Presented Interested
Choice Eligibility	None
Group Attributes	None
Group Eligibility	None
Dynamic Choices	None

Dependencies:

• Informant - Initiate Session

• Informant - Identify Customer

• Informant - Page Turn

• Informant - Performed Search

• Informant - Customer Action

• Informant - Offer Response

• Informant - Added to Cart

• Informant - Close Session

• Choice Group - Upsell Offers

• Choice Group - Cross Sell Offers

• Choice Group - Promotions

• Choice Group - Advertisements

3.4.2 Analysis Advisors

This section describes the following Advisors:

• Get Abandonment Propensity

• Get Likely Web Action

• Get Likely Web Duration

• Get Web Support Types

3.4.2.1 Get Abandonment Propensity

The Advisor Get Abandonment Propensity returns the likelihood of abandonment for a customer.

Table 3-20 describes the parameters for the Advisor Get Abandonment Propensity.

Table 3-20 Advisor Get Abandonment Propensity

Parameter	Description
Advisor Name	Get Abandonment Propensity
Session Keys	Session / Current Web Interaction / Interaction Id
Request Data	None
External System	Web E-Commerce
Order	0
Force session close	No
Decision	Select Abandonment Propensity
Group Decision	Select Abandonment Propensity
Default Choices	None
Logic	None
Pre-condition	None

Table 3-21 describes the parameters for the decision for the Advisor Get Abandonment Propensity.

Table 3-21 Decision for Advisor Get Abandonment Propensity

Parameter	Description
Decision Name	Select Abandonment Propensity
Select Choices From	Abandonment
Number of Choices to Select	1
Select at Random	No
Target Segments	Default
Priorities for Default Segment	Maximize Likelihood 100%
Pre Selection Logic	None
Post Selection Logic	None

Table 3-22 describes the parameters for the choice group for the Advisor Get Abandonment Propensity.

Table 3-22 Choice Group for Advisor Get Abandonment Propensity

Parameter	Description
Choice Group Name	Abandonment (Choice Group)
Choice Attributes	Name Likelihood = Get Choice Likelihood ("AbandonmentModel", this)
Scores	Maximize Likelihood = Likelihood
Choice Events	None
Choice Eligibility	None
Group Attributes	None
Group Eligibility	None
Dynamic Choices	None

Table 3-23 describes the parameters for the model for the Advisor Get Abandonment Propensity.

Table 3-23 Model for Advisor Get Abandonment Propensity

Parameter	Description
Model Name	Abandonment Model (Choice Model)
Model Setting	Use for prediction, Randomize Likelihood, Default time window, Algorithm: Bayesian
Choice Group	Abandonment
Mutually Exclusive	Yes
Partitioning Attributes	None
Excluded Attributes	None
Learn Location	On session close
Temporary Data Storage	None
Model Name	Abandonment Model (Choice Model)

Dependencies:

• Informant - Close Session

• Function - Get Choice Likelihood (Model Name, Choice)

3.4.2.2 Get Likely Web Action

The Advisor Get Likely Web Action predicts the most likely Web Action that a particular customer will perform next.

Table 3-24 describes the parameters for the Advisor Get Likely Web Action.

Table 3-24 Advisor Get Likely Web Action

Parameter	Description
Advisor Name	Get Likely Web Action
Session Keys	Session / Current Web Interaction / Interaction Id
Request Data	None
External System	Web E-Commerce
Order	0
Force session close	No
Decision	Select Likely Web Action
Group Decision	Select Likely Web Action
Default Choices	None
Logic	None
Pre-condition	None

Table 3-25 describes the parameters for the decision for the Advisor Get Likely Web Action.

Table 3-25 Decision for Advisor Get Likely Web Action

Parameter	Description
Decision Name	Select Likely Web Action
Select Choices From	Web Actions
Number of Choices to Select	1
Select at Random	No
Target Segments	Default
Priorities for Default Segment	Maximize Likelihood 100%
Pre Selection Logic	None
Post Selection Logic	None

Table 3-26 describes the parameters for the choice group for the Advisor Get Likely Web Action.

Table 3-26 Choice Group for Advisor Get Likely Web Action

Parameter	Description
Choice Group Name	Web Actions (Choice Group)
Choice Attributes	Name Likelihood = Get Choice Likelihood ("WebActionModel", this)
Scores	Maximize Likelihood = Likelihood
Choice Events	None
Choice Eligibility	None
Group Attributes	None
Group Eligibility	None
Dynamic Choices	None

Table 3-27 describes the parameters for the model for the Advisor Get Likely Web Action.

Table 3-27 Model for Advisor Get Likely Web Action

Parameter	Description
Model Name	Web Action Model (Choice Model)
Model Setting	Use for prediction, Randomize Likelihood, Default time window, Algorithm: Bayesian
Choice Group	Web Actions
Mutually Exclusive	No
Partitioning Attributes	None
Excluded Attributes	None
Learn Location	Customer Action
Temporary Data Storage	None
Model Name	Web Action Model (Choice Model)

Dependencies:

• Informant - Customer Action

• Function - Get Choice Likelihood (Model Name, Choice)

3.4.2.3 Get Likely Web Duration

The Advisor Get Likely Web Duration predicts the length of time that a particular customer will spend on the site.

Table 3-28 describes the parameters for the Advisor Get Likely Web Duration.

Table 3-28 Advisor Get Likely Web Duration

Parameter	Description
Advisor Name	Get Likely Web Duration
Session Keys	Session / Current Web Interaction / Interaction Id
Request Data	None
External System	Web E-Commerce
Order	0
Force session close	No
Decision	Select Likely Web Duration
Group Decision	Select Likely Web Duration
Default Choices	None
Logic	None
Pre-condition	None

Table 3-29 describes the parameters for the decision for the Advisor Get Likely Web Duration.

Table 3-29 Decision for Advisor Get Likely Web Duration

Parameter	Description
Decision Name	Select Likely Web Duration
Select Choices From	Web Site Duration
Number of Choices to Select	1
Select at Random	No
Target Segments	Default
Priorities for Default Segment	Maximize Likelihood 100%
Pre Selection Logic	None
Post Selection Logic	None

Table 3-30 describes the parameters for the choice group for the Advisor Get Likely Web Duration.

