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Jdruker/GCXI UserData

Genesys CX Insights

Genesys Customer Experience Insights (Genesys CX Insights or sometimes GCXI) provides a presentation layer that extracts data from the Genesys Info Mart database, and presents it in readable historical reports to enable business and contact center managers to make better business decisions for streamlining operations, reducing costs, and providing better services.

Genesys CX Insights has replaced Genesys Interactive Insights (GI2) as the historical reporting presentation layer. See also Genesys Info Mart and Reporting and Analytics Aggregates (RAA).



Glossary

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Using Attached Data

Use the information on this page to customize the GCXI projects and reports, to provide results that are organized based on your own business’s user data.

Configuring Social Media User Data

The Social Engagement Report relies on how user data is configured in your environment, and on the strategies you use to route interactions. This section describes how to set up your environment to report on social media user data. The Social Engagement Report and the objects that directly support it are described on the Agent Social Engagement Report page. Perform the following steps to configure social media user data:

  1. Review the routing strategies in your environment with respect to user data and update them as appropriate. .Note that, while Genesys Info Mart provides for including the Revenue and Satisfaction KVPs in reporting by default, the actual KVPs are not defined by default in the Genesys configuration and therefore are not included in Genesys-provided routing strategies.
    The default Genesys-provided routing strategies do not set the Sent reason when responses are sent. You must design your strategy to change the StopProcessing reason from Normal to Sent when this event occurs. If you do not do so, the GCXI third-party media reports generate results for transfers only—not for responses.
  2. In the attached-data specification file* that controls which user data KVPs Interaction Concentrator (ICON) stores, ensure that the following keys are specified.
    • Classify_Actionability_CtgRelevancy
    • Classify_Sentiment_CtgRelevancy
    • KloutScore
    • CtgName
    • Screen_Sentiment_CtgName
    • Screen_Actionability_CtgName
    • Classify_Actionability_CtgName
    • Classify_Sentiment_CtgName
    • desktop_influence
    *The Genesys Info Mart installation package includes a sample attached-data specification file, ccon_adata_spec_GIM_example.xml, in which the required social media KVPs are listed, but commented out. If you base your ICON attached-data specification file on ccon_adata_spec_GIM_example.xml, uncomment the appropriate rows to enable ICON to record the required data.
    Place this file in ICON’s root directory. Refer to Steps 1 and 2 of Enabling Reporting on User Data in the Genesys Info Mart Deployment Guide for detailed instructions.
  3. Run make_gim_UDE_template_<rdbms>.sql against the Info Mart database to create the database objects for social media detail reporting. This SQL script is deployed in the \script subfolder as part of a GCXI installation. Refer to the Application Files chapter of the Reporting and Analytics Aggregates Deployment Guide for more information.
    Are we missing anything here? Does make_gim_UDE_template_<rdbms>.sql need to be edited before it is run? Jose points out that: The file on RAA Git has the following comment where the USER_DATA_GEN_ES table is defined: --Only 5 columns per dimension is allowed --Use either 2 Screen categories (Screen_Sentiment_CtgName, Screen_Actionability_CtgName) or 2 Classify categories and comment other 2 out
  4. Run aggregation in autonomous mode and specify the setFeature runtime parameter as follows:
    -setFeature=eServicesSM
    This parameter enables RAA to aggregate social media data, including mapping GEN_ES_KEY (in the IRF_USER_DATA_KEYS table) to USER_DATA_KEY1 in the H_ID, H_AGENT, and H_AGENT_QUEUE hierarchies.
    Note that USER_DATA_KEY1 can be mapped only once per hierarchy. If you previously mapped this field to CUSTOM_KEY_10 (as instructed in step 2 of Example - Custom Handling Attempt Report) for the Product Line example, then consider mapping USER_DATA_KEY2 to CUSTOM_KEY_10 instead.

Refer to the Reporting and Analytics Aggregates User’s Guide to learn how to run aggregation in this autonomous mode.

Your environment is ready to process social media user data for each interaction, and RAA is equipped to aggregate this data. You can now use the Agent Social Engagement and Social Engagement reports to retrieve meaningful data.

Configuring Custom User Data

This procedure is newly added. If it is correct, should it rather go on How Do I Configure User Data for Aggregation in the RAA UG?

