In short-term rentals, there is more to revenue management than just dynamic pricing. Guests do not evaluate a nightly rate on its own when searching for a stay. They evaluate it alongside reviews, ratings, photos, and recent guest experiences. A listing that has just received a below-average review is often perceived differently than one with a strong reputation, even if everything else is equal.

That is why Beyond is introducing a new dynamic pricing algorithm component: Reputation Factor.

The Reputation Factor automatically adjusts prices when a listing receives a negative or below-average Airbnb review. The goal is not to “penalize” a listing, but to respond to a real, measurable shift in booking behavior that happens after negative reviews are received. In addition to helping reflect guest perception, these price adjustments also serve to protect a listing’s placement within Airbnb’s search ranking logic, as listings with recent negative reviews are often displayed less often to searchers. 

This factor helps listings stay competitive during short-term dips in demand, without requiring manual base price changes or overrides by revenue managers.

Why Reviews Matter More Than You Think

Our revenue management and data science teams analyzed the relationship between Airbnb reviews and booking pace across thousands of listings. The findings were consistent and intuitive: when a listing receives a low or below-average review, its booking pace declines shortly afterward for a period of time.

The magnitude and duration of that decline depends on the severity of the recent review:

• One-star reviews show the strongest and longest impact, with booking pace declining immediately after the review is published and continuing to impact booking activity for more than a month until the effect declines further. 
• Two-star reviews show a moderate but still meaningful decline that lasts several weeks.
• Three-star reviews create a shorter, but still statistically significant, dip in booking velocity.

In all cases, booking pace drops by double-digit percentages compared to similar listings that did not receive a negative review, with the largest impact typically occurring two to three weeks after the review is received. This pattern was observed consistently across global markets and time periods.

In other words, reviews are not just a reputation signal. They are a demand signal.

How Reputation Factor Works

The Reputation Factor is applied automatically to eligible listings that are connected to Beyond, either through a property management system or through a direct Airbnb connection. Once a PMS listing is connected, Beyond is able to identify the corresponding Airbnb listing (if available) and can continuously monitor review activity.

When a negative or below-average review is detected, Reputation Factor activates immediately and applies a temporary, targeted price adjustment. The adjustment is designed to reflect the expected short-term impact on booking velocity, while encouraging faster bookings and quicker recovery.

The calculation takes into account three key dimensions: severity, timing, and recovery.

Review Severity Determines the Size of the Adjustment

Not all reviews have the same impact, and the new Reputation Factor reflects that.

Based on observed booking behavior, the maximum price adjustment is tied to the peak booking-pace impact for each review type:

• One-star reviews can trigger a discount of up to roughly 24 percent.
• Two-star reviews can trigger a discount of up to roughly 20 percent.
• Three-star reviews can trigger a discount of up to roughly 14 percent.

These values are grounded in historical booking data rather than assumptions or anecdotal behavior.

Timing and Decay Are Built In

The impact of a negative review is strongest in the weeks immediately following the review, then gradually fades.

The Reputation Factor mirrors this pattern. The price adjustment is strongest in the near term and decays over time, softening after the peak impact period of the below-average review, rather than an abrupt on-off switch. This approach helps listings capture bookings when demand is most sensitive, without permanently suppressing rates. Additionally, this reflects the normal review process where below-average reviews can get “buried” and viewed less by potential guests. 

The default duration of the price adjustment period depends on the severity of the recent review, with shorter windows for less severe reviews and longer windows for lower, one-star reviews. In fast-booking markets, the factor can recover even sooner using market-specific lead-time data, ensuring that destinations with shorter booking windows are not over-discounted.

Automatic Recovery Based on Positive Reviews

Recovery is just as important as the initial adjustment.

Rather than relying only on time-based recovery, Reputation Factor can end early when the listing receives strong positive signals. Specifically, the adjustment is removed once two new five-star reviews are received, signaling that guest perception has stabilized.

This avoids unnecessary discounts for listings that quickly rebound and reinforces pricing discipline once confidence returns.

There are also built-in safeguards. For example, listings with multiple recent bookings around the review date may be excluded from the adjustment if there is strong evidence that positive reviews are likely to follow. Peak demand periods and major events are also protected to avoid unnecessary rate suppression during high-value dates.

What This Means for You

Reputation Factor is designed to reduce manual work while improving pricing accuracy.

Instead of reacting to a bad review by lowering base prices, applying overrides, or second-guessing the algorithm, revenue teams can rely on Beyond’s Reputation Factor to make a measured, temporary adjustment that reflects real data. 

The result is fewer manual price changes, faster recovery after bad reviews, and pricing that stays aligned with how guests are actually shopping.

Most importantly, Reputation Factor reinforces Beyond’s core philosophy: prices should respond to live market signals, not static assumptions. Reviews are one of those signals, and now they are directly reflected in pricing decisions.

Pricing That Adapts to Reality

Reputation is not static, and neither is demand. With Reputation Factor, Beyond pricing now adapts automatically when guest perception changes, helping listings stay competitive in the moments that matter most.

This is one more step toward a pricing engine that responds earlier, adjusts smarter, and reduces the operational burden on hosts and property managers, without sacrificing revenue discipline.