Table 3-30 Choice Group for Advisor Get Likely Web Duration

Parameter	Description
Choice Group Name	Web Site Duration (Choice Group)
Choice Attributes	Name Likelihood = Get Choice Likelihood ("WebSiteDurationModel", this)
Scores	Maximize Likelihood = Likelihood
Choice Events	None
Choice Eligibility	None
Group Attributes	None
Group Eligibility	None
Dynamic Choices	None

Table 3-31 describes the parameters for the model for the Advisor Get Likely Web Duration.

Table 3-31 Model for Advisor Get Likely Web Duration

Parameter	Description
Model Name	Web Site Duration Model (Choice Model)
Model Setting	Use for prediction, Randomize Likelihood, Default time window, Algorithm: Bayesian
Choice Group	Web Site Duration
Mutually Exclusive	Yes
Partitioning Attributes	None
Excluded Attributes	None
Learn Location	On session close
Temporary Data Storage	None
Model Name	Web Site Duration Model (Choice Model)

Dependencies:

• Informant - Customer Action

• Function - Get Choice Likelihood (Model Name, Choice)

3.4.2.4 Get Web Support Types

The Advisor Get Web Support Types returns the likelihood for a customer to accept a chat request or email support if offered.

Table 3-32 describes the parameters for the Advisor Get Web Support Types.

Table 3-32 Advisor Get Web Support Types

Parameter	Description
Advisor Name	Get Web Support Types
Session Keys	Session / Current Web Interaction / Interaction Id
Request Data	None
External System	Web E-Commerce
Order	0
Force session close	No
Decision	Select Web Supports
Group Decision	Select Web Supports
Default Choices	None
Logic	None
Pre-condition	None

Table 3-33 describes the parameters for the decision for the Advisor Get Web Support Types.

Table 3-33 Decision for Advisor Get Web Support Types

Parameter	Description
Decision Name	Select Web Support Types
Select Choices From	Web Support Types
Number of Choices to Select	2
Select at Random	No
Target Segments	Default
Priorities for Default Segment	Maximize Likelihood 100%
Pre Selection Logic	None
Post Selection Logic	Generate learning entries for (int i = 0; i < choices.size(); i++) {choices.get(i).recordEvent("presented");}

Table 3-34 describes the parameters for the choice group for the Advisor Get Web Support Types.

Table 3-34 Choice Group for Advisor Get Web Support Types

Parameter	Description
Choice Group Name	Web Support Types (Choice Group)
Choice Attributes	Name Likelihood of Usage = Predicted by Web Support Usage Model: Used Threshold = 0.5
Scores	Maximize Likelihood = Likelihood of Usage
Choice Events	Presented Used
Choice Eligibility	Choice / Likelihood of Usage > choice / Threshold
Group Attributes	None
Group Eligibility	None
Dynamic Choices	None

Table 3-35 describes the parameters for the model for the Advisor Get Web Support Types.

Table 3-35 Model for Advisor Get Web Support Types

Parameter	Description
Model Name	Web Support Usage Model (Choice Event Model)
Model Setting	Use for prediction, Randomize Likelihood, Default time window, Algorithm: Bayesian
Choice Group	Web Support Types
Base Event	Presented
Positive Events	Used
Partitioning Attributes	None
Excluded Attributes	None
Learn Location	On session close
Temporary Data Storage	None

Dependencies:

• Informant - Web Support Feedback

3.5 Inline Service Informants

This section describes the following Informants:

• Initiate Session

• Identify Customer

• Page Turn

• Performed Search

• Customer Action

• Added To Cart

• Offer Response

• Web Support Feedback

• Close Session

3.5.1 Initiate Session

The Informant Initiate Session creates the session for the interaction and updates current web interaction attributes for the session.

Table 3-36 describes the parameters for the Informant Initiate Session.

Table 3-36 Informant Initiate Session

Parameter	Description
Informant Name	Initiate Session
Session Keys	Session / Current Web Interaction / Interaction Id
Request Data	Origin To Website => Session / Current Web Interaction / Web Interaction / Origin To Website Time Of Day => Session / Current Web Interaction / Web Interaction / Time Of Day User Location => Session / Current Web Interaction / Web Interaction / Web User Location
External System	Web E-Commerce
Order	0
Force session close	No
Logic	None
Pre-condition	None

3.5.2 Identify Customer

The Informant Identify Customer updates and triggers loading of the following customer related attributes for the session:

• Customer Profile

• Interaction History

• Purchase History

• Campaign History

The caller provides Oracle RTD with the Customer Id after a customer is identified while on the web site. In most cases, identification can be made upon user logon or by previously set cookies on the caller's web browser.

Table 3-37 describes the parameters for the Informant Identify Customer.

Table 3-37 Informant Identify Customer

Parameter	Description
Informant Name	Identify Customer
Session Keys	Session / Current Web Interaction / Interaction Id
Request Data	Customer Id => Customer / Customer Id
External System	Web E-Commerce
Order	0
Force session close	No
Logic	None
Pre-condition	None

3.5.3 Page Turn

The Informant Page Turn updates current web interaction attributes (Web Pages) for the session. Identifies any given page a customer navigates to that needs to be tracked

Table 3-38 describes the parameters for the Informant Page Turn.

Table 3-38 Informant Page Turn

Parameter	Description
Informant Name	Page Turn
Session Keys	Session / Current Web Interaction / Interaction Id
Request Data	Current Page => Session / Current Web Interaction / Current Page Current Page Type => Session / Current Web Interaction / Current Page Type Previous Page => Session / Current Web Interaction / Previous Page Previous Page Type => Session / Current Web Interaction / Previous Page Type Time Spent on Previous Page => Session / Current Web Interaction / Time Spent on Previous Page Current Viewed Product Id => Session / Current Web Interaction / Current Viewed Product Id
External System	Web E-Commerce
Order	0
Force session close	No
Logic	(Asynchronous) Update the nested Web Pages session attributes
Pre-condition	None

Supplied Current Viewed Product Id can be used later as the base product id in making cross sell or up sell decision.

3.5.4 Performed Search

The Informant Performed Search updates current web interaction attributes (Search Keywords) for the session. It identifies search words used by a user or customer.

Table 3-39 describes the parameters for the Informant Performed Search.

