Why data quality is key for successful dynamic pricing decisions

With the proliferation of commercial strategy and market intelligence tools, AI-powered capabilities and dynamic pricing platforms, even small independent chains (and even individual hotels) are increasingly able to compete with larger, more established competitors. 

Dynamic pricing platforms specifically have been one of the largest factors contributing to smaller players being able to gain a competitive edge.

In the past, dynamic pricing was only accessible by the largest groups and chains with multi-million dollar budgets, an ability to enforce and monitor adoption amongst franchise partners, and elaborate agreements with tech vendors.

Fast forward to the present day, where an independent hotelier can sign up for a dynamic pricing tool in the morning, and be up-and-running by the afternoon. 

The benefits of dynamic pricing are numerous. When a hotelier makes the switch from an older, outdated pricing model (such as static pricing), they will notice a few key changes:

• Fewer missed revenue opportunities during peak times thanks to 24/7 decisions making and observation of market conditions, leading to better ADR outcomes

• More time for hoteliers to focus on creating a better guest experience by not having to fret over last-minute pricing changes

• Increased occupancy levels in low-demand and off-peak periods, leading to better predictability in budgeting and forecasting and higher RevPAR

So with so many benefits, what is the catch with dynamic pricing? Even though the playing field has become more level, and the tools better than ever, there is still a big consideration when it comes to dynamic pricing solutions: No matter how sophisticated the tool, it won’t unlock optimal pricing outcomes if the underlying data that powers the decision engine is low quality.

There is an old cliche quote you’ll often hear in the industry especially any time automated forecasts, algorithms, or pricing recommendations are in question:

“Garbage in, garbage out”.

Pithy? Certainly. But is it true? In this blog let’s explore what makes for high-quality data, and how it leads to better outcomes for a dynamic pricing system.

Dynamic pricing strategies are becoming a hospitality industry standard

First, let’s first explore the concept of dynamic pricing and why it has taken over the world of hotel revenue management. Dynamic pricing allows hotels to constantly monitor and scan external market conditions (hotel pricing, demand data, booking patterns, etc.) and internal data (pickup, occupancy, segmentation trends, etc.) to recommend an optimal price in real-time.

Adopting a dynamic pricing strategy is no longer a “nice to have”, but rather is becoming essential to remain competitive.

Dynamic pricing solutions are no longer just for the major chains with big budgets and complicated tech-stacks. In fact, the hotels most at risk of falling behind are small chains, and independent properties that are still utilizing a static pricing strategy, without understanding the pitfalls

If you’re curious whether or not your property is lagging behind those using a dynamic pricing strategy, you can use our free pricing audit tool to see whether you may have opportunities.

Hoteliers need real-time data insights to stay competitive

One of the most important determinants of data quality is timeliness. Ten or fifteen years ago, it wasn’t uncommon to rely on an OTA or GDS rate shop that was updated perhaps once per day, early in the morning. For revenue managers and commercial strategists analyzing market trends and making pricing decisions in a late-afternoon strategy meeting, this means that their market intelligence was already 8 or more hours old.

Now, a revenue manager (and by extension their dynamic pricing system) is analyzing not only pricing, but also ranking across various channels, flight and search demand, competitor rate evolution, and much more. This data must be pulled on-demand, and be analyzed in-the-moment to be relevant. 

Stay on top of competitor pricing

Competitor pricing remains one of the key data points that a dynamic pricing system ingests and utilizes to generate a pricing recommendation. But when is this data high-quality? Competitor pricing data is at its absolute best when it is: freshly updated, well categorized, and collected from relevant competitors.

Freshly updated

In 2024, we at Lighthouse conducted an industry survey confirming that data within our industry is becoming ever-more complex; in the survey we demonstrate that fluctuations in rate have increased 20% worldwide since 2019. This is for a combination of reasons, including the adoption of dynamic pricing solutions. This is significant because it means that hoteliers are optimizing room rates more frequently, leading to an overall more competitive pricing environment. 

If your dynamic pricing system isn’t able to ingest real-time, on demand competitor rates - you run the risk of pricing based on stale data. While this may mean missing out on just a few rooms in a day, the impact can be massive when extrapolated over the course of a year. How do you ensure that your dynamic pricing system is indeed getting the most up-to-date rates when making decisions? The answer is to pair with a best-in-class rate provider with on-demand rate shops. 

Well categorized

How many times has this happened to you: A quick OTA search of your competitors toward the end of a busy day reveals an eye-popping rate - $899, from a competitor that is typically priced at $199 - do your eyes deceive you? Have you missed a major opportunity? After several minutes of panic-searching you realize what’s going on: this competitor has sold all of their standard hotel rooms, and is advertising their most premium loft (of which they have one available room!).

