Big Data Can Improve Revenue Management in the Travel Industry

Big data has become a vital asset in many different industries in recent years. With so many people sharing their information online and platforms logging customer behavior, there’s a need for an efficient way to process all that raw information. The travel industry is no different, as owners and managers are constantly discovering new ways to use big data.

It’s not a new concept, but many thought it was a waste of time until they saw others reap the benefits of properly applied big data practices. If you are having doubts about it, you’ve come to the right place. In this post, we will give you a single example of how big data can dramatically improve revenue management for a travel company.

Gathering, managing, and using big data isn’t that difficult as it was in the past. It has become widely available, but it’s up to companies to take advantage of it.

How Big Data is Connected to Revenue Management

Big data is large volumes of data that can be gathered from external or internal sources with consistent or inconsistent structure. Within this data, there is tons of information linked with itself in a complex fashion.

It’s important to enforce accuracy and quality through specialized solutions to manage such complex data. Accuracy is also the core principle of revenue management, and it’s achieved by using quality data.

Big data can improve processes like forecasting, segmentation, and personalization. Revenue management is focused on data regarding performance and analytics, and big data is perfect for predicting consumer behaviors and demand.

The larger amounts of accurate data enable travel companies to make better decisions regarding distribution and pricing to optimize their revenue and ultimately boost profits. Simply put, big data is the tool that allows companies to do better revenue management.

New Insights and More Information

In many cases, business owners and managers within the travel industry get stuck in their comfort zones. They only compare their current performance with their performance in the past, often failing to see the big picture regarding demand, competition, customers, and the overall market.

The valuable information big data gives can help companies ask new questions relevant to their performance and recognize new opportunities for improving revenue. With this new data, companies can look outside of their own demand.

Instead, they look at the overall demand that still might not be related to their performance but can capture opportunities through analysis and adjusting their approach. The main goal should be to understand all the phases of the customer purchasing process and acquisition.

Hotelmize – Big Data & Machine Learning

Big data would be useless if we didn’t have the necessary technology to gather, store, and analyze it properly. Hotelmize is a perfect example of a big data company that provides its services to various travel companies in a streamlined way so that they can instantly start to reap the benefits of big data. (Tools we use: Azure Blob Storage, CouchBase, ElasticSearch)

Hotelmize provides machine learning capabilities that allow companies to gather essential travel data and update their information in real-time. This company has a “Room Mapping System” that can track accommodation down to the tiniest detail according to demand.

OTAs, booking companies, and tour operators can instantly find accommodation that they can offer to their customers while looking for the best prices and profit margins. Hotelmize also offers “Asymmetrical Room Matching” that can find suitable accommodation with all the essential requirements while taking into consideration other amenities.

All of that enables organizations to optimize post-booking revenue while ensuring the customers are satisfied with their services.

Examples of Other Tech Companies Using Big Data to Help Travel Companies

Beyond Pricing

This company offers an automated pricing tool for people using Airbnb as renters. When users connect their accounts with this tool, Beyond Pricing automatically updates their prices on a daily basis. It offers dynamic repricing and enables users to increase their income.

Duetto

With cloud analytics and big data, Duetto allows hotels to adjust their pricing. It’s specifically designed for large chains as it can give them valuable insights into market changes. It’s more than just revenue prediction as it gives actionable information that helps hotels adjust their approach.

UpStay

UpStay, uses powerful algorithms to identify underperforming inventory and provide targeted and personalized upsell offers to help increase hotel revenue and operational efficiency. UpStay quickly generates consistent conversions and revenue from the very first moment it goes live in any hotel.

Conclusion

Most revenue managers are playing the “small game” – they work with a limited set of data and focus on a narrow approach. That’s where big data can help them create and identify new opportunities and ultimately improve their revenue management.