Your Portfolio page can show a lot of data. Revenue, Occupancy, Pickup, ADR, RevPAR, flags, and plenty more, each with its own date range.

Different jobs call for different columns. A morning pickup check needs a different view than a quarterly owner review, and both look different from a quick scan of flagged listings.

Now, you can save each of those views as a Column Set and switch between them instantly.

At the top of your Portfolio page, next to the listing count, you'll see the Column Views dropdown. Open it, and you'll find:

The columns button next to it shows how many columns are in your current set (e.g. "4 columns"), so you can add, remove, or edit columns from there.

Not sure where to start? We've built a handful of Column Views around the questions revenue managers ask most:

Each "Zoom" set focuses your Portfolio on one lens, so you can jump straight into the analysis without assembling columns first.

Let's imagine you start every Monday with the same routine: check recent pickup, then compare this month's revenue against what's on the books for next month.

Here's how you'd build that view once, and never rebuild it again:

Now, every Monday, it's one click away.

And, since you can save as many sets as you need, you can build one for each part of your workflow: a pickup set, an owner reporting set, a holiday planning set, and so on.

Here's where it gets fun.

We recently expanded metric filters to support static date ranges: months, quarters, and years. Those same options are available on your columns, and Column Sets save them.

When you open a column's date range, you'll see:

So, you could build a "Holiday Watch" set with:

Last December's results next to this December's position, side by side, every time you open the set.

Have a favorite?

Set it as your Default, and your portfolio pages will open with that Column Set already applied.

Your default set is marked with a Default tag in the dropdown.

Together, they let you jump straight to a precise view of your portfolio. For example:

Apply your "Peak Season Watchlist" Segment (listings light on the books for next July) and switch to Occupancy Zoom.

In two clicks, you're looking at exactly the right listings, through exactly the right lens.

Name your Column Sets after the task, not the columns. "Monday Pickup Check" and "Q1 Owner Review" are much easier to find than "Revenue + Occ + ADR v2." Your team (and your future self) will thank you.

Until now, metric filters were built on rolling windows: "Occupancy, last 30 days" or "Revenue, next 90 days."

Rolling windows are great for day-to-day monitoring. But a lot of revenue management questions aren't asked in rolling windows. They're asked in calendar periods:

Now you can answer those directly. When you pick a date range on a metric filter, you'll see three options:

These new ranges are available for all your performance metrics - which as you might recall, just got a major expansion, as well!

Here's where it gets fun. Static periods work in both directions.

Let's imagine it's late October, and you're planning for the holidays.

First, look back:

Then, look forward:

Two filters, and you've got a precise list of listings worth a second look before the holiday booking window closes.

The same pattern works for any period. Compare to the upcoming , or isolate a peak month in a ski or beach market.

As our filter list has grown, we've organized it into top-level categories:

Each category collapses, and Wheelhouse remembers the state you left it in. If you only ever use Metrics, collapse the rest and they'll stay out of your way.

And, as you add filters, you'll see a next to them on your Portfolio and Reports pages, so you know exactly how many listings you're working with.

With this update, your smart segments continue to get more powerful.

A Segment built on a window updates as time moves. "Occupancy, next 30 days" today is a different window than it is next week.

A Segment built on a period stays anchored. "Occupancy, Q3 2026" always means Q3 2026.

Now, you can build smart segments that keep watch over the exact periods you care about. A few ideas:

Your listings that are light on the books for next summer's peak month pacing behind their neighborhood. Check it weekly as July approaches, and watch the list shrink as you make adjustments.

Every listing with heavy owner or maintenance blocks in an upcoming quarter. A handy list to review before a busy season, so you can confirm blocks with owners while there's still time to open nights back up.

Static periods are ideal for anything you want to revisit consistently: quarterly owner reviews, season retros, or a fixed watchlist for a specific event month.

🥳

Pair static period filters with .

Filter to listings with in your top tier, select them all, and adjust Base Prices up by 5% for next year. Your Events & Seasons pricing updates right along with them.

TL;DR →

🪄

Until now, every Last Minute and Far Future rule has applied as a step. Set "-20% within 3 days," and day 4 gets no discount while day 3 gets the full -20%.

