You can now on table visualizations in dashboards. Instead of manually recreating the same rule multiple times, copy an existing rule and simply update what it applies to.

All colors, thresholds, formatting styles, and total behavior carry over automatically — you just adjust the reference column.

Watch the short Loom below for a quick walkthrough.

We've heard your feedback! Many of you requested better visibility into all your KPIs when forecasting and budgeting. We've enhanced the Planning view with a comprehensive totals footer that displays all your metrics in one convenient location.

This update streamlines your forecasting and budgeting workflow by:

You can now use the directly on your dashboards!

Many of you have asked for a way to stay in the flow while reviewing dashboards, ask follow-up questions, and explore what’s driving changes without switching to workbooks or a separate AI experience. Bringing AI Assistant onto dashboards is a direct response to that feedback.

The assistant uses the full dashboard as context, working across all tiles together. When a dashboard is well curated around a specific type of analysis, the AI helps you focus on what matters and go deeper without losing context.

You’ll still use the to build analysis from scratch and the standalone for open exploration. The Dashboard Assistant adds another way to work with AI, grounded in the dashboards you already rely on.

Open any dashboard and click the icon in the bottom-right corner to start chatting.

The AI Assistant is turned .

To enable it on a dashboard:

Once enabled, the AI Assistant icon will appear in the bottom-right corner of the dashboard.

All dashboard templates already have this enabled by default, so any new dashboards created from templates will automatically include the AI Assistant.

If enabled, you can:

You’re not limited to the tiles on the screen, but dashboards designed with a clear analytical purpose create the best experience.

Just like in the standalone AI Assistant, the **Dashboard Assistant supports uploading documents**.

This means you can combine:

This can be especially helpful when you want to enrich dashboard analysis with information that lives outside of Insights, such as:

The assistant can use this uploaded information alongside your dashboard to help answer questions and provide more complete, contextual insights.

We’re excited to see how you use the Dashboard Assistant and how it fits into your day-to-day workflows. As always, your feedback helps shape what we build next, so keep it coming via chat.

👉 help desk article

A couple months ago, we announced expanded analysis for and — allowing these revenue types to be broken down by I and hierarchies in the same way as .

We’re happy to share an update on that release.

This expanded revenue breakdown is now enabled for the following additional PMS integrations that were part of this project:

If your property uses any of the PMSs above, you can now analyze and by:

This brings these PMSs into alignment with the PMSs included in the initial release (Opera Cloud via OHIP, Mews, and Apaleo).

As with the original rollout, this applies automatically to new and updated reservations. Historical data continues to be resynced in the background to support full year-over-year and same-period analysis.

This update extends the expanded revenue breakdown across all PMS integrations planned for this project, making it easier to analyze total revenue consistently across inventory, rate plans, and segmentation.

We’ve redesigned the Optimization interface to give you a cleaner, more intuitive way to manage your pricing strategy. While everything works exactly as it did before, we’ve reorganized the layout to ensure the data you need most is always front and center.

This update is all about making your workflow more efficient. By surfacing dependent rates and highlighting price variances, we’ve removed the guesswork and the "hidden" info found in tooltips. , ensuring your experience remains fast, clear, and consistent as we grow.

💬.

You can now manually apply restrictions to specific rate plans within the Base Rate Parity group. This update gives you the precision to manage individual parity rate plans where needed, while still benefiting from engine recommendations that ensure consistency with your overall Base Rate Parity strategy.

This update is all about matching the platform to your specific strategy. You now have the freedom to:

💬.

Custom scheduling lets you go beyond standard daily, weekly, or monthly deliveries by defining exactly when something should run using a cron expression. Historically, this required knowing cron syntax, which made custom schedules harder to use and easy to get wrong.

Now, you can simply describe the schedule you want in plain language — and the AI will generate a valid cron string for you automatically.

The most frequent schedule supported is once per hour. More frequent intervals (for example, every 5 minutes) are not supported, even when using AI.

You can now bring event context directly into your Pick-up analysis.

Following the earlier release that introduced Events in the Bookings topic, Events data is now available in the topic as well. This means you can go beyond aggregate pick-up trends and start understanding how booking changes behave across different event types, categories, and individual events — helping explain pick-up is accelerating, flattening, or behaving differently than expected.

Whether you’re validating assumptions about event-driven demand or adding richer context to ongoing pick-up monitoring, this unlocks a more complete view of how events influence booking behavior over time.

, including:

These fields mirror what’s already available in the Bookings topic, keeping event workflows consistent across performance and pick-up analysis.

You’ll already see these updates reflected in the existing

Pick-up Overview

dashboard:

This means you can immediately start layering event context into the views you’re already using — filtering to specific events, grouping by event categories, and adding helpful explanation to the pick-up patterns you’re monitoring, without needing to rebuild or reconfigure anything.

Pick-up is ideal for understanding how booking changes build over time and how those patterns differ by event type or category. However, it’s not always the right place to compare one event's pick-up to another across periods, especially when event dates shift year over year.

If you’re comparing two events (or the same event across different years) and the stay dates don’t align, we recommend using the

Event Pacing & Comparison Dashboard

instead. It’s designed specifically to compare lead time behavior, booking curves, and side-by-side event trajectories in a like-for-like way.

Managing Channels and Companies just got easier. You can now copy Data Enrichment configurations across your property portfolio in seconds, eliminating repetitive manual setup.

Managing Data Enrichment across multiple properties can be time-consuming and error-prone. With this update, you can:

⚡- replicate your Data Enrichment setup across properties instantly instead of recreating it manually each time.

🎯 - eliminate inconsistencies by using a single source of truth for your Channel and Company data.

📊 - onboard new properties with pre-configured Data Enrichment in minutes.

Copying Data Enrichment configurations is straightforward:

You can now turn your AI Assistant conversations into dashboards in just a few clicks.

Previously, moving from a conversation in the AI Assistant to a dashboard meant a multi-step, manual process: exploring each result, opening workbooks, creating a dashboard, and stitching everything together across multiple tabs.

Now, when you’re chatting with the AI Assistant and reviewing visual results, you can simply select the , choose the visualizations you want to include, and create a dashboard instantly. You’re taken straight into the newly created dashboard, ready to customize, add filters, or set up delivery.

This update is available directly within the AI Assistant, alongside your existing conversations and visual results.

This makes it much easier to move from asking questions about your data to creating reusable, shareable content. You can go from exploration to a dashboard that supports daily, weekly, or monthly review in one smooth flow—without breaking your workflow or repeating work.