Just like a person, a dynamic pricing solution benefits from context. This is why tools like Pricing Manager and Rate Insight allow the user to categorize competitor room types and compare them to like groupings for your own hotel. In this way, the system will not simply play follow-the-leader, but instead will suggest a rate for each category of room based on how the compset is their similar room categories that you’ve identified as a good analogue.

From relevant competitors

Every hotel monitors a handful of other, similar hotels in their market to gain intelligence and insight. Most commonly, a compset provides valuable pricing queues; to illustrate: if a hotel across the street is pushing rate heavily for July, and you have the same amenities, service level, and similar review scores, it’s important to pay attention and adjust your strategy accordingly.

A dynamic pricing solution, when calibrated correctly, will perform similar analysis.

In fact, dynamic pricing solutions look at even more complicated factors, such as pricing adjustment frequency, demand fluctuations, and other aspects that influence pricing which are more subtle and harder to analyze frequently as a human.

Having a well-selected compset makes a huge positive impact on any dynamic pricing solutions.

But what makes a relevant compset?

There are many factors, but competitor hotels that should be included in your compset and monitored by your dynamic pricing solution are those that:

• are of a somewhat similar size (room count)

• a similar service level (don’t compare a 2-star hostel to a 5-star luxury hotel)

• have similar amenities, and should be geographically relevant. 
  

Features like Benchmark Insight’s Smart Compset can suggest a tailored competitive set automatically based on dozens of factors, and when the dynamic compset is accepted, tools like Lighthouse’s Pricing Manager can be further adjusted using competitor weights to further fine-tune automated pricing suggestions.

Monitor travel trends in your market

Trends such as seasonality give rough guide-rails for a dynamic pricing system to operate within. Having multiple years of accurate and reliable historical occupancy rates, pickup, and demand data allows your dynamic pricing system to predict when it can capitalize on rate in the high season, and push for occupancy in the low season.

One common weak link that hotels often experience is low-quality PMS data. Historical PMS data is highest quality when it is free of things like dummy reservations and ‘manager holds’, unnecessary out of service rooms, rate overrides, and comp rooms.

Future-looking data is just as important, market-demand data can indicate whether future dates will be stronger or softer than historical averages.

Keep up with event announcements

Imagine: it’s peak season, and a major event announcement happens late on a Saturday night when your revenue manager isn’t in the office and the bookings start pouring in?

Maybe you’re just miles from a venue where a new music festival is scheduled to happen?

Or maybe your local team has just made the playoffs for the first time in 15 years and demand is through the roof as your hotel is walking distance to the stadium?

These are some classic nightmare scenarios, but imagine all of the many smaller local events that crop up throughout the year; there is a strong chance you aren’t responding to each event in the fastest, most optimal way every time. 

Event data also depends on quality. Having real-time access to event announcements and estimated attendance - especially when combined with data from similar past events and search trends - can help a dynamic pricing system quickly react to major announcements and protect your hotel’s inventory

Dynamic pricing software is essential for independent hotels

Data can only take you so far, especially if you don’t know how to use it, or can’t put the insights into practice. You may already be putting in the effort and hard work to ensure that your data is accurate and timely, but find yourself falling prey to ‘data-overload’ and don’t have the bandwidth to utilize the data you’ve worked so hard to compile.

If this sounds like an issue you’ve experienced before, that is exactly where dynamic pricing solutions save the day.

Lighthouse Pricing Manager

Solutions like Lighthouse’s Pricing Manager are able to detect the signal amidst all of the data noise. By looking at relevant market data, hotel performance, and other external factors,  Pricing Manager’s AI enabled decision engine digests the data, generates the best possible recommended rate in real time, and then pushes that rate directly to the property management system.

Pricing Manager stands out among other dynamic pricing tools for a few key reasons- it’s best-in-class real-time price data and unparalleled market demand data, when combined with your own hotel’s data allows for deeper analysis than dynamic pricing engines and rms’s that are only looking at a few basic criteria (such as occupancy and competitor room rates only).

Secondly, PM’s auto-pilot feature allows the user to set pricing rules based on various factors. Set room price caps and ceilings for high-demand periods, or only push rates to the PMS on certain weekdays. The possibilities for customization are near endless.

Optimize pricing and drive profitability with Lighthouse Pricing Manager

The adoption of dynamic pricing solutions continues to grow as more hoteliers are catching on to the benefits of adding automation and AI in their tech stacks.

By partnering with a solution provider known for best-in-class data, you can ensure that you don’t fall into the ‘garbage-in-garbage-out” conundrum, and can always be sure that your strategy solutions are based on the cleanest, highest quality inputs.

If you’ve been curious about whether a dynamic pricing solution is viable for your independent hotel, consider trying a demo of Lighthouse’s Pricing Manager and see if it is a fit for you.

You will likely discover that there are still opportunities to increase revenue for even the most savvy hoteliers, especially when it comes to optimizing pricing decisions in real time.