Now, each Last Minute and Far Future card has a switch:

The same switch now appears in Seasonality too, so all three settings work the same way.

📉

Let's imagine you have four Last Minute rules:

With , your pricing curve has 4 hard drops: at day 90, 45, 30 & 15.

With , Wheelhouse eases your Last Minute Discount, with each ramp drawing it's slope from the ranges that surround it.

The result: a few simple rules, a smooth pricing curve.

🗓️

Far Future Premiums work the same way.

Say you set +10% beyond 90 days and +20% beyond 180 days. Instead of two hard jumps, your premium climbs gradually around each threshold, with each ramp reaching full strength on the dates the rule covers.

To keep changes contained, every ramp is capped at 28 days. That means a rule you add far in the future won't ripple back into today's prices.

🧮

Smoothing applies across all the rules in your Last Minute and Far Future cards, including:

So if a season starts in two weeks with a different Last Minute discount, Smooth eases you into it rather than flipping on day one. And, smoothing works with just one rule.

🔒

A few things are intentionally left alone:

🗂️

You can set Smooth or Stepped in bulk from your Portfolio Settings page.

When you have selected, simply find the group of listings you want to adjust, and update them, per the image below.

🚀

🥳 Pair Smooth with a Last Minute "bounce back"

Many of you raise prices again right before the stay date to avoid unwanted bookings. With Smooth on, your discount can ease in, hold at full strength, and then ease back out, all from a few simple rules.

🤓

📃 Help Center article

Historical Protections now let you decide your prior data protects your future nights:

Let's explore these two options more deeply.

Weight increases your recommended price by a percentage of the difference between your current recommendation and historical price.

Example: If your current recommendation is $600 and your historical price is $1,000, the difference is $400.

Weight only increases prices. When set to 100%, if your current recommendation is already higher than your historical price, no adjustment is made. If set above 100%, your recommendation won't fall below that percentage of your historical price. For example, at 150%, a $1,000 historical price would imply a future price of $1,500 or more.

Floor establishes a minimum recommended price based on a percentage of your historical price.

If your historical price is $1,000 and you set a 50% Floor, future recommendations won't fall below $500. A recommendation of $400 would increase to $500, while a recommendation of $600 would remain unchanged.

If you have set a minimum price is higher than your floor, the higher minimum price will determine the final price.

You can choose your type under in .

In what has been one of our most interesting product learnings to date, it came to our attention in Q3 that we were not consistently communicating how Historical Anchoring (now, Historical Protections) worked.

In short, this setting has always been a "weight", meaning it could pull prices up.

However, we learned that certain clients had been taught this setting as a "floor", meaning they thought this setting created a price floor. (It did not)

As we explored the best way to solve this miscommunication with a number of customers, you all taught us that BOTH of these options were valuable, which is why we are now making both options available.

Thank you for the guidance and insights!

Additinonally, you now have access to for the Historical Protections :

Booked price was our initial setting value.

Earlier this year, we introduced "posted price" as a second protection source. This option become the popular choice for teams whose booked rates are distorted by promos, commissions, or contracted rates.

However, "posted price" had one major limitation - properly handling new listings.

For example, Wheelhouse never posted a price for a date, there was nothing to protect that night with.

This happens most often when:

In both cases there's a real booked rate, but no posted rate, because Wheelhouse wasn't setting the price at the time.

Hence, why we have introduced your 3rd option - "posted price w/ booking fallback".

Most of a listing's calendar stays protected by posted prices, and a handful of gap dates fall back to booked price automatically.

You onboarded a listing to Wheelhouse in early 2026 and imported its existing reservations. New Year's Eve 2026 was booked at $650 before the listing came onto Wheelhouse pricing.

To protect New Year's Eve 2027, your Historical Protection is a weight set to 80%, and the current recommendation is .

For every other date on that listing's calendar where a posted price exists, posted price remains the foundation.

These updates change of protection is applied and it references. They don't change how the comparable date is chosen:

With more options comes more need to see what's happening. Before you switch, you can:

Posted price (with booking fallback) works with the portfolio tools you already use:

Already on Posted price? Nothing changes unless you choose the new option.

🥳 Use Grouped Settings to find every listing currently on Posted price, then preview the fallback series on a few with imported or older reservation history. Those are the listings most likely to have gap dates that will start being protected.