Table 3-39 Informant Performed Search

Parameter	Description
Informant Name	Performed Search
Session Keys	Session / Current Web Interaction / Interaction Id
Request Data	Search Keyword
External System	Web E-Commerce
Order	0
Force session close	No
Logic	(Asynchronous) Update the nested Searches session attributes
Pre-condition	None

3.5.5 Customer Action

The Informant Customer Action updates current web interaction attributes (Web Action) for the session. It identifies key actions performed by a customer that can later be applied to models, for example, Update Customer Profile, Register, Un-register, Chat request.

Table 3-40 describes the parameters for the Informant Customer Action.

Table 3-40 Informant Customer Action

Parameter	Description
Informant Name	Customer Action
Session Keys	Session / Current Web Interaction / Interaction Id
Request Data	Action Name
External System	Web E-Commerce
Order	0
Force session close	No
Logic	Update Web Action Model (Choice Model) Create or Update Web Action session variable of current interaction
Pre-condition	None

Set Action Name as a choice name into the Web Action Model.

3.5.6 Added To Cart

The Informant Added To Cart updates current web interaction attributes (Cart Item) for the session. It registers a shopping cart item along with its quantity added during the session.

Table 3-41 describes the parameters for the Informant Added To Cart.

Table 3-41 Informant Added to Cart

Parameter	Description
Informant Name	Customer Action
Session Keys	Session / Current Web Interaction / Interaction Id
Request Data	Product Id Quantity
External System	Web E-Commerce
Order	0
Force session close	No
Logic	Update Web Action Model (Choice Model) Create or Update Shopping Cart Item session variable of current interaction
Pre-condition	None

3.5.7 Offer Response

The Informant Offer Response creates prediction model entries and also captures shopping cart addition events. It identifies if an offer (Up Sell, Cross Sell, Promotion, Ad) is clicked, added to cart, or purchased by a web user or customer.

Table 3-42 describes the parameters for the Informant Offer Response.

Table 3-42 Informant Offer Response

Parameter	Description
Informant Name	Offer Response
Session Keys	Session / Current Web Interaction / Interaction Id
Request Data	Offer Id {choice id} Offer Type {Up Sell, Cross Sell, Promotion, Ad} Event {Interested, Added To Cart, Purchased}
External System	Web E-Commerce
Order	0
Force session close	No
Logic	If event = Interested then if offer type = Promotion then create/update Clicked Promotion (increase count if previously exist) if offer type = Ad then create/update Clicked Ad (increase count if previously exist) Record the event into the appropriate Model for the choice (determined by choice id / offer id)
Pre-condition	None

3.5.8 Web Support Feedback

The Informant Web Support Feedback updates the Web Support prediction model.

Table 3-43 describes the parameters for the Informant Web Support Feedback.

Table 3-43 Informant Web Support Feedback

Parameter	Description
Informant Name	Web Support Feedback
Session Keys	Session / Current Web Interaction / Interaction Id
Request Data	Choice Name Choice Event
External System	Web E-Commerce
Order	0
Force session close	No
Logic	If Choice Event = Used then record the event into the Web Support Usage Model
Pre-condition	None

Dependencies:

• Function - Set Choice Event Model (Model Name, Choice Name, Choice Event)

3.5.9 Close Session

The Informant Close Session creates analytical prediction model entries, triggers learning, and formally closes out the Oracle RTD session.

Table 3-44 describes the parameters for the Informant Close Session.

Table 3-44 Informant Close Session

Parameter	Description
Informant Name	Close Session
Session Keys	Session / Current Web Interaction / Interaction Id
Request Data	Abandonment Flag Interaction Duration
External System	Web E-Commerce
Order	0
Force session close	No
Logic	Update Abandonment Model. Possible values for Abandonment Flag are: "Abandoned" "Not Abandoned" Update Web Site Duration Model. Possible values for Interaction Duration are: "00 to 05 Minutes" "05 to 10 Minutes" "10 to 15 Minutes" "15 to 20 Minutes" "20 Minutes or Greater"
Pre-condition	None

Dependencies:

• Function - Set Choice Model (Model Name, Choice Name)

3.6 Inline Service Entities

The following diagram shows the relationships between the Entities defined in the Base E-Commerce Inline Service.

Notation

The diagram shows the standard notation used in UML class diagrams, with each directed line representing a relationship from element A to element B, as follows:

• A line with no diamond represents an association between elements A and B.

• A line with a clear diamond represents an aggregation, with element A "owning" element B. However, with aggregation, removing an instance of element A does not remove the corresponding B element instances.

• A line with a filled diamond represents a composition, with element A "owning" element B. For a composition, removing an instance of element A also removes the corresponding B element instances.

The multiplicity of a relationship restricts how many element B instances the relationship may have. The restriction denotes either a precise limit, such as 1 or 0..1, or an open-ended upper limit, such as "zero or more" or "one or more."

For example:

• A Web Interaction may have many Web Pages. Deleting a particular Web Interaction automatically deletes the corresponding Web Pages.

• A Cart Item has one Product. Deleting the Cart Item does not delete the corresponding Product.

System-Oriented Entities

The Session Entity is a built-in Oracle RTD Entity for maintaining session attribute values.

The following Entities are used for dynamic choice retrieval from external data sources: Ad List, Promotion List, Cross Sell Product List, and Up Sell Product List.

Entities Outline

The Current Web Interaction Entity is a session attribute that keeps track of the current user interaction with the client system.

The Current Web Interaction Entity references the Web Interaction Entity, that itself keeps track of the following data:

• Clicked advertisements, using the Clicked Ad Entity

• Clicked promotions, using the Clicked Promotion Entity

• Searches performed, using the Search Entity

• Actions performed, using the Web Action Entity

• Visited Web pages, using the Web Page Entity

• Items added to the shopping cart, using the Cart Item Entity

The Customer Entity is a session attribute that contains details of the customer profile as well as past customer behavior.

A customer can be a Person or an Organization.

The Customer may have historical information, in Purchase History, Campaign History, and Interaction History. Past customer interactions could be either or both of the following:

• Self-service Web-based interactions, using the Web Interaction Entity

• Interactions through agents, using the Agent Interaction Entity

After a Customer Id has been identified and supplied to Oracle RTD by the Identify Customer Informant, Oracle RTD retrieves data from external data sources for the Customer Entity and for its associated entity attributes.

