Dashboards let you combine visualizations, summaries, metrics, documents and explanatory text from the same text analysis project. Use them to organize an analysis around a particular audience or business question instead of moving between individual features during every review.
A dashboard can help you:
Monitor recurring customer or employee experience metrics
Compare products, segments, or reporting periods
Track changes in volume, sentiment and Drivers
Present AI-generated summaries alongside supporting visualizations
Create a reusable view for meetings and reports
Open the Dashboard
Open a text analysis project and select Dashboard from the main navigation.
Use the dashboard dropdown to open an existing dashboard or select the + button to create one.
The Dashboard and the main Journey Insights Hub application provide different views of the same text analysis project:
Use the main main application to explore concepts, test filters and validate findings
Use Dashboard to organize selected findings into a reusable report or monitoring view
When available, use the menu under the Journey Insights Hub logo to switch between Dashboard and the main application.
Create a dashboard with a clear purpose
Before adding widgets, decide:
Who will use the dashboard?
What question should it answer?
Is it intended for exploration, recurring monitoring, or presentation?
Which text analysis project fields, concepts, and periods should remain consistent?
Use a descriptive dashboard name that identifies its audience or purpose, such as:
Monthly Customer Experience Review
Product Launch Feedback
Contact Center Issue Monitoring
Employee Experience by Region
Avoid placing every available analysis on one dashboard. Create separate dashboards when different audiences or questions require substantially different information.
Add widgets
The widget panel organizes the available widgets into folders based on their analytical purpose.
Add a widget by selecting it from the panel or dragging it onto the dashboard canvas.
Depending on the text analysis project and available fields, you can add widgets for:
Text analysis project metrics and metadata
AI-generated findings
Concept volume
Sentiment
Drivers
NPS
Matching records
Explanatory text
After adding a widget, position and resize it according to its importance. Give the most important result enough space to be understood without requiring the audience to inspect every smaller widget first.
Add structure with text boxes
Use Text Box widgets to explain the dashboard rather than relying on charts alone.
Text boxes can provide:
A dashboard title
The purpose of the analysis
The population and reporting period
Definitions of important metrics
Notes about filters or comparison groups
Key findings and recommended follow-up questions
Keep explanatory text concise. The dashboard should guide the reader through the analysis without becoming a full written report.
Create a business-focused dashboard flow
Build the dashboard around the business question it needs to answer. A useful flow moves from the overall result to where it is changing, what may be influencing it, and the records supporting the finding.
A dashboard can follow this sequence:
Define the question and scope - Use a text widget to identify the reporting period, data sources, active filters, and business question.
Show the primary outcome - Begin with the most important performance measure. For example, use the available NPS widgets to provide a high-level view of customer loyalty.
Show where the result differs - Compare the outcome across periods, products, regions, channels, journey stages, or customer segments to identify where the strongest differences appear.
Explain what is associated with the outcome - Use Drivers to identify concepts associated with higher or lower values in the selected metric.
Measure the reach and tone of key experiences - Use Volume to show how widely important themes appear and Sentiment to show how those experiences are discussed.
Summarize the findings - Add an AI-generated summary or comparison that connects the most important quantitative and qualitative results.
Provide supporting evidence - Include a Records View with representative feedback from the relevant concepts and groups.
State the implication or next action - End with a text widget summarizing the priority, affected group, recommended follow-up, or question requiring further investigation.
For example, a customer-experience dashboard designed to explain a decline in performance might include:
A text widget defining the period, audience, and data sources
A high-level score and comparison with the previous period
A segment comparison showing where the decline is concentrated
A Drivers widget identifying concepts associated with the result
Volume and Sentiment widgets for the priority themes
An AI-generated summary of the main differences
A Records View with representative feedback
A text widget documenting the recommended next step
Keep the dashboard focused
Every widget should support the dashboard’s purpose.
Before keeping a widget, ask:
Does it answer a question the audience cares about?
Does it add information that is not already shown?
Can the audience interpret it without opening the text analysis project?
Does it use the same population and period as the surrounding widgets?
Is another widget a clearer way to communicate the result?
A smaller number of well-configured widgets usually communicates more effectively than a dashboard containing every available visualization.