Genesys Cloud - Main

Hi everyone,

I wanted to share a utility I recently built while working on contact center analytics and Architect-driven workflows, specifically around extracting participant data set within flows.

The Problem:

In many real-world implementations, we rely heavily on Set Participant Data in Architect to store:

- CRM context (e.g., Salesforce URL pop / IDs)

- Routing decisions and metadata

- Authentication context

- Bot / IVR interaction signals

However, analyzing this data for a specific queue over time is not straightforward:

- Standard reports don't expose participant attributes cleanly

- Conversation structure (participants → sessions → segments) makes extraction tricky

- Transfers and multiple queue segments create duplication challenges

- Async analytics APIs require orchestration

Solution:

I created an interactive Python tool that leverages the Analytics Conversation Detail Jobs API to extract participant data in a structured and usable way.

What the Tool Does:

- Filters conversations by Queue ID

- Extracts a specific Participant Data attribute

- Supports auto-discovery of attribute names

- Handles async job creation and polling

- Flattens complex conversation structures

- Exports results into an Excel workbook

Key Features:

- Interactive CLI

- Queue validation (displays queue name)

- Attribute discovery

- Handles multi-segment conversations

- Deduplicated and detailed outputs

- Region-aware

Output:

The Excel file contains:

- Results_Unique: One row per conversation ID + attribute value

- Results_Detailed: Full breakdown (participants, sessions, segments)

- Metadata: Query and job details

Permissions Required:

- Analytics > Conversation Detail > View

- Analytics > Data Export > All

- Reporting > CustomParticipantAttributes > View

GitHub:

Repository Link

Use Cases:

- Debugging Architect flows

- Extracting CRM context

- Auditing routing decisions

- IVR/Bot analytics

- Building analytics datasets

Would love feedback:

- Any improvements?

- Other approaches?

- Interest in UI version?

Thanks!

Hi everyone,

I wanted to share a utility I recently built while working on contact center analytics and Architect-driven workflows, specifically around extracting participant data set within flows.

The Problem:

In many real-world implementations, we rely heavily on Set Participant Data in Architect to store:

- CRM context (e.g., Salesforce URL pop / IDs)

- Routing decisions and metadata

- Authentication context

- Bot / IVR interaction signals

However, analyzing this data for a specific queue over time is not straightforward:

- Standard reports don't expose participant attributes cleanly

- Conversation structure (participants → sessions → segments) makes extraction tricky

- Transfers and multiple queue segments create duplication challenges

- Async analytics APIs require orchestration

Solution:

I created an interactive Python tool that leverages the Analytics Conversation Detail Jobs API to extract participant data in a structured and usable way.

What the Tool Does:

- Filters conversations by Queue ID

- Extracts a specific Participant Data attribute

- Supports auto-discovery of attribute names

- Handles async job creation and polling

- Flattens complex conversation structures

- Exports results into an Excel workbook

Key Features:

- Interactive CLI

- Queue validation (displays queue name)

- Attribute discovery

- Handles multi-segment conversations

- Deduplicated and detailed outputs

- Region-aware

Output:

The Excel file contains:

- Results_Unique: One row per conversation ID + attribute value

- Results_Detailed: Full breakdown (participants, sessions, segments)

- Metadata: Query and job details

Permissions Required:

- Analytics > Conversation Detail > View

- Analytics > Data Export > All

- Reporting > CustomParticipantAttributes > View

GitHub:

Repository Link

Use Cases:

- Debugging Architect flows

- Extracting CRM context

- Auditing routing decisions

- IVR/Bot analytics

- Building analytics datasets

Would love feedback:

- Any improvements?

- Other approaches?

- Interest in UI version?

Thanks!

#Reporting/Analytics

------------------------------
Vipin Kalra
Lead Engineer
------------------------------

Hi everyone,

I wanted to share a utility I recently built while working on contact center analytics and Architect-driven workflows, specifically around extracting participant data set within flows.

The Problem:

In many real-world implementations, we rely heavily on Set Participant Data in Architect to store:

- CRM context (e.g., Salesforce URL pop / IDs)

- Routing decisions and metadata

- Authentication context

- Bot / IVR interaction signals

However, analyzing this data for a specific queue over time is not straightforward:

- Standard reports don't expose participant attributes cleanly

- Conversation structure (participants → sessions → segments) makes extraction tricky

- Transfers and multiple queue segments create duplication challenges

- Async analytics APIs require orchestration

Solution:

I created an interactive Python tool that leverages the Analytics Conversation Detail Jobs API to extract participant data in a structured and usable way.