In addition to the Entity attributes that are normally mapped to a data source directly, derived attributes are also included, which obtain their values via Java functions that utilize the applicable raw data extracted from data sources as inputs.

This section describes the following Entities:

• Session Entity

• Ad Entity

• Ad List Entity

• Agent Interaction Entity

• Campaign Entity

• Campaign History Entity

• Campaign Item Entity

• Cart Item Entity

• Clicked Ad Entity

• Clicked Promotion Entity

• Cross Sell Product List Entity

• Current Web Interaction Entity

• Customer Entity

• Interaction History Entity

• Organization Entity

• Person Entity

• Product Entity

• Promoted Item Entity

• Promotion Entity

• Promotion List Entity

• Purchased Item Entity

• Purchase History Entity

• Rank Offers Entity

• Search Entity

• Up Sell Product List Entity

• Web Action Entity

• Web Interaction Entity

• Web Page Entity

3.6.1 Session Entity

(Key = Web Session Id)

Table 3-45 Session Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Customer	No	Customer	Yes	Yes	None
Current Web Interaction	No	Current Web Interaction	Yes	Yes	None
Rank Offers	No	Rank Offers	No	No	Utilized when ranking offers directly from an Offer Advisor instead of read from a data source.
Supplied Product Id	No	String	No	No	Utilized when ranking offers directly from an Offer Advisor instead of read from a data source.

3.6.2 Ad Entity

The Ad Entity is used in conjunction with the Ad List Entity and is used for the dynamic choice associated to the Ad Choice group.

Table 3-46 Ad Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Ad Id	No	String	No	No	Key
Category	No	String	No	No	None
Name	No	String	No	No	None
Type	No	String	No	No	None

3.6.3 Ad List Entity

The Ad List Entity is used in conjunction with the Ad Entity and is used for the dynamic choice associated to the Ad Choice group.

Table 3-47 Ad List Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Active	No	String	No	No	Key
Ads	Yes	Ad	No	No	The Ads attribute is an array attribute based on the Ad Entity.

3.6.4 Agent Interaction Entity

The Agent Interaction Entity contains attributes related to agent interactions that have taken place with a customer. This Entity is used to create an array of agent interactions within the Interaction History Entity, which in turn is associated to the Customer Entity.

Table 3-48 Agent Interaction Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Interaction Id	No	String	No	No	None
Agent Id	No	String	No	No	None
Agent Location	No	String	No	No	None
Customer Location	No	String	No	No	None
Interaction Channel	No	String	No	No	None
Interaction Date	No	None	No	No	None
Interaction Duration	No	Integer	No	No	None
Interaction Reason	No	String	No	No	None
Interaction Status	No	String	No	No	None
Interaction Type	No	String	No	No	None
Time Of Day	No	String	No	No	None

3.6.5 Campaign Entity

The Campaign Entity contains attributes related to campaigns that have been associated to a customer. This Entity is associated to the customer via the Campaign Item and Campaign History entities.

Table 3-49 Campaign Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Campaign Id	No	String	No	No	None
Category	No	String	Yes	Yes	None
Name	No	String	Yes	Yes	None
Period	No	String	Yes	Yes	None
Type	No	String	Yes	Yes	None

3.6.6 Campaign History Entity

The Campaign History Entity contains attributes related to campaigns that have been associated to a customer. This Entity is associated to the Customer Entity and also contains the Campaign Items Entity.

Table 3-50 Campaign History Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Last Campaign Category	No	String	Yes	Yes	Default Value based on the Get Last Campaign function
Last Campaign Date	No	Date	Yes	Yes	Default Value based on the Get Last Campaign Date function
Last Campaign Delivery Method	No	String	Yes	Yes	Default Value based on the Get Last Campaign Delivery Method function
Last Campaign Name	No	String	Yes	Yes	Default Value based on the Get Last Campaign Name function
Last Campaign Type	No	String	Yes	Yes	Default Value based on the Get Last Campaign Type function
Days Since Last Campaign	No	Integer	Yes	Yes	Default Value based on the Get Days Since Last Campaign
Campaign Items	Yes	Campaign Item	Yes	Yes	The Campaign Items attribute is an array attribute based on the Campaign Item Entity.

3.6.7 Campaign Item Entity

The Campaign Item Entity contains attributes related to campaigns that have been associated to a customer. This Entity is associated to the customer via the Campaign History Entity and contains the Campaign Entity.

Table 3-51 Campaign Item Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Campaign Date	No	Date	Yes	Yes	None
Delivery Method	No	String	Yes	Yes	None
Campaign	No	Campaign	Yes	Yes	The Campaign attribute is based on the Campaign Entity.

3.6.8 Cart Item Entity

The Cart Item Entity contains attributes related to the products that a customer has put in their shopping cart in their web session. The Cart Item Entity contains the Product Entity, and is itself embedded in the Web Interaction Entity.

Table 3-52 Cart Item Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Quantity	No	Integer	Yes	Yes	None
Product	No	Product	Yes	Yes	None

3.6.9 Clicked Ad Entity

The Clicked Ad Entity contains attributes related to the ads which a customer may have clicked during their web session. The Clicked Ad Entity contains the Ad Entity, and is itself embedded in the Web Interaction Entity.

Table 3-53 Clicked Ad Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Count	No	Integer	Yes	Yes	None
Ad	No	Ad	Yes	Yes	None

3.6.10 Clicked Promotion Entity

The Clicked Promotion Entity contains attributes related to the ads which a customer may have clicked during their web session. The Clicked Promotion Entity contains the Promotion Entity, and is itself embedded in the Web Interaction Entity.

Table 3-54 Clicked Promotion Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Count	No	Integer	Yes	Yes	None
Promotion	No	Promotion	Yes	Yes	None

3.6.11 Cross Sell Product List Entity

The Cross Sell Product List Entity is used in conjunction with the Products Entity (instantiated as Cross Sell Products), and is used for the dynamic choice associated to the Cross Sell Offers Choice group.

Table 3-55 Cross Sell Product List Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Product Id	No	String	No	No	None
Cross Sell Products	Yes	Product	No	No	The Cross Sell Products attribute is an array attribute based on the Product Entity.
Cross Sell Products - Product Id	No	String	No	No	None

3.6.12 Current Web Interaction Entity

The Current Web Interaction Entity contains attributes related to what a customer is doing during their current web session. The Current Web Interaction Entity contains its own attributes as well as attributes from the Web Interaction Entity.

