Latest / Pricing Power Podcast with Fexingo: How Businesses Set Prices, Raise Margins, and Win Customers / How Hilton Prices Hotel Rooms for Maximum Revenue
Transcript
- Lucas: We talk a lot on this show about companies that sell products they physically make. But there's a whole category of business where the product vanishes if you don't sell it by midnight. Hotel rooms. Luna: Right—perishable inventory. An empty room tonight generates exactly zero dollars tomorrow. Lucas: Exactly. And that makes hotel pricing one of the most fascinating, high-stakes problems in all of business. The industry calls it revenue management, and the company that arguably does it better than anyone is Hilton. Luna: So how does Hilton actually decide what a room costs on any given night? Is it just supply and demand? Lucas: It is, but with a lot of layers. Take a specific example: a Hilton Garden Inn in Nashville. That property has about 150 rooms. In Q2 of 2025, its revenue management team—actually, it's mostly software now—adjusted prices thousands of times. The result? They pushed RevPAR, that's revenue per available room, up 7.8 percent compared to the same quarter the year before. Luna: And what was the strategy behind that 7.8 percent? Lucas: A few things. First, they segmented demand. Business travelers during the week, leisure on weekends. The software looks at historical booking patterns and predicts how many rooms will sell at each price point. Then it sets what's called an 'opening rate' for each night. A Tuesday in February might open at $129. A Saturday in July, when there's a country music festival? That opens at $349. Luna: And those rates change over time, right? As the date gets closer? Lucas: Exactly. That's the booking curve. The system monitors how many rooms have been sold and at what pace. If a Friday night in March is selling faster than expected, the system bumps the rate up. If it's selling slowly, it might drop the rate or offer a promotional package. The Nashville property's Q2 win came from fine-tuning that curve—they got more aggressive with weekend rate increases earlier in the booking window. Luna: So they basically captured more revenue from people who booked early, because those early bookers were willing to pay more than the original rate? Lucas: Exactly. And here's the counterintuitive part: they also raised rates for last-minute bookers. The old assumption was that last-minute meant discount—fill the room. But their data showed that a lot of late bookers were business travelers with urgent trips, and they had very low price sensitivity. So the system actually increased the rate for bookings within three days of arrival, unless availability was very low. Luna: That's a fascinating flip. And it worked? Lucas: The 7.8 percent RevPAR gain suggests it did. But there's a risk—you can overprice and lose customers permanently. Hilton's system has guardrails. It won't let a rate exceed a certain ceiling based on competitive set pricing. Every property has a 'competitive set' of nearby hotels, and the system tracks their rates in real time. Luna: I know from traveling that Hilton has a price-match guarantee. Doesn't that complicate things? Lucas: It does, but it's actually a strategic tool. The guarantee—they'll match a lower rate if you find one on another site—forces the system to be disciplined. If you set a rate too far above competition, you'll have to match anyway, so you might as well set it closer to the optimal level from the start. Hilton uses that as a check on overzealous pricing. Luna: What about the psychology? Does the number itself matter beyond supply and demand? Lucas: Hugely. There's the 'charm pricing' effect—$189 instead of $190. But more interesting is the concept of 'last room available' pricing. When you book a room, the system shows you one rate. But if you're a Hilton Honors member, you might see a different rate. If you're booking a non-refundable rate, another. The system dynamically offers the rate that maximizes revenue for that specific customer segment. Luna: It's like airline pricing, but with fewer seats per plane. Lucas: Exactly. Airlines pioneered revenue management in the 1980s. Hotels adopted it later, and Hilton was an early adopter. They have a centralized system called OnQ that connects all their properties. It's been refined over decades. The Nashville Garden Inn's Q2 success was just one example of thousands of hotels running similar algorithms every day. Luna: I wonder what happens when demand drops suddenly. Like a weather event or a sudden cancellation of a big conference. Lucas: The system has override capabilities. A human revenue manager can step in and set a manual rate. But the system also learns from anomalies. If a convention cancels and the hotel sees a demand drop, the algorithm adjusts future predictions for similar events. It's machine learning at scale. Luna: So the technology is smart, but it still needs human oversight? Lucas: Absolutely. The revenue manager's job is to monitor exceptions and set strategic parameters. For example, they might decide to target a higher occupancy for a holiday weekend even if it means a slightly lower average rate, to capture ancillary revenue from food and beverage. The system optimizes for RevPAR, but the human sets the goal. Luna: It's a good reminder that pricing isn't just a math problem. It's a strategic decision about what kind of business you want. Lucas: Right. And if this kind of conversation has been useful to you in your work or just your curiosity, honestly, if today was worth a coffee, there's a link for that. It's buy me a coffee dot com slash fexingo. That tiny bit of listener support is what keeps this show ad-free and independent. Luna: Yeah, it's such a small gesture that makes a big difference to us. And we really appreciate everyone who's chipped in. Lucas: Anyway, back to the Nashville Garden Inn. The other lever they pulled was group pricing. They noticed that small group bookings—wedding blocks, corporate meetings—were coming in at a discount that was too generous. So they tightened the parameters, raising group rates by about 12 percent. And guess what? Groups still booked. The demand was there. Luna: So they had been leaving money on the table by underpricing groups. Lucas: Exactly. And that's a common mistake in revenue management. You assume groups need a big discount because they buy multiple rooms. But often, they have limited alternatives—they want that specific hotel for location or brand loyalty. Hilton's system now incorporates a 'group displacement' analysis that calculates whether accepting a group at a given rate is worth more than the potential individual bookings it might crowd out. Luna: That's a complex calculation. It must involve a lot of data. Lucas: Years of data. Hilton's revenue management system is built on over a decade of transaction history from over 7,000 properties worldwide. Every booking, cancellation, and rate change is a data point. The algorithms are constantly retrained. That's the moat—a competitor can't replicate that overnight. Luna: So what's the next frontier? More personalization? Lucas: Personalization is already happening. Hilton has a loyalty program with 170 million members. They know your preferences, your past spending, your travel patterns. The system can offer you a specific rate based on your likelihood to book. But there's a fine line between smart pricing and creepy. Hilton is careful not to show wildly different rates to people standing at the same front desk. Luna: That would be a PR nightmare. Lucas: Huge. So the personalization is mostly in the digital channel—when you're logged in on the app or website. The rate you see may be slightly different from what a non-member sees, but the front desk rate is uniform. That's a deliberate boundary. Luna: Makes sense. So for a business traveler booking a Hilton for a trip next week, what's one thing they should know about the pricing they're seeing? Lucas: Book early if you can, but don't assume the rate only goes up. For some properties, rates actually drop if the hotel sees soft demand closer to the date. The classic 'wait until the last minute' advice only works if you're flexible. Otherwise, the best strategy is to book a refundable rate early, then check back periodically. Some systems allow you to rebook at a lower rate without penalty. Luna: That's great advice. And for the hotel, it's about balancing occupancy and rate. Maximum revenue is not always the highest rate—it's the right rate for each customer at the right time. Lucas: Exactly. And that's the core lesson from Hilton. Pricing is not a single number. It's a system of decisions, each informed by data, each targeted at a specific segment, and all designed to answer one question: how do we get the most value from a room that expires at midnight? Luna: And that's a question every business with perishable inventory should be asking.