Freshdesk

Analyze support tickets, agent performance, and customer satisfaction

Connect Freshdesk to Scoop to analyze your customer support operations, track ticket trends, monitor SLA compliance, and measure agent performance.

AI-Assisted Setup

When connecting Freshdesk to Scoop, choose "Guide me with AI" for an intelligent, guided setup experience.

Available Analysis Templates

TemplateObjectData ModeBest ForWhat You'll Analyze
Ticket Volume & Status (Default)ticketsSnapshotSupport operationsVolume trends, status distribution, SLA compliance
Agent Workload & AssignmentagentsSyncTeam managementAgent availability, workload distribution
Customer CompaniescompaniesSyncAccount analysisSupport patterns by customer organization
Customer ContactscontactsSyncCustomer trackingContact database, support history
Support Team GroupsgroupsSyncTeam structureTeam organization, escalation paths

Example Questions You Can Answer

Ticket Analysis:

  • "How many tickets were created this week by priority?"
  • "What's our ticket resolution rate?"
  • "Which channels generate the most tickets (email, phone, chat)?"
  • "How many tickets are overdue on their SLA?"
  • "What's the distribution of Open vs Pending vs Resolved tickets?"

Agent Performance:

  • "Which agents handle the most tickets?"
  • "What's the average resolution time by agent?"
  • "How many tickets are unassigned right now?"
  • "Which group has the highest ticket load?"
  • "How does ticket assignment vary by priority?"

Customer Insights:

  • "Which companies submit the most support tickets?"
  • "What's the ticket volume by customer industry?"
  • "Which account tiers have the longest resolution times?"
  • "How does ticket priority vary by company?"

SLA Compliance:

  • "What percentage of tickets meet first response SLA?"
  • "How many tickets are at risk of breaching SLA?"
  • "Which priorities have the worst SLA compliance?"
  • "What's our SLA performance trend over time?"

Need Something Different?

If the templates above don't match your needs, select "Something else" and describe what you want to analyze. For example:

  • "I want to track escalation rates by team"
  • "I need to see first response times by channel"
  • "I want to analyze ticket tags for common issues"

Scoop's AI will recommend the right configuration for your specific use case.

Snapshotting for Ticket Analysis

Tickets change over time - status updates, assignments change, resolutions happen. Configure your Tickets extract as a Snapshot dataset to:

  • Track how tickets progress through statuses
  • Monitor SLA compliance over time
  • Analyze backlog growth and reduction
  • Compare ticket snapshots day-over-day or week-over-week

Pro Tip: Enable snapshotting on day one for tickets. Support teams need historical data to track resolution patterns and identify bottlenecks in their workflow.

Connecting Freshdesk to Scoop

  1. Create a new dataset in Scoop
  2. Select Freshdesk from the application list
  3. Enter your Freshdesk subdomain (e.g., yourcompany from yourcompany.freshdesk.com)
  4. Enter your API Key (found in Profile Settings > Your API Key)
  5. Choose your analysis template or customize
  6. Save and extract data

What Data You Get

Tickets (19 fields)

Support requests with status, priority, and assignment information.

FieldDescription
Ticket IDUnique identifier (prefixed with FD)
SubjectTicket subject line
DescriptionTicket body text
StatusOpen, Pending, Resolved, or Closed
PriorityLow, Medium, High, or Urgent
TypeTicket category
SourceChannel: 1=Email, 2=Portal, 3=Phone, 7=Chat, 9=Feedback Widget, 10=Outbound Email
Requester IDCustomer who opened the ticket
Responder IDAgent assigned to ticket
Group IDTeam/department assigned
Company IDCustomer's organization
Created DateWhen ticket was opened
Updated DateWhen ticket was last modified
Due DateSLA resolution deadline
First Response DueFirst response SLA deadline
Is EscalatedWhether ticket has been escalated
TagsTicket labels
Is SpamWhether ticket is marked as spam
CC EmailsAdditional email recipients

Contacts (13 fields)

Customers who submit support requests.

FieldDescription
Contact IDUnique identifier
NameCustomer name
EmailContact email
PhonePhone number
MobileMobile phone number
Company IDAssociated company
Created DateWhen contact was created
Updated DateWhen contact was last modified
ActiveWhether contact is active
Job TitleCustomer's role
LanguagePreferred language
Time ZoneContact's time zone
TagsContact labels

Companies (11 fields)

Customer organizations.

FieldDescription
Company IDUnique identifier
NameCompany name
DescriptionCompany description
DomainsEmail domains associated with company
Created DateWhen company was created
Updated DateWhen company was last modified
NotesAdditional notes about the company
Health ScoreCustomer health indicator
Account TierService level tier
Renewal DateContract renewal date
IndustryBusiness industry

Agents (10 fields)

Support staff who handle tickets.

FieldDescription
Agent IDUnique identifier
NameAgent's full name
EmailAgent email
Ticket ScopeAccess level: 1=Global, 2=Group, 3=Restricted
AvailableCurrent availability status
Occasional AgentWhether agent is part-time/occasional
Created DateWhen agent was created
Updated DateWhen agent was last modified
Group IDsTeams agent belongs to
Role IDsRoles assigned to agent

Groups (9 fields)

Support teams and departments.

FieldDescription
Group IDUnique identifier
NameTeam name
DescriptionTeam description
Created DateWhen group was created
Updated DateWhen group was last modified
Escalate To GroupEscalation target group
Unassigned DurationHow long tickets can be unassigned
Agent IDsAgents in this group
Auto AssignWhether tickets auto-assign to this group

Analysis Examples

Ticket Volume Trends

Track daily, weekly, or monthly ticket volume with breakdowns by:

  • Status (Open, Pending, Resolved, Closed)
  • Priority (Low, Medium, High, Urgent)
  • Channel (Email, Phone, Chat, Portal)
  • Group/team

SLA Performance

Monitor service level compliance:

  • First response SLA adherence
  • Resolution SLA adherence
  • At-risk tickets approaching SLA breach
  • SLA trends over time

Agent Productivity

Analyze support team performance:

  • Tickets handled per agent
  • Resolution time by agent
  • Workload distribution across team
  • Escalation patterns

Customer Support Patterns

Understand customer needs:

  • Tickets by company
  • Support volume by account tier
  • Priority distribution by customer
  • Industry-specific ticket patterns

Best Practices

  • Start with Tickets: The tickets object contains the core support metrics
  • Enable Snapshotting: Track ticket lifecycle and SLA compliance over time
  • Combine with Companies: Blend tickets + companies for customer-centric analysis
  • Use Tags: Freshdesk tags help categorize issues for root cause analysis

Troubleshooting

Connection Issues

  • Verify your subdomain is correct (just the prefix, not full URL)
  • Check that your API key is valid (regenerate if needed)
  • Ensure your Freshdesk account has API access enabled

Missing Data

  • Only tickets you have permission to view are included
  • Historical tickets may require pagination for large volumes
  • Some fields require specific Freshdesk plan features