This section describes the steps required to configure custom user data, and is applicable to attached data; it's not possible to use UserEvent user data. Perform the following steps to configure custom user data:

  1. Review the business attributes and routing strategies in your environment and update them as appropriate to attach the custom user data you require.
    [Question] Confirm that the KVPs don't have to use GIM's placeholder names (e.g., CustomAttribute1).
  2. In the attached-data specification file that controls which user data KVPs Interaction Concentrator (ICON) stores, ensure that your custom keys are specified.
    The Genesys Info Mart installation package includes a sample attached-data specification file, ccon_adata_spec_GIM_example.xml, in which placeholder custom KVPs are listed. CustomAttribute* are the placeholder names for low-cardinality KVPs, which will be mapped to custom dimension tables.
    Place the attached-data specification file in ICON’s root directory. Refer to Steps 1 and 2 of Enabling Reporting on User Data in the Genesys Info Mart Deployment Guide for detailed instructions.
  3. Modify the user data mapping file, user-data-map.ss, as described on How Do I Configure User Data for Aggregation?. Save it to the Genesys Info Mart root folder.
    No further action is required to complete the mapping of the custom KVPs through the IRF_USER_DATA_KEYS and USER_DATA_CUST_DIM_* tables or to create the tables in the Info Mart database.
    [Question] See the question below arising from the mapping of GEN_ES_KEY to a GCXI schema object. There is no mapping conflict on the GIM side, but do we need to warn about not using USER_DATA_CUST_DIM_1 in deployments with social media because of a mapping conflict on the GCXI side?

User Data Objects in Project

This section describes additional objects, some of which indirectly support social media user data reporting. Key objects that are related to user data are listed in the Predefined User Data Objects table.

Object Type and Name (M=Metric, A = Attribute/Dimension) User Data Table and Field Char or Numeric
Predefined User Data Objects
Agent\Activity

M Actionability AG2_AGENT_*.ACTIONABILITY

AG2_AGENT_GRP_*.ACTIONABILITY

AG2_AGENT_QUEUE_*.ACTIONABILITY

Numeric
M Influence Score AG2_AGENT_*.INFLUENCE

AG2_AGENT_GRP_*.INFLUENCE

AG2_AGENT_QUEUE_*.INFLUENCE

Numeric
M Offered with Actionability AG2_AGENT_*.ACTIONABILITY_OFFERED

AG2_AGENT_GRP_*.

          ACTIONABILITY_OFFERED

AG2_AGENT_QUEUE_*.

          ACTIONABILITY_OFFERED

Numeric
M Offered with Influence AG2_AGENT_*.INFLUENCE_OFFERED

AG2_AGENT_GRP_*.INFLUENCE_OFFERED

AG2_AGENT_QUEUE_*.INFLUENCE_OFFERED

Numeric
M Offered with Sentiment AG2_AGENT_*.SENTIMENT_OFFERED

AG2_AGENT_GRP_*.SENTIMENT_OFFERED

AG2_AGENT_QUEUE_*.SENTIMENT_OFFERED

Numeric
M SentimentScore AG2_AGENT_*.SENTIMENT

AG2_AGENT_GRP_*.SENTIMENT

AG2_AGENT_QUEUE_*.SENTIMENT

Numeric
Agent\Activity\Activity User Data Example
A Dimension 1

Dimension 2

...

Dimension 5

USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_1

USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_2


USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_5

Char
A Dimension 6

...

Dimension 10

USER_DATA_CUST_DIM_2.DIM_ATTRIBUTE_1


USER_DATA_CUST_DIM_2.DIM_ATTRIBUTE_5

Char
A Screen Actionability Category USER_DATA_GEN_ES.SCREEN_

    ACTIONABILITY_CTGNAME

Char
A Screen Sentiment Category USER_DATA_GEN_ES.SCREEN_

    SENTIMENT_CTGNAME

Char
Business Attribute\BA Customer
M Actionability Score AG2_ID_*.ACTIONABILITY Numeric
M Entered with Actionability AG2_ID_*.ACTIONABILITY_ENTERED Numeric
M Entered with Influence AG2_ID_*.INFLUENCE_ENTERED Numeric
M Entered with Sentiment AG2_ID_*.SENTIMENT_ENTERED Numeric
M Influence Score AG2_ID_*.INFLUENCE Numeric
M Sentiment Factor a factor of BA User Data Example\Classify Sentiment Category Numeric
M Sentiment Score AG2_ID_*.SENTIMENT Numeric
Business Attribute\BA User Data Example
A Dimension 1

Dimension 2

...

Dimension 5

USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_1

USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_2


USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_5

Char
A Dimension 6

...

Dimension 10

USER_DATA_CUST_DIM_2.DIM_ATTRIBUTE_1


USER_DATA_CUST_DIM_2.DIM_ATTRIBUTE_5

Char
A Screen Actionability Category USER_DATA_GEN_ES.SCREEN_

ACTIONABILITY_CTGNAME

Char
A Screen Sentiment Category USER_DATA_GEN_ES.SCREEN_

SENTIMENT_CTGNAME

Char


Detail\Handling Attempt\Handling User Data Example
A Detail 1

Detail 2

...

