Hotel Dynamic Pricing Solutions Development: Trends, Features, and Pitfalls

https://acropolium.com/img/articles/hotel-dynamic-pricing-solutions-development/img01.jpg

The concept of dynamic pricing—continuously adjusting prices based on demand and supply—has been around for a while. There’s no doubt that as a hotel owner, you raise rates for your properties during the high season and lower them during the quieter months. Meanwhile, smart technologies have taken this process to the next level.

According to Olexii Glib, co-founder of Acropolium, many companies keep their price optimization solutions a secret. This isn’t surprising: a truly sophisticated dynamic pricing system will allow you to react to any shifts in demand and supply in real-time, giving you a clear competitive edge.

In this article, we’ll talk about dynamic pricing software in the context of the hotel industry. You’ll learn about the benefits of using such software in your hotel business, the main trends, key features, hotel dynamic pricing system development tricks, and how Acropolium can help you build a reliable solution for your business needs.

Why do you need dynamic pricing software?

With high-end dynamic pricing software in place, today’s business owners can base their pricing decisions on an extensive variety of factors, from the weather to the buying patterns of a particular customer. This allows them to adjust prices as frequently as the variables change. On top of that, there are solutions with customer segmentation capabilities that show different customers different prices based on their buying threshold.

In terms of the hotel business, this translates into the following benefits:

• You can attract different customer segments.
• By changing prices dynamically, you can increase the number of bookings during the low season, as well as quiet days and even hours.
• You constantly stay current with the market and competition without doing any additional research.
• Your prices will be adjusted based on factors you might overlook (like a concert nearby). Besides, artificial intelligence tools can calculate cross-dependencies of huge volumes of data and come to pricing decisions no revenue manager would even think about.
• You can reduce your revenue management team without compromising your profit with dynamic pricing software that calculates everything automatically.

Long story short, a sophisticated solution will allow you to sell the right rooms to the right people at the right time, giving you no chance to leave money on the table. No wonder that even before the pandemic, in 2019, 25% of e-commerce businesses were already using dynamic pricing tools.

Are you ready to develop your own dynamic pricing solution? Then we recommend thinking of its functions and requirements beforehand.

And what better way to do that than by looking at the hottest trends in the industry?

Three main hotel revenue management market trends

The travel and hospitality industry is going through a difficult time, which is largely unprecedented. While some hotels are filing for bankruptcy, others are going the extra mile with revenue management strategies. This has given rise to the following dynamic pricing software trends.

Short-term data

Before 2020, hoteliers would set prices based on 365-day forecasts and historical data from previous years. However, this strategy doesn’t work today. The constantly changing travel restrictions have affected booking patterns. According to our clients that operate in the hospitality industry, today’s travelers tend to reserve rooms with very short lead times and can cancel anytime.

As a result, demand and supply data are becoming obsolete too quickly, making reliance on short-term data the new norm. This means that the best option is to rely on the data from last week and make 90-day forecasts that should be updated in real-time.

Machine learning

Most dynamic pricing systems run on rule-based algorithms that consist of a number of if/then rules stemming from various factors that might influence the price. The problem is that such systems can work with a limited number of factors, making pricing decisions far from reality. Given that hotel business owners are extremely dependent on pricing due to the crisis, they need much more reliable solutions.

That’s where machine learning (ML) technologies kick in. ML algorithms can process enormous quantities of data, including unstructured data (from hotel chatbots or customer reviews, for example), which is much more than a typical rule-based system can handle. Besides, ML-driven systems in hospitality can learn from the effects every change in rates makes on sales, meaning that every next price suggestion is more accurate than the previous one.

Automation

For many businesses, headcount cuts are the primary means to survive in the post-pandemic crisis. According to the Society for Human Resource Management, 15% of U.S. employers have cut their staff with no intent to rehire, while 38% have decreased employee hours.

