Connector Database / Kustomer
Analyze your Kustomer data with AI
Build interactive dashboards, generate automated reports, and unlock business intelligence insights from your Kustomer data with AI-powered assistant.
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Start with a question
Generate automated reports and business intelligence insights from your Kustomer data—as fast as you can ask them.
Build dashboards and data visualizations
Transform your conversation into dynamic data visualizations on an intuitive data canvas.
Integrate all your data
Unify your Kustomer data with DuckDB-powered data warehouse including Stripe, S3, Attio and Quickbooks.
Available Kustomer Data
Extracts Kustomer customer service CRM data, including customers, companies, conversations (tickets), messages, notes, custom objects (KObjects), attachments, tags, teams, users, shortcuts (macros), SLA policies, and custom field definitions. This enables analysis of customer profiles, support volume and resolution metrics, agent performance and staffing, SLA adherence and policy changes over time, and taxonomy/metadata used to categorize records. Supports both US and EU Kustomer regions.
Customer
Represents individual end users/contacts with profiles and history; enables segmentation, cohort analysis, and understanding of support demand and satisfaction by customer attributes.
Company
Represents organizations/accounts linked to customers; supports account-level analysis of support volume, health, SLA adherence, and escalations across related conversations.
Conversation (Ticket)
Represents a support case from creation to resolution; enables metrics like case volume, backlog, first response and resolution times, and SLA compliance by channel, team, or tag.
Message
Individual inbound/outbound communications within conversations across channels; supports response-time calculations, message counts per ticket, channel mix, and agent workload analysis.
Note
Internal agent notes attached to customers or conversations; used to analyze collaboration, handoffs, and case context for quality reviews.
Custom Object (KObject)
User-defined objects linked to customers or conversations; enables domain-specific KPI modeling and joins beyond the standard schema.
Attachment
Files associated with conversations (images, documents); supports analysis of attachment prevalence, types, and compliance considerations.
SLA Policy
Current and historical SLA configurations; used to measure adherence and breaches and to analyze the impact of policy changes on responsiveness and resolution performance.
Tag
Taxonomy used to categorize customers and conversations; enables segmentation, routing analysis, and topic/issue trend reporting.
Team
Support teams and their structures; enables workload distribution, queue performance, staffing capacity, and cross-team comparisons.
Agent (User)
Support agents with roles and profiles; supports KPIs such as first response time, resolutions handled, productivity, and utilization.
Shortcut (Macro)
Agent-created canned responses and automations; enables analysis of macro adoption, standardization, and time saved across teams or channels.
Authentication Required
Uses an API key from your Kustomer account sent as a Bearer token
Getting started with
Kustomer Analytics & Business Intelligence
Connect your Kustomer data
Connect to Kustomer once and automatically sync data to your centralized data warehouse for real-time reporting and analytics.
Build business intelligence models
Create automated reports, dashboards, and data visualizations with customizable business logic and AI-powered insights for consistent analytics across your organization.
Generate reports and insights
Create interactive dashboards, automated reports, and data visualizations with AI-powered business intelligence. Share live analytics and scheduled reporting with your team.
Want to see how easy it is to get started?
Kustomer usersDefinite
People love Definite because it lets you focus on what matters. Setting up your own data infrastructure doesn't make your beer taste better. Skip the tedium and start at analytics.
I was leading the efforts of setting up a business intelligence function. I was surprised how complex this all was to do even today. It's something that every tech company would need at some point but it hasn't been simplified. You need a whole team focused on building a data warehouse, setting up the right pipelines, and then integrating a BI tool on top.Definite wasn't only the answer to this problem, it tackled the next problem I knew I'd have as soon as the BI tool was ready — how do we get non-technical teams and people to learn and utilise such a tool.
Our analytics before Definite consisted of dozens of Excel sheets that took hours to update. Manual updates led to errors. Everyone questioned the accuracy of the numbers. Many people just stopped looking at the reports.After Definite, everything ran like clockwork.We immediately saved thousands of dollars per month in the time spent updating reports and have built strategies (e.g. improved ROI on ad spend, inventory management, etc.) on the data that will yield millions to our bottom line.
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