Detail 14

Detail 15

Detail 16

IRF_USER_DATA_CUST_1.CUSTOM_DATA_1

IRF_USER_DATA_CUST_1.CUSTOM_DATA_2


IRF_USER_DATA_CUST_1.CUSTOM_DATA_14

IRF_USER_DATA_CUST_1.CUSTOM_DATA_15

IRF_USER_DATA_CUST_1.CUSTOM_DATA_16

Char

Char


Char

Numeric

Numeric

A Dimension 1

Dimension 2

...

Dimension 5

USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_1

USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_2


USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_5

Char
A Dimension 6

...

Dimension 10

USER_DATA_CUST_DIM_2.DIM_ATTRIBUTE_1


USER_DATA_CUST_DIM_2.DIM_ATTRIBUTE_5

Char
Queue\Queue User Data Example
A Dimension 1

Dimension 2

...

Dimension 5

USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_1

USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_2


USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_5

Char
A Dimension 6

...

Dimension 10

USER_DATA_CUST_DIM_2.DIM_ATTRIBUTE_1


USER_DATA_CUST_DIM_2.DIM_ATTRIBUTE_5

Char
Detail\Transfer\Source User Data Example
A Dimension 1

Dimension 2

...

Dimension 5

USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_1

USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_2


USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_5

Char
A Dimension 6

...

Dimension 10

USER_DATA_CUST_DIM_2.DIM_ATTRIBUTE_1


USER_DATA_CUST_DIM_2.DIM_ATTRIBUTE_5

Char
Detail\Transfer\Target User Data Example
A Dimension 1

Dimension 2

...

Dimension 5

USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_1

USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_2


USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_5

Char
A Dimension 6

...

Dimension 10

USER_DATA_CUST_DIM_2.DIM_ATTRIBUTE_1


USER_DATA_CUST_DIM_2.DIM_ATTRIBUTE_5

Char
Queue\Queue User Data Example
A Dimension 1

Dimension 2

...

Dimension 5

USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_1

USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_2


USER_DATA_CUST_DIM_1.DIM_ATTRIBUTE_5

Char
A Dimension 6

...

Dimension 10

USER_DATA_CUST_DIM_2.DIM_ATTRIBUTE_1


USER_DATA_CUST_DIM_2.DIM_ATTRIBUTE_5

Char

User data key table mapping

[JD note] (a) Previous third column (Dimension table PK name) has been combined with the "GIM Table" column, to save width. (b) Given that some of the apparently custom GIM tables are defined by default and some aren't, I think you need to provide equivalent comments for all the tables. See my suggestions.

The following tables — Low Cardinality — Key table mapping and High Cardinality — Key table mapping — describe the default / recommended mapping for user data tables.

GCXI / Object name Key table mapping Comments
Genesys Info Mart database table name UDE key name <-> IRF_USER_DATA_KEYS GCXI Schema objects
Low Cardinality — Key table mapping
CX Insights\GCXI\Business Attribute \Business Result INTERACTION_DESCRIPTOR

Primary key: INTERACTION_DESCRIPTOR_KEY
Columns:
CUSTOMER_SEGMENT
SERVICE_TYPE
SERVICE_SUBTYPE
BUSINESS_RESULT

INTERACTION_DESCRIPTOR_KEY AG2_xxx.INTERACTION_DESCRIPTOR_KEY The INTERACTION_DESCRIPTOR table is provided with the default schema to store Genesys-defined low-cardinality KVPs, such as service type and customer segment. This table cannot be customized.
CX Insights\GCXI\Business Attribute \Customer Segment
CX Insights\GCXI\Business Attribute \Service Type
CX Insights\GCXI\Business Attribute \Service SubType
CX Insights\GCXI\User Data Example \Dimension 1- Dimension 5 USER_DATA_CUST_DIM_1

Primary key: ID
Columns:
DIM_ATTRIBUTE_1...DIM_ATTRIBUTE_5

CUSTOM_KEY_1 AG2_xxx.USER_DATA_KEY1

[JD note] Given the statements above about GEN_ES_KEY mapping, can you use this table if you're also including social media reporting?

