Zendesk Collect Slice

Overview

Zendesk is a customer service software and support ticketing system.

The Datacoral Zendesk slice collects data from a Zendesk API and writes it to S3 and Redshift.

Steps to add this slice to your installation

The steps to launch your slice are:

  1. Generate Zendesk API keys
  2. Generate Zendesk Chats API access token
  3. Specify the slice config
  4. Add the Zendesk slice

1. Generate Zendesk API keys

Setup requirements

Before getting started please make sure to have the following information:

  • Access to an active Zendesk account

Setup instructions

The Zendesk slice requires an auth token to collect data. An auth token can be obtained from Zendesk through the following steps:

  1. Click on gear icon in the left of the Zendesk navigation panel and access "Admin Home"
  2. Navigate to the "CHANNELS" section
  3. Click on "API" and access "Zendesk API".
  4. Enable the "Token Access" option and click on "+" button
  5. Provide an API token description, like "datacoral" and copy the Token
  6. Click on "Save" button

2. Generate Zendesk Chats API access token

Setup instructions

  1. Sign in as an admin to Zendesk Chat.
  2. In the Dashboard, go to Settings > Account, then select the API tab.
  3. Click Add API Client.
  4. Complete the following fields:
  • Client Name - datacoral
  • Company - datacoral.
  • Redirect URLs - http://localhost
  1. Click Create API Client. If the client is successfully created, a dialog appears listing a client ID and a client secret. You'll need both to create an OAuth access token later.
  2. Open in browser: https://www.zopim.com/oauth2/authorizations/new?response_type=token&client_id=<CLIENT_ID>&scope=read&redirect_uri=http%3A%2F%2Flocalhost&subdomain=
  3. Click Allow access, and after redirect, copy access_token from url.

3. Specify the slice config

To get a template for the Zendesk slice configuration save the output of the describe --input-parameters command as follows:

  datacoral collect describe --slice-type zendesk \
  --input-parameters > zendesk_parameters_file.json

Example template:

 {
   "subdomain": "test_subdomain",
   "token": "test_token",
   "user": "test_user",
   "chat_token": ""
 }

Modify the zendesk_parameters_file file to add the token generated from Zendesk

Necessary input parameters:

4. Add the Slice

datacoral collect add --slice-type zendesk --slice-name <slice-name> --parameters-file <params-file>
  • slice-name Name of your slice. A schema with your slice-name is automatically created in your warehouse
  • params-file File path to your input parameters file. Ex. zendesk_parameters_file.json

Supported load units

The Zendesk slice automatically collects the following loadunits from the Zendesk API and makes them available in your warehouse for analysis.

  • calls: this loadunit fetches data for calls data
  • legs: this loadunit fetches data for legs data
  • ticket_audits: this loadunit fetches data for ticket audits
  • groups: this loadunit fetches data for groups
  • group_memberships: this loadunit fetches data for group memberships
  • users: this loadunit fetches data for users
  • user_fields: this loadunit fetches data for user_fields
  • tickets: this loadunit fetches data for tickets
  • ticket_custom_fields: this loadunit fetches data for ticket_custom_fields
  • ticket_events: this loadunit fetches data for ticket events
  • ticket_metric_events: this loadunit fetches data for ticket metric events
  • organizations: this loadunit fetches data for organizations
  • ticket_metrics: this loadunit fetches data for ticket metrics
  • ticket_fields: this loadunit fetches data for ticket fields
  • activities: this loadunit fetches data for ticket activities
  • satisfaction_ratings: this loadunit fetches data for satisfaction ratings
  • sla_policies: this loadunit fetches data for SLA policies
  • phone_numbers: this loadunit fetches data for phone numbers
  • organization_fields: this loadunit fetches data for organization fields
  • organization_memberships: this loadunit fetches data for organization memberships
  • agent_metrics: this loadunit fetches data for agent metrics
  • chats: this loadunit fetch data for all chats
  • chat: this loadunit fetch data for chat
  • chat_agent: this loadunit fetch data for chat agent
  • chat_agents
  • chat_history
  • chat_visitor
  • chat_webpath
  • agents
  • organization_organization_fields
  • ticket_audit_events
  • ticket_event_child_events

Slice output

Output of this slice is stored in S3 and Redshift.

AWS S3 Data stored in AWS S3 is partitioned by date and time s3://customer_installation.datacoral/<slice-name>

AWS Redshift: Schema - schema name will be same as a slice-name. Tables produced by the slice are:

  - schema.calls
  - schema.legs
  - schema.ticket_audits
  - schema.groups
  - schema.group_memberships
  - schema.users
  - schema.user_fields
  - schema.tickets
  - schema.ticket_custom_fields
  - schema.ticket_events
  - schema.ticket_metric_events
  - schema.organizations
  - schema.ticket_metrics
  - schema.ticket_fields
  - schema.activities
  - schema.satisfaction_ratings
  - schema.sla_policies
  - schema.phone_numbers
  - schema.organization_fields
  - schema.organization_memberships
  - schema.agent_metrics
  - schema.chats
  - schema.chat
  - schema.chat_agents
  - schema.chat_agent
  - schema.chat_history
  - schema.chat_visitor
  - schema.chat_webpath
  - schema.agents
  - schema.organization_organization_fields
  - schema.ticket_audit_events
  - schema.ticket_event_child_events

Questions? Interested?

If you have questions or feedback, feel free to reach out at hello@datacoral.co or Request a demo

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