Insights enables hotel teams to seamlessly translate analysis into aligned priorities and an evolving strategy.
AI in Insights is designed to support that progression.
Sometimes that means answering a quick question.
Sometimes it means clarifying what you’re seeing on a dashboard.
Sometimes it means building structured content others will rely on.
Sometimes it means turning analysis into something leadership can immediately act on.
AI supports each of those moments — without forcing a single path.
To make this tangible, we’ll use pick-up analysis as an example. The same principles apply across room brand analysis, budget prep, market positioning review, and more.
If You’re Reviewing a Dashboard and Need Faster Clarity
Use the Dashboard AI Assistant
If your starting point is a published dashboard — such as the Pick-Up Overview template or a shared team dashboard — the Dashboard AI Assistant allows you to ask questions directly within that view.
You’ll find it inside the dashboard interface. It uses the full dashboard — all tiles, filters, and structure — as context.
This experience is intentionally focused and constrained:
You can ask follow-up questions.
You can clarify what metrics represent.
You can investigate anomalies.
You cannot modify or rebuild dashboard content from here.
Because it operates within a defined structure, it works best when dashboards are thoughtfully curated around a clear analytical objective.
Example: Reviewing Pick-Up
You open the Pick-Up Overview dashboard as part of your daily cadence.
Instead of scanning every tile manually, you might ask:
Portfolio perspective:
“Across the portfolio, where are we seeing the strongest pick-up trends?”
“Which properties are pacing differently this week?”
“Is the variance concentrated in specific segments?”
Property perspective:
“As the Director of Revenue for this property, where should I focus?”
“Which segment is driving the change versus last week?”
“Are we pacing ahead of same time last year?”
The assistant helps you move from raw performance signals to clear priorities.
Adding Business Context During Dashboard Review
When reviewing a dashboard, you may want to layer in operational context.
You can upload documents directly into the Dashboard AI Assistant by either:
Dragging and dropping a file into the chat window
Clicking the paperclip icon to select a document
These documents become part of the conversation context for that session.
📅 Marketing Calendars
“Did any campaigns align with this increase in pick-up?”
“Which campaign dates show the strongest lift?”
🧾 Group Pipeline Spreadsheets
“Does current pick-up align with expected group arrivals?”
“Where are we exposed if optional business doesn’t convert?”
In this mode, uploads help explain performance within an existing analytical structure.
If You Want to Ask Questions Freely
Use the AI Assistant (Side Navigation Panel)
If you’re not starting from a specific dashboard, open the AI Assistant from the side navigation panel.
This interface supports:
Open-ended questions
Cross-topic exploration
Hypothesis testing
Rapid iteration
Multi-step analytical conversations
Unlike the dashboard experience, this is not constrained to a single structured view.
Example: Pick-Up Exploration
You might ask:
“For compressed forward-looking dates, what has daily pick-up looked like over the last 7 days for each property?”
“How has segment mix shifted year over year this quarter?”
“Are we pacing differently against forecast this month?”
“What changed yesterday that explains this revenue increase?”
You can follow threads:
Narrow timeframes
Change segmentation
Add comparative views
Pivot across properties
The conversation can evolve as your understanding deepens.
Uploading Documents in Standalone Chat
Just like in the dashboard experience, you can upload documents into the AI Assistant by dragging and dropping a file into the chat or clicking the paperclip icon.
In standalone chat, uploads often help shape the direction of analysis.
📝 Internal Strategy Documents
“Which assumptions here are no longer supported by current performance?”
“Are we seeing early signals that support this repositioning plan?”
📅 Marketing or Group Plans
“Does our recent pick-up trend reflect the activity outlined here?”
“Are campaign-targeted segments showing stronger movement?”
Because this environment is not tied to a specific dashboard, uploads can:
Frame the analytical direction
Influence how the assistant structures queries
Help generate new content from external materials
From Exploration to Structured Content
Exploration doesn’t have to stay conversational.