The customizable USER_DATA_CUSTOM_DIM_* tables are not defined by default in the Info Mart schema.
CX Insights\GCXI\User Data Example \Dimension 1- Dimension 5 USER_DATA_CUST_DIM_2

Primary key: ID
Columns:
DIM_ATTRIBUTE_1...DIM_ATTRIBUTE_5

CUSTOM_KEY_2 AG2_xxx.USER_DATA_KEY2
CX Insights\GCXI\User Data Example \GSW Call Type, Dimension 2 Gen – Dimension 5 Gen USER_DATA_GEN_DIM_1

Primary key: ID
Columns:
DIM_ATTRIBUTE_1 (mapped to GSW_CALL_TYPE)
DIM_ATTRIBUTE_2...DIM_ATTRIBUTE_5

USER_DATA_GEN_DIM_KEY_1 AG2_xxx.USER_DATA_GEN_KEY1 The USER_DATA_GEN_DIM_* tables are provided with the default schema to store Genesys- or customer-defined low-cardinality KVPs. The tables themselves cannot be customized.
CX Insights\GCXI\User Data Example \ Dimension 6 Gen – Dimension 10 Gen USER_DATA_GEN_DIM_2

Primary key: ID
Columns:
DIM_ATTRIBUTE_1...DIM_ATTRIBUTE_5

USER_DATA_GEN_DIM_KEY_2 AG2_xxx.USER_DATA_GEN_KEY2 The USER_DATA_GEN_DIM_* tables are provided with the default schema to store Genesys- or customer-defined low-cardinality KVPs. The tables themselves cannot be customized.

[JD note] Previous third column (UDE key name <-> IRF_USER_DATA_KEYS) has been removed. "High cardinality" = facts. Custom UD fact data is not mapped through IRF_USER_DATA_KEYS.

GCXI / Object name Key table mapping Comments
Genesys Info Mart database GCXI Schema objects
Genesys Info Mart database Table name Dimension table PK Column name
High Cardinality — Key table mapping
CX Insights\GCXI\Detail\Handling Attempt\Handling User Data Example \Detail 1 – Detail 16 IRF_USER_DATA_CUST_1 CUSTOM_DATA_[1-16] IRF_USER_DATA_CUST_1.CUSTOM_DATA_[1-16] The customizable IRF_USER_DATA_CUST_1 table is not defined by default in the Info Mart schema.
CX Insights\GCXI\Detail\Handling Attempt \Case ID IRF_USER_DATA_GEN_1 CASE_ID IRF_USER_DATA_GEN_1.CASE_ID The IRF_USER_DATA_GEN_1 table is provided with the default schema to store predefined high-cardinality KVPs, such as customer ID. This table requires no customization.
CX Insights\GCXI\Detail\Handling Attempt \Customer_ID IRF_USER_DATA_GEN_1 CUSTOMER_ID IRF_USER_DATA_GEN_1.CUSTOMER_ID
CX Insights\GCXI\Detail\Handling Attempt \Revenue IRF_USER_DATA_GEN_1 REVENUE IRF_USER_DATA_GEN_1.REVENUE
CX Insights\GCXI\Detail\Handling Attempt \Satisfaction IRF_USER_DATA_GEN_1 SATISFACTION IRF_USER_DATA_GEN_1.SATISFACTION

Using the Predefined User Data Objects

If the user data that you configured within your environment exactly matches the sample tables that have been imported into the Project—as well as their structure—all you have to do to use the predefined user data objects in custom reports is make visible the corresponding objects, and save the project. The objects will be revealed to report designers and can be used in reports. If, however, your user data configuration employs different tables or table structure, perform the following steps:

  1. If necessary, add the appropriate user data table(s) to the GCXI schema. (See step 4 of Example - Custom Handling Attempt Report.)
  2. Alter user data object definitions if you want. For example::
    • Fields in the IRF_USER_DATA_CUST_* tables could be numeric or character.
    • If your user data table is named differently from that which is used in the table above.
    • If you want the attribute to reference a field different from that which is already defined for the object.
    • If you want to have the attribute available as a user prompt on a custom report. (See step 5 of Example - Custom Handling Attempt Report)
    • If you want to rename the predefined folders, attributes, or metrics.
  3. Save the project.

Special Note about Numeric User Data

The Customer Perspective Report includes four measures that are based on numeric user data—Revenue, Satisfaction, Avg Revenue, and Avg Satisfaction. Running aggregation (to populate the data for this report) will yield errors if users are permitted to attach non-numeric data for these business attributes to interactions. You must ensure that the resources that set the values of Revenue and Satisfaction user data keys are configured or trained, as applicable, to record numerical values only. Refer to Check for Incorrect Data Type in the Reporting and Analytics Aggregates User’s Guide to learn how to recover from this situation.

In addition to the information on this page, see:

This page was last edited on August 12, 2020, at 19:31.
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