📃 Help Center article

Length of Stay pricing has always made sense on paper.

What's been missing are collaborations between PMSs & RMSs to actually enable this powerful RM practice. Now, that's changing, and Wheelhouse and multiple PMS partners are leading the way.

With this launch, we're bringing to market the we've seen anywhere in the accommodations space.

Specifically. now you can create LOS rules for Months, Day of Week, Seasons, Events, Time-Based and more, and easily visualize the impact on your pricing strategy, in real time.

Head to your listing's tab → section → to find the new setup.

Every stay length gets its own tab — 2 nights, 3 nights, 4 nights, 5 nights, 6 nights, 7+ nights, 14+ nights, and 28+ nights — each with its own rule count and its own default adjustment.

LOS pricing historically mostly meant discounting longer stays.

Now it can work the other way, too — every rule accepts a positive or negative adjustment, so you can charge a premium for shorter stays exactly when you want to.

Picture a five-night event weekend on your calendar. You don't want to sit on empty nights waiting for someone to book all five — but you also don't want a 2-night guest to get in for less than what those nights are worth during peak demand.

With an Event rule and a positive adjustment on your 2-night (or 3-night) tab, you can open those shorter stays up for sale while making sure you're still capturing the full value of the event.

In this case, we're taking your Fourth of July holiday, and letting someone book for 2 days... as long as they paid you 2x the daily price!

Want your 2-night discount to be deeper Sunday through Wednesday, but lighter on weekends?

You can now easily set a percentage adjustment for each day of the week, independently.

Time-based rules let you set a different adjustment depending on how close to check-in a booking is made — for example, 0% within 14 days, then an additional -20% within 7 days.

Stack as many time-based rules as you need to build your full last-minute (or advance-booking) LOS strategy.

All of your Events & Seasons are setup for LOS, too.

Therefore, when you customize your LOS rules for these events & seasons, the dates are already pre-configured, ensuring you can easily adjust & manage LOS pricing for your most important time periods.

In the image here, we show you "removing" the 4 day discount during your Summer High Season.

Below your Rules, Date-specific overrides give you a place to handle the true exceptions — specific dates that shouldn't follow any of your standing rules — without disturbing the rest of your configuration.

In exploring a LOS solution, one of our priorities was making it easy to see both your % override, and the actual final pricing output for any calendar day.

Every change here updates your Length of Stay pricing chart in real time, plotting a line for each stay length across your full pricing calendar.

Flip the toggle between and to view your rules either as relative adjustments or as the actual dollar rate they produce — whichever makes it easiest to sanity-check your strategy before saving.

Importantly, LOS pricing rules take precedence over your Min Stay rules, including your absolute minimum stay.

Therefore, an Event LOS rule can open up a 2-night booking even on a date where your global minimum stay is set higher.

We'll surface this in your Min Stays Setting, to make sure you & your team are always aware!

Today, we’re sharing the Wheelhouse Plugin Library — a public, growing collection of Revenue Management skills you can connect straight into your AI client.

If you’re already using the Wheelhouse MCP, you know it gives your agent direct access to your portfolio — listings, pricing, reservations, preferences, and more.

The Plugin Library goes a step further: it packages that MCP connection together with the actual workflows our Revenue Management team builds, so your agents can do real analysis, faster & easier.

A few of the skills already in the library:

You don’t have to name a skill or remember which one to use — ask in plain English and your agent picks the right one:

Under the hood, we’ve also made a real efficiency improvement to how the Wheelhouse MCP handles complex, data-heavy requests.

Previously, when your agent needed to work through a lot of data, it worked one step at a time: call a tool, wait for the full result to come back through the model, decide what to do next, call the next tool. Every one of those round trips costs tokens and time.

Now, for multi-step, data-heavy requests, your agent can write a short piece of code that calls the tools it needs, loops through the results, and filters everything down — all before anything comes back into its context. Instead of pulling every reservation or every day’s pricing data through the model just to produce a summary, only the answer you actually asked for makes the trip.

As an example, this enabled us to reduce pulling reservations by 96%!

Connecting is a one-step install, and our Plugin Library is supported everywhere: Claude Code, Cursor, Codex, Grok Build, and ChatGPT (Enterprise/Work, via admin-managed import) can all run the library.