From the AI Assistant, you can:
Select one or multiple generated queries
Click Create dashboard from chat in the left-hand panel
Generate a structured dashboard draft
This is particularly useful when:
You’ve iteratively built multiple related analyses
You’ve followed a narrative thread worth preserving
You want to operationalize something you discovered
You’re converting insight into durable structure.
Starting in Chat With the Intent to Build
Some users open the AI Assistant with a clear goal: build new content quickly.
You can:
Upload an existing report, spreadsheet, or document (via drag-and-drop or paperclip) and ask the assistant to recreate it in Insights
Describe a full dashboard concept and generate multiple related analyses in one conversation
Rebuild reporting previously managed in Excel or another BI product
Because the AI Assistant can generate several related queries in a single thread, it’s often the fastest way to assemble an initial dashboard structure.
That draft can then be refined in a workbook if greater control is needed.
If You Prefer Precision and Hands-On Control
Use the AI Query Helper (Workbook)
The AI Query Helper, located inside Workbooks, supports structured, durable analysis.
This is often the preferred entry point when:
You know exactly what you want to build
You want visibility into dimensions, measures, and filters
You’re maintaining dashboards long-term
You want tighter control over structure
Here, the flow is deliberate:
Intent → Query → Visualization → Saved Content
Example prompts:
“Create daily pick-up by property for the last 30 days.”
“Show pick-up by segment compared to same time last year.”
Calculation Generation Is Built In
The AI Query Helper can generate calculations directly during the conversation.
“Add revenue share.”
“Add year-over-year variance.”
“Add variance to forecast.”
You describe the logic. The assistant builds it into the structured query.
Shaping the Visualization
After generating the query, you can use AI to adjust how it’s visualized:
“Show this as a line chart.”
“Convert this to a stacked column chart.”
“Pivot segments across columns.”
Visualization choices influence how clearly analysis translates into insight.
👉 How to Use the AI Query Helper to Shape Chart Visualizations
👉 Make the Most of the AI Query Helper
Turning Analysis Into Aligned Communication
AI Summary Visualization
After building a query, you may decide that a written explanation is more effective than a traditional chart.
Select AI Summary as a visualization type to generate a narrative based on your query.
Unlike other chart types, this output is text-driven and dynamically updates as data or filters change.
This is particularly valuable when:
Scheduling dashboards for automated distribution
Preparing leadership or ownership updates
Creating portfolio-level rollups
Making dashboards self-explanatory
Instead of manually writing commentary each time performance updates, the summary evolves with the data.
Guiding the Output with Additional Context
When adding an AI Summary, use the Additional Context field to shape the output.
You can specify:
Format (bullet points, paragraph, executive tone)
Depth (high-level overview vs. detailed analysis)
Focus (segment mix, forecast variance, risks, anomalies)
Desired outcome (highlight areas needing attention)
This allows you to translate analysis into aligned priorities without rewriting summaries manually.
A Flexible System — Not a Fixed Path
The same flexibility applies whether you’re:
Reviewing forecast accuracy
Assessing pricing strategy
Comparing against market benchmarks
Analyzing booked vs. stayed behavior
Monitoring compression and risk
Evaluating portfolio-level trends
Your objective determines your entry point.
Reviewing structured dashboards → Dashboard AI Assistant
Exploring layered or cross-topic questions → AI Assistant
Building durable reporting → AI Query Helper & AI Assistant
Communicating clearly to stakeholders → AI Summary
These are different ways of working — all designed to support the same progression:
From analysis → to understanding → to aligned priorities → to evolving strategy.
Summary
AI in Insights supports:
In-context clarification
Open-ended exploration
Structured content creation
Dynamic narrative communication
You can use these independently or together, depending on how you prefer to work.
The goal is to reduce friction between curiosity, insight, and action — so you can move seamlessly from analysis to aligned decisions.