See Section 3.6.27.1, "Derivation of Web Interaction Attributes in Referencing Entities" for details of how the Web Interaction attributes Interaction Date, Start Time, and Total Duration in Minutes are derived.

Table 3-56 Current Web Interaction Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Interaction Id	No	String	Yes	Yes	None
Current Page	No	String	Yes	Yes	None
Current Page Type	No	String	Yes	Yes	None
Current Viewed Product Id	No	String	Yes	Yes	None
Last Added Product Id	No	String	Yes	Yes	None
Previous Page	No	String	Yes	Yes	None
Previous Page Type	No	String	Yes	Yes	None
Time Spent on Previous Page	No	Integer	Yes	Yes	None
Web Interaction	No	Web Interaction	Yes	Yes	None

3.6.13 Customer Entity

The Customer Entity contains attributes related to the profile of the customer. The Customer Entity contains its own attributes and links in the Campaign History, Interaction History, Organization, Person, and Purchase History Entities.

Table 3-57 Customer Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Customer Id	No	String	No	No	Key
Address City	No	String	Yes	Yes	None
Address Country	No	String	Yes	Yes	None
Address Postal Code	No	String	Yes	Yes	None
Address Region	No	String	Yes	Yes	None
Address State Province	No	String	Yes	Yes	None
Credit Hold	No	String	Yes	Yes	None
Life Time Value Score	No	Double	Yes	Yes	None
Offline Churn Propensity	No	Double	Yes	Yes	None
Phone Area Code	No	String	Yes	Yes	None
Preferred Language	No	String	Yes	Yes	None
Start Date	No	Date	Yes	Yes	None
Status	No	String	Yes	Yes	None
Target Market Segment	No	String	Yes	Yes	None
Tenure	No	Integer	Yes	Yes	None
Total Credit Limit	No	Double	Yes	Yes	None
Type	No	String	Yes	Yes	Default Value determined by Get Customer Type function.
Campaign History	No	Campaign History	Yes	Yes	The Campaign History attribute is based on the Campaign History Entity. See Campaign History Entity for attribute breakdown.
Interaction History	No	Interaction History	Yes	Yes	The Interaction History attribute is based on the Interaction History Entity. See Interaction History Entity for attribute breakdown.
Organization	No	Organization	Yes	Yes	The Organization attribute is based on the Organization Entity. See Organization Entity for attribute breakdown.
Person	No	Person	Yes	Yes	The Person attribute is based on the Person Entity. See Person Entity for attribute breakdown.
Purchase History	No	Purchase History	Yes	Yes	The Purchase History attribute is based on the Purchase History Entity. See Purchase History Entity for attribute breakdown.

3.6.14 Interaction History Entity

The Interaction History Entity contains attributes that record what a customer has done in the past regarding previous interactions. The Interaction History Entity contains derived attributes from both previous Agent Interactions and previous Web Interactions.

See Section 3.6.27.1, "Derivation of Web Interaction Attributes in Referencing Entities" for details of how the Past Web Interactions attributes Interaction Date, Start Time, and Total Duration in Minutes are derived.

Table 3-58 Interaction History Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Agent Interaction Reasons In Past 30 Days	Yes	String	Yes	Yes	Default determined by Get Agent Interaction Reasons In Past Days function
Agent Interaction Types in Past 30 Days	Yes	String	Yes	Yes	Default determined by Get Agent Interaction Types In Past Days function
Days Since Last Agent Interaction	No	Integer	Yes	Yes	Default determined by Get Days Since Last Agent Interaction function
Days Since Last Interaction	No	Integer	Yes	Yes	Default determined by Maximum function
Days Since Last Web Interaction	No	Integer	Yes	Yes	Default determined by Get Days Since Last Web Interaction function
Interaction Types In Past 30 Days	No	String	Yes	Yes	Default determined by Get Interaction Types function
Last Agent Interaction Status	No	String	Yes	Yes	Default determined by Get Last Agent Interaction Status function
Last Agent Interaction Type	No	String	Yes	Yes	Default determined by Get Last Agent Interaction Type function
Last Interaction Type	No	String	Yes	Yes	Default determined by Get Last Interaction Type function
Number of Agent Interactions In Past 30 Days	No	Integer	Yes	Yes	Default determined by Get Number Of Agent Interaction in Past Days function
Number of Agent Interactions In Past 90 Days	No	Integer	Yes	Yes	Default determined by Get Number Of Agent Interaction in Past Days function
Number of Agent Interactions In Past Year	No	Integer	Yes	Yes	Default determined by Get Number Of Agent Interaction in Past Days function
Number of Web Interactions In Past 30 Days	No	Integer	Yes	Yes	Default determined by Get Number Of Web Interaction in Past Days function
Number of Web Interactions In Past 90 Days	No	Integer	Yes	Yes	Default determined by Get Number Of Web Interaction in Past Days function
Number of Web Interactions In Past Year	No	Integer	Yes	Yes	Default determined by Get Number Of Web Interaction in Past Days function
Performed Web Actions In Past 30 Days	Yes	String	Yes	Yes	Default determined by Get Performed Web Actions in Past Days function
Past Agent Interactions	Yes	Agent Interaction	No	No	None
Past Web Interactions	Yes	Web Interaction	No	No	None

3.6.15 Organization Entity

The Organization Entity contains attributes related to the profile of an Organization. The Organization Entity is linked to the session through the Customer Entity.

Table 3-59 Organization Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Annual Gross Profit	No	Double	Yes	Yes	None
Annual Revenue	No	Double	Yes	Yes	None
Business Partner Flag	No	String	Yes	Yes	None
Established Service	No	Integer	Yes	Yes	None
Line Of Business	No	String	Yes	Yes	None
Number of Employees	No	Integer	Yes	Yes	None
Number Of Years Established	No	Integer	Yes	Yes	None
Size	No	String	Yes	Yes	None
Type	No	String	Yes	Yes	None

3.6.16 Person Entity

The Person Entity contains attributes related to the profile of a Person. The Person Entity is linked to the session through the Customer Entity.