What the Tool Does:

- Filters conversations by Queue ID

- Extracts a specific Participant Data attribute

- Supports auto-discovery of attribute names

- Handles async job creation and polling

- Flattens complex conversation structures

- Exports results into an Excel workbook

Key Features:

- Interactive CLI

- Queue validation (displays queue name)

- Attribute discovery

- Handles multi-segment conversations

- Deduplicated and detailed outputs

- Region-aware

Output:

The Excel file contains:

- Results_Unique: One row per conversation ID + attribute value

- Results_Detailed: Full breakdown (participants, sessions, segments)

- Metadata: Query and job details

Permissions Required:

- Analytics > Conversation Detail > View

- Analytics > Data Export > All

- Reporting > CustomParticipantAttributes > View

GitHub:

Repository Link

Use Cases:

- Debugging Architect flows

- Extracting CRM context

- Auditing routing decisions

- IVR/Bot analytics

- Building analytics datasets

Would love feedback:

- Any improvements?

- Other approaches?

- Interest in UI version?

Thanks!

Hi everyone,

I wanted to share a utility I recently built while working on contact center analytics and Architect-driven workflows, specifically around extracting participant data set within flows.

The Problem:

In many real-world implementations, we rely heavily on Set Participant Data in Architect to store:

- CRM context (e.g., Salesforce URL pop / IDs)

- Routing decisions and metadata

- Authentication context

- Bot / IVR interaction signals

However, analyzing this data for a specific queue over time is not straightforward:

- Standard reports don't expose participant attributes cleanly

- Conversation structure (participants → sessions → segments) makes extraction tricky

- Transfers and multiple queue segments create duplication challenges

- Async analytics APIs require orchestration

Solution:

I created an interactive Python tool that leverages the Analytics Conversation Detail Jobs API to extract participant data in a structured and usable way.

What the Tool Does:

- Filters conversations by Queue ID

- Extracts a specific Participant Data attribute

- Supports auto-discovery of attribute names

- Handles async job creation and polling

- Flattens complex conversation structures

- Exports results into an Excel workbook

Key Features:

- Interactive CLI

- Queue validation (displays queue name)

- Attribute discovery

- Handles multi-segment conversations

- Deduplicated and detailed outputs

- Region-aware

Output:

The Excel file contains:

- Results_Unique: One row per conversation ID + attribute value

- Results_Detailed: Full breakdown (participants, sessions, segments)

- Metadata: Query and job details

Permissions Required:

- Analytics > Conversation Detail > View

- Analytics > Data Export > All

- Reporting > CustomParticipantAttributes > View

GitHub:

Repository Link

Use Cases:

- Debugging Architect flows

- Extracting CRM context

- Auditing routing decisions

- IVR/Bot analytics

- Building analytics datasets

Would love feedback:

- Any improvements?

- Other approaches?

- Interest in UI version?

Thanks!

Hi everyone,

I wanted to share a utility I recently built while working on contact center analytics and Architect-driven workflows, specifically around extracting participant data set within flows.

The Problem:

In many real-world implementations, we rely heavily on Set Participant Data in Architect to store:

- CRM context (e.g., Salesforce URL pop / IDs)

- Routing decisions and metadata

- Authentication context

- Bot / IVR interaction signals

However, analyzing this data for a specific queue over time is not straightforward:

- Standard reports don't expose participant attributes cleanly

- Conversation structure (participants → sessions → segments) makes extraction tricky

- Transfers and multiple queue segments create duplication challenges

- Async analytics APIs require orchestration

Solution:

I created an interactive Python tool that leverages the Analytics Conversation Detail Jobs API to extract participant data in a structured and usable way.

What the Tool Does:

- Filters conversations by Queue ID

- Extracts a specific Participant Data attribute

- Supports auto-discovery of attribute names

- Handles async job creation and polling

- Flattens complex conversation structures

- Exports results into an Excel workbook

Key Features:

- Interactive CLI

- Queue validation (displays queue name)

- Attribute discovery

- Handles multi-segment conversations

- Deduplicated and detailed outputs

- Region-aware

Output:

The Excel file contains:

- Results_Unique: One row per conversation ID + attribute value

- Results_Detailed: Full breakdown (participants, sessions, segments)

- Metadata: Query and job details

Permissions Required:

- Analytics > Conversation Detail > View

- Analytics > Data Export > All

- Reporting > CustomParticipantAttributes > View

GitHub:

Repository Link

Use Cases:

- Debugging Architect flows

- Extracting CRM context

- Auditing routing decisions

- IVR/Bot analytics

- Building analytics datasets

Would love feedback:

- Any improvements?

- Other approaches?

- Interest in UI version?

Thanks!