Meanwhile, a typical hotel makes five million pricing decisions every year, an impossible task for a business with limited human resources. That’s why it’s critical to automate as many repetitive processes as possible, from the generation of prices to updating them in real-time on all distribution channels. This will allow hoteliers to make the right pricing decisions at the right time and spend more time with their guests while providing a better customer experience.

Key hotel dynamic pricing system features

If you look at the hotel revenue management market, you’ll notice that most smart pricing tools share a common set of features, such as price suggestions, various levels of control, reports, and integrations. So, if you really want to develop hotel dynamic pricing software that will improve your bottom line, be sure that it has these basic functions and that they perform optimally.

Price suggestions

This feature is the main reason why e-commerce business owners decide on purchasing or building a hotel dynamic pricing system. Here’s how it works:

1. Data processing. Every day, the system collects and analyzes numerous external and internal data points (seasonality, local events, flight demand, the hotel’s reputation and its prices, the number of days left to book, the number of vacant rooms, your historical data, etc.). Some solutions might also rely on customer behavior analysis and device data to make personalized pricing suggestions.
2. Best rate forecasting. Based on the cross-dependencies between these data points, the system detects the most profitable pricing options for a set number of days. Most solutions allow users to see how each price was calculated, taking the guesswork out of the process. For example, you can see that the rate is higher because of seasonality or a special event in your hotel restaurant.
3. Updates. Since it’s dynamic pricing, all suggestions update regularly, for example, once in 24 hours. There are also tools that sync with changes in data cross-dependencies in real-time.

Various levels of control

You may choose to set base, minimum, and maximum rates, as well as minimum and maximum stay rules. If you disagree with recommendations, you can adjust prices for individual days, weeks, or months manually. For example, you may consider raising your rates because you are offering a special dinner service or hosting a business conference.

Alternatively, you can fully rely on the system by letting it suggest prices without any input. On top of that, you can configure your smart assistant to update prices on all channels automatically as rate suggestions change instead of doing it manually.

Analytics and performance reports

Even the most basic smart pricing tool can analyze your past performance, giving you insights on your overall hotel business “health,” occupancy rates, booking patterns, lead times, the average length of stay, the most popular offerings, and more. Similarly, some solutions have a revenue performance forecasting feature that makes predictions on future performance, for example, in the next 30 or 90 days.

With this information, you can see whether you are on the right track in terms of pricing. For example, if your hotel performs well, it’s probably underpriced, and you could consider raising your rates. Alternatively, if KPIs don’t live up to your expectations, your prices may be too high.

Integrations

If you own a hotel, chances are you list your rooms on various online booking platforms, such as Airbnb, Expedia Group, Booking.com, etc. Changing prices on each of them every day or a few times a day manually would be a mess, especially if you have dozens of offerings on multiple platforms.

That’s why a robust smart pricing solution that easily integrates with all your channels to synchronize price updates will save you from this unnecessary effort. Plus, it should integrate with other tools you’re using for daily operations, such as inventory or overbooking management systems.

Read also: How to build a custom hotel management software.

So, how to develop hotel dynamic pricing software?

To build a custom hotel dynamic pricing system, you’ll need a business analyst, data science experts (if your solution is set to run on ML algorithms), a UI/UX designer, back-end and front-end developers for the web version, QA experts, and a project manager.

No matter which software development approach your team chooses, the process should contain the following phases:

1. Discovery. Why do I need a custom solution? What features would help me to improve my pricing workflow? Which data do I need to improve my pricing decisions? Are there ready-made solutions on the market I can use instead? These are just a few of a variety of questions you (with the assistance of your business analyst and technical experts) should answer at this stage.
2. Ideation. As your business goals and the initial requirements are discussed, your team will brainstorm on possible ways to address your pricing needs and, finally, decide on the best possible solution. After that, the UI/UX designer will make a hotel dynamic pricing system prototype to help you define how your solution will look and work.
3. Implementation. When you accept the design prototype and technical specifications of your future product, the implementation phase begins. If you’re building an ML-driven system, the process will also involve training algorithmic models, not just coding.
4. Testing and integration. If you’re building a complex system with multiple modules, we recommend implementing them one by one. This means your team implements, tests, and integrates the first module (not the entire system), then proceeds with the second one, and so on. When all the components are ready, your QA experts will test the entire system.