And, the plugin library updates automatically as we ship new changes — there is nothing to reinstall/update/etc.

Here’s how easy it is in Claude Code, as an example — two lines, pointing at one repo:

See a full walkthrough of connecting it in Claude here:

Instructions for Cursor, Codex, Grok Build, and ChatGPT are linked at the bottom of this post.

And, for more, you can always review our API docs:

🎥

🩻

Your Pricing Chart just got much more robust. It now features 43 series, which includes major new series such as the:

Your series are now organized into 9 categories — Pricing Series, Pricing Modifiers, Limits & Controls, Bookings & Blockings, Your Settings, Pricing Engine Breakdown, Set Data, Neighborhood Data, and Market Data — each expandable, each with its own set of series you can turn on or off. You control exactly how much (or how little) is on screen at once.

⚙️

We made it much easier to compare each of your settings to the Pricing Engine Recommendations.

For example, if you have a custom Seasonality setting, you can easily see how it compares to our Pricing Engine's current Seasonal Recommendation.

We think this view will be very helpful both now, and when evaluating or updating to future Pricing Engine versions (e.g. 9.1, 10.0).

📊

Comparing your price to comps just got more useful. Neighborhood Data now includes Occupancy and Occupancy (Adj.), not just price median and range — so you can see whether a market is actually filling up, not just what it's asking. Set Data (your Dynamic Sets) gets the same Occupancy additions, and Market Data now supports Occupancy alongside its existing Median and Range series.

🧮

A few series were renamed so the label matches what the number actually is:

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19 series have been renamed, but the data is unchanged.

We renamed these series to make it easier to find & leverage the right data sets for you.

Often, we made Series names more explicit. Sometimes, we shortened them, and moved data to the descriptions you see when you hover on a series name.

The full list of updated names is here:

TL;DR →

For a while, understanding daily performance for a group of listings required heading to your Performance page.

Now, we're bringing daily performance information where you need it - right to the top of your Portfolio Calendar. That means you can easily see:

Hover over any value for a full definition — no more guessing which flavor of a metric you're looking at.

Here's where it gets useful at scale.

Whatever slice of your portfolio you're looking at, the aggregate performance numbers for that slice are already sitting at the top of the calendar.

Recently, we launched many new metrics, so you can better unpack how any listing is performing.

However, another important view is how performance is rolling up to a daily level.

Adding these metrics to your calendar view is step one of helping you think about pricing strategies tied to how each day is performing... not just each listing.

For teams managing large portfolios, that means faster triage, without ever leaving the calendar.

Aggregate Performance Rows are on by default in your Portfolio Calendar. To show or hide them:

As noted in the intro, due to data loading, we currently ONLY show the aggregated rows for views that contain .

📽️ Link here

🌙

We've refined how the More conservative option handles last-minute pricing. The updated curve applies deeper discounts as arrival gets closer, then tapers those discounts more gradually the farther out you go — reflecting real-world discounting patterns we've seen across operators.

🔭

The More conservative option for Far Future Premium got the same treatment. Previously, it didn't start adding a meaningful premium until roughly 365 days before arrival. The new curve starts building a modest premium around , gradually increasing toward approximately the farther into the future you price.

🛡️

If one or more of your listings were already using More conservative for either setting, we didn't flip you onto the new curve. Instead, we moved those listings to a that closely matches the More conservative curve — so the pricing behavior you were already relying on stayed consistent.

In other words: improving the data-driven option doesn't mean your live strategy changed out from under you. If you did nothing, you're exactly where you were.

🚀

No action is needed if you're happy with how your pricing has been working. If the new curve sounds like a better fit for your listing(s):

🥳

Not sure whether the new curve or your current Custom rule is the better fit? Try switching one listing over first and compare pacing over the next few weeks before rolling it out portfolio-wide.

Questions? Reach out to our 24/7 live chat — we're happy to walk through it.

Yes.

It is for us to endorse tech platforms for our users.

However, having spent time with the Wander team, in our opinion, this platform has reached the point that it is well worth highlighting to you.

So, why learn about Wander?

Our hot takes...

Learn a LOT more about Wander here.