Connector Database / Help Scout
Analyze your Help Scout data with AI
Build interactive dashboards, generate automated reports, and unlock business intelligence insights from your Help Scout data with AI-powered assistant.
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Start with a question
Generate automated reports and business intelligence insights from your Help Scout 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 Help Scout data with DuckDB-powered data warehouse including Stripe, MongoDB, HubSpot and Google Sheets.
Available Help Scout Data
Extracts Help Scout Mailbox data including conversations (support tickets), message threads, customers, users (agents), teams and members, mailboxes with folders and custom fields, workflows, and customer satisfaction (Happiness) ratings. Enables analysis of support volume and trends, agent and team performance, mailbox organization, automation rules, and CSAT over time.
Conversation
Support tickets across mailboxes with status, assignee, and timestamps; enables analysis of ticket volume, backlog and status trends, SLA compliance (first response and resolution time), and routing by mailbox or custom fields.
Thread/Message
Individual replies and internal notes within a conversation; supports metrics such as first response time, reply cadence, handle time, and collaboration patterns.
Customer
End customers/contacts associated with conversations; used for segmentation, support demand by customer or segment, repeat contact rates, and CSAT by customer.
Agent
Help Scout users handling conversations; enables reporting on agent workload, responsiveness, resolution efficiency, and CSAT by agent.
Team
Groups of agents; supports team-level throughput, backlog and SLA performance, and capacity planning.
Mailbox
Shared inboxes organizing conversations; enables analysis by queue (mailbox), custom field usage, and performance by mailbox or saved views (folders).
Happiness Rating (CSAT)
Customer satisfaction ratings tied to conversations and customers; used to track CSAT distribution and trends and analyze drivers by agent, team, mailbox, or customer segment.
Workflow (Automation Rule)
Automation rules that route, tag, or update conversations; useful for auditing automation coverage and understanding rule-driven categorization in support processes.
Authentication Required
Connects to Help Scout using OAuth 2.0 with a client ID, client secret, and refresh token from your Help Scout app
Getting started with
Help Scout Analytics & Business Intelligence
Connect your Help Scout data
Connect to Help Scout 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?
Help Scout 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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