Depending on the size of your business, the complexity of the solution you’re planning to build, and the expertise level of your tech resources, the development will take from weeks to several months. Still, you can test the waters with a minimum viable product (MVP), the most basic version of your solution.

Why is it challenging to build a dynamic pricing system from scratch?

Using a custom hotel dynamic pricing solution means that none of your competitors have the exact same system. However, if you’re looking to develop one on your own, be prepared for challenges. Here are some of the most persistent ones.

Read also: Complete guide on hotel property management software development.

Difficulties related to data collection, selection, and processing

One of the main advantages of dynamic pricing is that it’s based on a huge amount of data, enabling you to make informed decisions around prices. Ironically, such reliance on data poses a challenge to hoteliers looking to build hotel dynamic pricing software on their own.

The main problem is that your pricing system performance will largely depend on the quantity and the quality of your data. This especially applies to ML-based solutions that crunch gazillions of information. That’s why, when building such systems, it’s critical to make sure you feed your algorithms with error-free, complete, consistent, and correct data and that its volume will suffice for your pricing strategies.

So, before proceeding with the development process, be sure to answer the following questions:

• Which data is most suitable in your case?
• How are you going to collect this data? For example, for weather data collection, you might consider integrating a dedicated API. Meanwhile, to monitor your competitors, you’ll need web crawler software.
• Managing large amounts of data in different formats and from different sources is challenging. So, how will you prepare your data?
• How exactly will you feed your ML algorithm with data? Be sure to establish procedures for data input so nothing is overlooked by your system.

Cybersecurity

Another “side effect” of collecting large volumes of data is that it makes you more vulnerable to cyberattacks. Sadly, the more data you have and the more it helps you win the competitive edge, the more hackers will want to steal your data.

So, be prepared to protect your system from ransomware, phishing, and distributed denial-of-service (DDoS) attacks. As cyberattacks become increasingly more sophisticated, you should take care of your system’s security throughout the entire lifecycle of your solution with continuous testing and updates.

Besides, hackers are not the only threat to your data. There’s also the risk of losing data due to human error or hardware disruption. That’s why it’s also important to be vigilant about data backup.

Usability

If you look at customer reviews of some of the most popular off-the-shelf dynamic pricing solutions, you’ll notice that usability is one of the biggest concerns. Even if your solution relies on rich and quality data, runs on best-performing algorithms, and offers tons of useful features, you won’t be able to capitalize on it fully without a clear understanding of how to use it properly.

No doubt, what your system can do is crucial. However, it’s also important to make sure it’s easy to understand. This way, you’ll reduce the learning curve in your organization while making truly data-driven pricing decisions.

What’s next?

Custom dynamic pricing systems have proven to be effective at helping hoteliers make the right pricing decisions at the right time while anticipating market demands. Still, the fact that you’re using a system like this doesn’t guarantee it actually improves your bottom line. To get the most out of the best dynamic pricing practices, you’ll need to have relevant expertise in place. Since hiring developers in-house can be time-consuming and, in most cases, cost-prohibitive, the best way to go is to outsource hotel dynamic pricing software development to a company that specializes in building HoReCa IT solutions. Acropolium is an ideal option in this respect. In addition to the profound tech expertise needed to build a truly sophisticated system, we also have extensive experience delivering products for large hotel chains, which allows us to know the ins and outs of the hospitality industry. So, whether you’re interested in learning more about the topic or want to develop a dynamic pricing system for hotels, don’t hesitate to get in touch with us. Read also about hotel app development.