Reporting in Gladly gives you comprehensive visibility into your customer service operations, from real-time performance monitoring to deep analytical insights.
This guide covers what you need to know about accessing and using reporting in Gladly, including out-of-the-box reports, API data access, and the powerful Insight Builder tool for custom reporting.
Gladly's Data Structure
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Gladly's data model centers around key entities that connect to provide a complete picture of your customer interactions. Explore each in the tabs below:
The individual reaching out to your team. Each customer has a unified profile that tracks their entire history with your organization.
A complete interaction with a customer, which may span multiple contacts. Conversations have attributes like:
Created at date
Closed at date
Topic
Sidekick (Gladly's AI summary)
Individual touchpoints within a conversation, such as a phone call, email, or chat message. Each contact has data timestamps for when it was:
Queued
Fulfilled
Ended
Time periods when agents are actively working on contacts. Work sessions track metrics such as:
Agent
Inbox
Handle Time
Work items that can be created and tracked, like follow-ups or internal to-dos. Tasks have attributes including:
Creation at date
Assigned agent
Inbox
Due date
Building Blocks
When creating reports in Gladly, you'll work with three fundamental concepts:
Datasets
Datasets determine what type of information you're analyzing. Each dataset is tied to a specific entity in Gladly's data model:
Conversations (identified by unique ID): Report on conversation-level metrics and attributes
Contacts (identified by unique ID): Analyze individual customer touch-points
Work Sessions: Track agent productivity and time allocation
Agents (identified by unique ID): View agent-specific performance
Tasks (identified by unique ID): Monitor task creation, assignment, and completion
Sidekick: Leverage AI-generated conversation summaries in your reporting
Time Anchors
Time anchors determine which timestamp is used to include data in your report. Different entities have different relevant timestamps:
Conversations: created, updated, closed
Contacts: queued, fulfilled, ended
Agents: timestamp of activity taking place
Tasks: created, updated, closed
Accurate Time Anchors for accurate data
Choosing the right time anchor is critical for accurate reporting. For example, if you want to see how many conversations were resolved last week, you'd use "Conversations" as your dataset with "closed" as the time anchor.
Report Types
Gladly offers three types of reports to serve different analytical needs:
Summary: Aggregated data showing totals, averages, and other calculated metrics across your selected time period
Export: Detailed record-by-record data that can be exported for deeper analysis in external tools
Events: Granular timestamp-based data showing when specific actions occurred
Data Sources
Gladly provides three main pathways for accessing your reporting data, each designed for different use cases and technical requirements.
Out-of-the-Box Reports and Liveboards
UI sources are best for:
Teams who need little to no customization, quick insights, coaching support, real-time monitoring, contact center performance tracking, and manual one-off analysis.
Out-of-the-Box (OOTB) Reports
Gladly's user interface includes pre-built reports that cover the most common customer service metrics. These reports are ready to use immediately and require no configuration.
Key capabilities:
Access standard agent, contact, conversation, answer, and payment reports
Schedule reports to run automatically and receive them via email
Download data as CSV files for offline analysis
View historical trends and performance patterns
Example OOTB Reports:
Agent performance metrics (Away Time, Durations, Login Time, Summary, Timestamps)
Contact center metrics (First Contact Resolution by Agent)
Work session tracking
Liveboards: Real-Time Performance Monitoring
Liveboards complement traditional reporting by providing a live view of your team's current performance. While reports are designed for analyzing trends and historical data over time, Liveboards give you an at-a-glance reference to monitor operations throughout the day and ensure things are running smoothly.
Use Liveboards for:
Monitoring current queue depths and wait times
Tracking agent availability in real-time
Viewing today's key metrics as they update
Quick status checks without generating full reports
OOTB Dashboards
In addition to individual reports, Gladly provides pre-configured dashboards that combine multiple related reports into a single view for holistic performance monitoring.
API Sources
API sources are best for:
Integrations with external systems, workforce management providers, RTA (Real-Time Analytics) tools, data warehouses, event-based alerting and monitoring, and custom actions triggered by data (e.g., automatically closing conversations matching specific criteria).
Gladly's API provides programmatic access to your data for advanced integration scenarios. If you need to feed Gladly data into your organization's data warehouse, trigger automated workflows, or build custom analytics platforms, the API gives you the flexibility to extract and work with raw data.
Common use cases:
Syncing Gladly data with your data warehouse (Snowflake, BigQuery, etc.)
Building custom dashboards in BI tools (Tableau, Looker, Power BI)
Integrating with workforce management platforms
Creating automated alerts based on performance thresholds
Combining Gladly data with other business data sources for cross-platform analysis
Insight Builder
Insight Builder sources are best for:
Creating custom reports and dashboards tailored to your business operations, combining multiple datasets into unified views, and building scheduled reports with specific metrics and visualizations.
How Insight Builder Works
Insight Builder uses a step-by-step process to help you create custom reports:
Step 1: Choose a Base Dataset
Start by selecting which entity you want to report on. Your options include:
Events: Granular timestamp data (e.g., Agent X closed Conversation Y on DATE)
Metrics: Rolled-up aggregated data (e.g., Agent X accrued N minutes of Handle Time from DATE to DATE)
Agents: Agent-specific information (e.g., logged in status)
Contact: Individual interaction data (e.g., handle time for a specific contact)
Conversation: Conversation-level data (e.g., average number of contacts)
Task: Task tracking data (e.g., number of tasks created in an inbox)
Step 2: Choose Filters
Narrow your data to focus on what matters most. You can filter by:
Date Range: Select your reporting period (pay close attention to anchoring - which timestamp determines inclusion)
Any Dimension: Filter by agent, inbox, topic, channel, custom fields, or any other available dimension
Step 3: Choose Data
Select the specific information you want to include in your report:
Dimensions: Individual attributes that provide context (e.g., a single conversation's handle time, assigned agent ID, inbox name)
Measures: Aggregated calculations (e.g., count of conversations, sum of handle time, averages)
Custom Fields: Create your own dimensions or measures using conditional logic (e.g., if a conversation was created in Inbox A, B, or C, categorize it as "Team A", otherwise "Team B")
Step 4: Choose Visualization
Present your data in the format that best communicates your insights:
Bar graphs for comparisons
Line charts for trends over time
Tables for detailed data views
Custom color schemes to match your brand or highlight key information
Step 5: Save to a Dashboard
Organize your reports by saving them to dashboards:
Personal folders: Private dashboards visible only to you
Group folders: Shared dashboards that other team members can access