Table 3-60 Person Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Age	No	Integer	Yes	Yes	None
Annual Income	No	Double	Yes	Yes	None
Credit Score	No	Integer	Yes	Yes	None
Education Level	No	String	Yes	Yes	None
Ethnicity	No	String	Yes	Yes	None
Gender	No	String	Yes	Yes	None
Marital Status	No	String	Yes	Yes	None
Net Worth	No	Double	Yes	Yes	None
Number Of Children	No	Integer	Yes	Yes	None
Profession	No	String	Yes	Yes	None

3.6.17 Product Entity

The Product Entity contains attributes related to a generic Product. The Product Entity is used as a reference entity under the Cart Item, Cross Sell Product List, Promoted Item, Purchased Item, and Up Sell Product Entities.

Table 3-61 Product Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Product Id	No	String	No	No	Key
Category	No	String	Yes	Yes	None
Name	No	String	Yes	Yes	None
Popularity Rank	No	Integer	Yes	Yes	None
Product Line	No	String	Yes	Yes	None
Type	No	String	Yes	Yes	None
Unit Price	No	Double	Yes	Yes	None

3.6.18 Promoted Item Entity

The Promoted Item Entity contains attributes related to a Promoted Item. The Promoted Item Entity is used in conjunction with the Promotion Entity, which can contain multiple promoted Items.

Table 3-62 Promoted Item Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Discount Rate	No	Double	Yes	Yes	None
Promoted Product	No	Product	Yes	Yes	None

3.6.19 Promotion Entity

The Promotion Entity is used in conjunction with the Promotion List Entity, and is used for the dynamic choice associated to the Promotions Choice group.

Table 3-63 Promotion Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Promotion Id	No	String	No	No	None
Category	No	String	No	No	None
Days Left	No	Integer	No	No	Default Value set by Get Days Left function
Duration In Days	No	Integer	No	No	Default Value set by Get Duration In Days function
Effective Date	No	Date	No	No	None
Expiry Date	No	Date	No	No	None
Name	No	String	No	No	None
Period	No	String	No	No	None
Type	No	String	No	No	None
Promoted Items	Yes	Promoted Item	No	No	The Promoted Items attribute is based on the Promoted Item Entity. See Promoted Item Entity for attribute breakdown.

3.6.20 Promotion List Entity

The Promotion List Entity is used in conjunction with the Promotion Entity, and is used for the dynamic choice associated to the Promotions Choice group.

Table 3-64 Promotion List Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Active	No	String	No	No	Key
Promotions	Yes	Promotion	No	No	The Promotions attribute is based on the Promotion Entity. See Promotion Entity for attribute breakdown.

3.6.21 Purchased Item Entity

The Purchased Item Entity contains attributes related to a purchased item. This Entity is associated to the Customer Entity through the Purchase History Entity.

Table 3-65 Purchased Item Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Purchase Amount	No	Double	Yes	Yes	None
Purchase Date	No	Date	Yes	Yes	None
Purchased Product	No	Product	Yes	Yes	None

3.6.22 Purchase History Entity

The Purchased History Entity contains attributes related to a customer's past purchases. This Entity is associated to the session via the Customer Entity.

Table 3-66 Purchase History Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Days Since Last Purchase	No	Integer	Yes	Yes	Default Value set by Get Days Since Last Purchase function
Last Purchase Amount	No	Double	Yes	Yes	Default Value set by Get Last Purchase Amount function
Last Purchased Product	No	String	Yes	Yes	Default Value set by Get Last Purchased Product function
Last Purchased Product Line	No	String	Yes	Yes	Default Value set by Get Last Purchased Product Line function
Product Lines Owned	Yes	String	Yes	Yes	Default Value set by Get Product Lines Owned function
Total Amount Spent	No	Double	Yes	Yes	Default Value set by Get Total Amount Spent function
Total Amount Spent in Last 90 Days	No	Double	Yes	Yes	Default Value set by Get Total Amount Spent In Last 90 Days function
Purchased Items	Yes	Purchased Item	Yes	Yes	The Purchased Items array attribute is based on the Purchased Item Entity. See Purchased Item Entity for attribute breakdown.

3.6.23 Rank Offers Entity

The Rank Offers Entity is used to store arrays of different offer types that are passed to the Inline Service via an Advisor. After it is filled by the Advisor input, the Entity is then used to populate the corresponding dynamic choice.

Table 3-67 Rank Offers Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Ads	Yes	String	No	No	None
CrossSellOffers	Yes	String	No	No	None
In Use	No	Boolean	No	No	Default Value is False
Promotions	Yes	String	No	No
UpSellOffers	Yes	String	No	No

3.6.24 Search Entity

The Search Entity is used to store attributes related to search strings performed by a customer. This Entity is used by the Web Interaction Entity as an array attribute.

Table 3-68 Search Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Count	No	Integer	Yes	Yes	None
Keyword	No	String	Yes	Yes	None

3.6.25 Up Sell Product List Entity

The Up Sell Product List Entity is used in conjunction with the Products Entity (instantiated as Up Sell Products), and is used for the dynamic choice associated to the Up Sell Offers Choice group.

Table 3-69 Up Sell Product List Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Product Id	No	String	No	No	None
Up Sell Products	Yes	Product	No	No	The Up Sell Products attribute is an array attribute based on the Product Entity.

3.6.26 Web Action Entity

The Web Action Entity is used to store attributes related to actions performed by a customer while on the web. This Entity is used by the Web Interaction Entity as an array attribute.

Table 3-70 Web Action Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Name	No	String	No	No	Key
Category	No	String	Yes	Yes	None
Type	No	String	Yes	Yes	None
Web Action Id	No	String	Yes	Yes	None

3.6.27 Web Interaction Entity

The Web Interaction Entity contains attributes related to a generic Web Interaction. This Entity is used as a reference entity under for the Current Web Interaction Entity as well as an array attribute (Past Web Interactions) under the Interaction History Entity.

See Section 3.6.27.1, "Derivation of Web Interaction Attributes in Referencing Entities" for details of how the Interaction Date, Start Time, and Total Duration in Minutes attributes are used in the Current Web Interaction Entity and the Interaction History Entity.

