This guide defines key terms you’ll encounter while using Dovetail. Whether you’re new to the platform or need a quick refresher, this reference helps you navigate Dovetail’s features so you can organize your data, analyze feedback, and share your insights with confidence.
A workspace is the top-level organizational structure that houses all of your company’s data and brings your entire team together. It serves as a single, centralized knowledge base where qualitative data is organized, analysized, queried and accessed.
Folders are a way to create a logical structure for organizing data, enabling intuitive navigation, controlled access, efficient searching, and using contextual chat.
Projects are a space for you to thoroughly analyze high-density data sources like customer interviews, usability tests, sales calls, or surveys to draw very detailed insights.
Channels uses AI to automatically analyze continuous streams of customer feedback from sources like support tickets, product reviews, or NPS responses and identifies and tracks themes over time.
Agents are AI-powered automations in Dovetail that perform actions on your behalf - from continuously monitor feedback, generate shareable docs, to notify via email or your team on Slack.
Contextual Chat is an AI assistant that provides detailed, insightful answers about your Dovetail data. You can ask questions at the Workspace, Folder, Channel, Project, Data, or Insight level and receive responses with direct citations. This feature allows you to have a continuous conversation with your data, from understanding the top user feedback to brainstorming a plan of action.
With Dovetail Search, you can quickly find any object in your workspace, including projects, channels, data, highlights, and insights. You can filter results by common fields or tags to analyze themes across different projects and folders.
Data is an individual piece of information or a file uploaded into Dovetail for analysis. Common examples include video call recordings, usability tests, and surveys. Also referred to as a “data object”.
A Field provides context that applies to an entire piece of data, enabling you to filter and analyze it across your workspace. Think of a field as a filter to refine your work and group data for analysis (e.g., assigning a region or a customer persona to a video call).
Tags are labels you attach to specific moments within a piece of data to help you find structure and themes in your research. They help you cluster similar content for analysis and identify patterns (e.g., tagging a specific moment in a video with “competitor mention” or “usability feedback”).
Data views are individually saved view and filter configurations for the data within your project. They eliminate the need to re-apply your preferences every time you open a project.
A Highlight reel in Dovetail is a video of stitched-together clips that share a theme, tag or topic. It’s a powerful way to bring the voice of your customer to life when sharing with your team or organization.
An Insight is a document used to generate, collaborate on, and share your research findings after data analysis. Think of it as a report in Dovetail, where you can turn your analysis into a published report to share with stakeholders. You can also think of these as “artifacts” that you create in Dovetail.
Data Points are individual pieces of feedback synced into a channel. Each data point represents a single piece of customer input, such as a support ticket, an app review, an NPS response, or any form of continuous feedback.
Topics are high-level categories that organize your themes. They provide structure to help you quickly navigate and understand your feedback landscape.