Table 3-71 Web Interaction Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Interaction Id	No	String	No	No	Key
Clicked Ads	Yes	Clicked Ad	Yes	Yes	The Clicked Ads attribute is an array attribute based on the Clicked Ad Entity. See the Clicked Ad Entity for attribute breakdown.
Clicked Promotions	Yes	Clicked Promotion	Yes	Yes	The Clicked Promotions attribute is an array attribute based on the Clicked Promotion Entity. See the Clicked Promotion entity for attribute breakdown.
Interaction Date	No	Date	Yes	Yes	None
Origin To Website	No	String	Yes	Yes	None
Performed Actions	Yes	Web Action	Yes	Yes	The Performed Actions attribute is an array attribute based on the Web Action Entity. See the Web Action Entity for attribute breakdown.
Performed Searches	Yes	Search	Yes	Yes	The Performed Searches attribute is an array attribute based on the Search Entity. See the Search Entity for attribute breakdown.
Shopping Cart Items	Yes	Cart Item	Yes	Yes	The Shopping Cart Items attribute is an array attribute based on the Cart Item Entity. See the Cart Item Entity for attribute breakdown.
Start Time	No	Date	No	No	Attribute used to derive the Web Interaction attribute Total Duration in Minutes when used in the Current Web Interaction Entity.
Time Of Day	No	String	Yes	Yes	None
Total Duration in Minutes	No	String	Yes	Yes	None
Visited Pages	Yes	Web Page	Yes	Yes	The Visited Pages attribute is an array attribute based on the Web Page Entity. See the Web Page Entity for attribute breakdown.
Web User Location	No	String	Yes	Yes	None

3.6.27.1 Derivation of Web Interaction Attributes in Referencing Entities

When the Current Web Interaction Entity and the Interaction History Entity reference the Web Interaction Entity, special considerations apply to the derivation of certain attributes, as follows:

Table 3-72 Derivation of Web Interaction Attributes in Referencing Entities

Web Interaction Attribute	As used in the Current Web Interaction Entity attribute Web Interaction	As used in the Interaction History Entity attribute Past Web Interactions
Interaction Date	NA	Retrieved from the external data source using Web Interaction mapping
Start Date	Initialized by Informant Initiate Session with the Current Time	Not initialized
Total Duration in Minutes	Computed as the difference between Web Interaction-Start Time and Current Time	Retrieved from the external data source using Web Interaction mapping

3.6.28 Web Page Entity

The Web Page Entity is used to store attributes related to the attributes of a web page that a customer has visited while on the web. This Entity is used by the Web Interaction Entity as an array attribute.

Table 3-73 Web Page Entity

Attribute	Array	Type	Show In DC	Use for Analysis	Comments
Web Page Id	No	String	No	No	Key
Average Time Spent On Page	No	Double	Yes	Yes	None
Category	No	String	Yes	Yes	None
Count	No	Integer	Yes	Yes	None
Name	No	String	Yes	Yes	None
Type	No	String	Yes	Yes	None

3.7 Inline Service Functions

This section describes the functions used in the Base E-Commerce Inline Service.

Table 3-74 Base E-Commerce Inline Service Functions

Function	Inputs	Outputs	Area Utilized In	Comments
Get Ad List	None	Advertisements (Array of Ad)	Used for Advertisements dynamic choices. See corresponding functions: Set Session Rank Offers.	This function is used to return array of Ad Entity for Advertisement dynamic choice. The result is either ranked advertisements array supplied as incoming parameter of Advisors or array of advertisements loaded using data source mapping.
Get Agent Interaction Reasons In Past Days	Past Agent Interactions (Array of Agent Interaction), Days (Integer)	Interaction Reasons (Array of String)	Used for deriving values for Interaction History Entity.	This function returns array of interaction reason in past given days.
Get Agent Interaction Types In Past Days	Past Agent Interactions (Array of Agent Interaction), Days (Integer)	Interaction Types (Array of String)	Used for deriving values for Interaction History Entity.	This function returns array of interaction types in past given days.
Get Campaign Names In Past Days	Campaign Items (Array of Campaign Item), Days (Integer)	Campaign Names (Array of String)	Used for deriving values for Campaign History Entity	This function returns array of campaign names delivered in past given days.
Get Choice Likelihood	Model Name (String), Choice (Choice)	Likelihood (Double)	Used for scoring in Abandonment, Web Actions, Web Site Duration choice groups	This function returns likelihood for a given inputted choice that is part of a Choice Model (as opposed to a choice even model). As inputs, the user must pass in a choice and the model name that choice is part of.
Get Cross Sell Product List	Product Id (String) to be used as base product for cross sell	Cross Sell Products (Array of Product)	Used for Cross Sell dynamic choices. See corresponding functions: Set Session Rank Offers.	This function is used to return array of Product Entity for Cross Sell dynamic choice. The result is either ranked products array supplied as incoming parameter of Advisors or array of cross sell products loaded using data source mapping.
Get Customer Type	Person (Person), Organization (Organization)	Customer Type (String)	Used by Customer Entity.	This function is used to determine customer type.
Get Days Left	Expiration Date (Date)	Number of Days Left (Integer)	Used by Promotion Entity.	This function calculates the number of days from now to expiryDate.
Get Days Since Last Agent Interaction	Past Agent Interactions (Array of Agent Interaction)	Number of Days (Integer)	Used by Interaction History Entity.	This function calculates the number of days from last agent interaction to now.
Get Days Since Last Campaign	Campaign Items (Array of Campaign Item)	Number of Days (Integer)	Used by Campaign History Entity.	This function calculates the number of days from last campaign to now.
Get Days Since Last Purchase	Purchased Items (Array of Purchased Item)	Number of Days (Integer)	Used by Purchase History Entity.	This function calculates the number of days from last purchase to now.
Get Days Since Last Web Interaction	Past Web Interactions (Array of Web Interaction)	Number of Days (Integer)	Used by Interaction History Entity.	This function calculates the number of days from last web interaction to now.
Get Duration In Days	Start Date (Date), End Date (Date)	Number of Days (Integer)	Used by Promotion Entity and various other functions.	This function calculates the number of days from start date to end date.
Get Duration In Minutes	Start Time (Date), End Time (Date)	Number of Minutes (Integer)	NA.	This function calculates the number of minutes from start time to end time.
Get Gender	Male (Boolean)	Gender In Text (String)	Used by Customer Entity.	This function determines the gender of a person. This converts the given gender type from boolean to string. In Male case, genderMale is boolean value=true fetched from data source.
Get Interaction Types In Past Days	Past Agent Interactions (Array of Agent Interaction), Past Web Interactions (Array of Web Interaction), Days (Integer)	Interaction Type in Text (String)	Used by Interaction History Entity.	This function returns interaction type in past given days.
Get Last Agent Interaction Status	Past Agent Interactions (Array of Agent Interaction)	Last Status (String)	Used by Interaction History Entity	This function returns last agent interaction status.
Get Last Agent Interaction Type	Past Agent Interactions (Array of Agent Interaction)	Last Type (String)	Used by Interaction History Entity	This function returns last agent interaction type.
Get Last Campaign Category	Campaign Items (Array of Campaign Item)	Category (String)	Used by Campaign History Entity.	This function returns last campaign category.
Get Last Campaign Delivery Method	Campaign Items (Array of Campaign Item)	Delivery Method (String)	Used by Campaign History Entity.	This function returns last campaign delivery method.
Get Last Campaign Name	Campaign Items (Array of Campaign Item)	Name (String)	Used by Campaign History Entity.	This function returns last campaign name.
Get Last Campaign Type	Campaign Items (Array of Campaign Item)	Type (String)	Used by Campaign History Entity.	This function returns last campaign type.
Get Last Interaction Type	Days Since Last Agent Interaction (Integer), Days Since Last Web Interaction (Integer)	Interaction Type (String)	Used by Interaction History Entity.	This function returns last interaction type. Return value will be Agent, Web, or Both.
Get Last Purchase Amount	Purchased Items (Array of Purchased Item)	Purchase Amount (Double)	Used by Purchase History Entity.	This function returns last purchase amount.
Get Last Purchased Product	Purchased Items (Array of Purchased Item)	Product Name (String)	Used by Purchase History Entity.	This function returns last purchased product name.
Get Last Purchased Product Line	Purchased Items (Array of Purchased Item)	Product Line (String)	Used by Purchase History Entity.	This function returns last purchased product line.
Get Number Of Agent Interaction In Past Days	Past Agent Interactions (Array of Agent Interaction), Days (Integer)	Count (Integer)	Used by Interaction History Entity.	This function counts number of agent interactions in past given days.
Get Number Of Web Interaction In Past Days	Past Web Interactions (Array of Web Interaction), Days (Integer)	Count (Integer)	Used by Interaction History Entity.	This function counts number of web interactions in past given days.
Get Performed Web Action Names In Past Days	Past Web Interactions (Array of Web Interaction), Days (Integer)	Action Names (Array of String)	Used by Interaction History Entity.	This function returns array of web action names performed in past given days.
Get Product Lines Owned	Purchased Items (Array of Purchased Item)	Product Lines (Array of String)	Used by Purchase History Entity.	This function returns product lines of customer owned.
Get Promotion List	None	Promotions (Array of Promotion)	Used for Promotion dynamic choices. See corresponding functions: Set Session Rank Offers.	This function is used to return array of Promotion Entity for Promotion dynamic choice. The result is either ranked promotion array supplied as incoming parameter of Advisors or array of promotions loaded using data source mapping.
Get Specific Choice Likelihood	Model Name (String), Choice Name (String)	Likelihood (Double)	None. See similar function: Get Choice Likelihood	This function returns likelihood for a given inputted choice that is part of a Choice Model (as opposed to a choice even model). As inputs, the user must pass in the value for the Name attribute assigned to the choice and the model name that choice is part of.
Get Total Amount Spent	Purchased Items (Array of Purchased Item)	Amount (Double)	Used by Purchase History Entity.	This function sums up the amount of customer spent so far.
Get Total Amount Spent in Last 90 Days	Purchased Items (Array of Purchased Item)	Amount (Double)	Used by Purchase History Entity.	This function sums up the amount of customer spent in past 90 days.
Get Total Duration In Minutes	Start Time (Date)	Number of Minutes (Integer)	Used by Web Interaction Entity.	This function calculates number of minutes between the given start time and now.
Get Up Sell Product List	Product Id (String) to be used as base product for up sell	Up Sell Products (Array of Product)	Used for Up Sell dynamic choices. See corresponding functions: Set Session Rank Offers.	This function is used to return array of Product Entity for Up Sell dynamic choice. The result is either ranked products array supplied as incoming parameter of Advisors or array of up sell products loaded using data source mapping.
Get Year	Date (Date)	Year (Integer)	Used by Customer Entity.	This function returns the year part of Date.
Is Web Support Type Eligible	Web Support Types Choice (Web Support Types Choice)	Eligible (Boolean)	Used by Web Support Types Choice Group.	This function returns the eligibility of a Web Support Types Choice.
Maximum	X (Integer), Y (Integer)	Maximum (Integer)	Used by Interaction History Entity.	This function returns the greater parameter.
Minutes To Now	Start Time (Date)	Minutes (Integer)	Used by Total Duration In Minutes function	This function returns time between given time in the past and now.
Multiply	a (Double, b (Double)	Result (Double)	Used by various RTD elements	This function multiplies the given parameters.
Property Reflect	NA	NA	NA	This function is used for testing. This dumps the values of session attributes.
Select Product Id	None	Product Id (String)	Used as base product for Up Sell and Cross Sell dynamic choices.	This function determines what Product Id to be used as base Product Id for Up Sell or Cross Sell.
Set Choice Event Model	Choice Event Model Name (String), Choice Name (String), Choice Event (String)	None	Used by Web Support Feedback informant.	This function is used to store all of the logic needed to set the Choice Models tied to the Choice Groups.
Set Choice Model	Choice Model Name (String), Choice Name (String)	None	Used by Customer Action and Close Session informants.	This function is used to store all of the logic needed to set the Choice Models tied to the Choice Groups.
Set Session Rank Offers	Offers (Array of String)	None	Used by all offer-oriented advisors to set the optionally supplied string array of keys into session for later use as dynamic choice source. See corresponding functions: Get Ad List, Get Promotion List, Get Cross Sell Product List, Get Up Sell Product List.	This procedure is used to parse and set Rank Offers before decision selection.
Years To Now	Start Time (Date)	Years (Integer)	Used by Customer Entity.	This function calculates the number of years from given date to now.