Why big data presents big opportunities for Indonesian Hoteliers

Hotelier Indonesia



Why big data presents big opportunities for Indonesian Hoteliers
Written by: Rachel Grier, Area Managing Director Asia Pacific for IDeaS

The Indonesian hotel sector has long recognised that good pricing decisions start with good information. Today hotels from Bali to Jakarta and beyond are beginning to turn to big data and analytics to gain insights into the vast amounts of guest data they have at hand, and utilising these insights to develop strategies that attract and retain valuable guests, ultimately driving better revenues and profit.

Not all data is good dataThe data sources that support hotel pricing decisions commonly include stay history, inventory history, future reservations, future inventory, competitor pricing and future rate information. However, whilst it was once assumed that more data leads to more informed decision-making, the focus is now on ensuring the right data is collected in the first place.

But what type of data is considered quality data for a hotel? In many cases, much of the “big data” that will help a hotel make more informed pricing decisions is demand associated data; that is, data that is used in the creation and curation of accurate demand forecasts.

Optimising decision making with advanced analytics

It goes without saying that in the age of big data, advanced analytics and real time visualisation of clean data critical. Any Indonesian hotelier working without the support of an analytical revenue management system will find themselves overwhelmed by the sheer volume of information and complexity of the data.

Forward-looking predictive analytics, embedded in today's advanced revenue management systems, help hoteliers uncover emerging trends and identify opportunities to capture more revenue.

Advanced hotel revenue management analytics use data mining, machine learning and a variable deployment of complex predictive algorithm sets to calculate optimal pricing and inventory decisions for hotels.

Analytics assist hoteliers to move beyond their normal revenue management processes into harnessing their data and forecasting capabilities to explore, predict and optimise total revenue performance.

Best in class revenue management system analytics enable hoteliers to uncover granular patterns and trends at a micro-level. By determining why specific results are emerging, and if a hotel can expect them to continue, hoteliers can optimise their revenue opportunities.

What guests say about you online matters

As the hotel industry and revenue management has changed over the years, so has the relationship between a hotel and its guests. Thirty years ago the guest relationship with a hotel was direct, personal and on a one-to-one basis.

Today, according to Scott Cook, Founder of Intuit, “A brand is no longer what we tell the consumer it is – it is what consumers tell each other it is.”

This change in the control of brand value is a critical to hoteliers across the region. Reputation management companies enable the capture, measurement and management of consumer sentiment and these can be utilised by revenue management systems to assess value perception in relation to both you and your competitor brands at any given time.

In this context, social media and reputation information becomes essential as it forms a basis of value perception in regards to price sensitivity and thus demand as a subsequent function of price.

Revenue managers incorporate value perception data points, competitor set reputation and value weighting when developing pricing strategies and executing marketing campaigns, since value perception directly impacts a hotel’s ability to capture guests.

Increasing profit and loyalty from guest intelligenceToday's digital environment has created more competition for a hotel’s consumer business than ever before. This competition is no longer just about competing with the big global brands; hotels are now competing with third-party distributors and disruptors from the sharing economy, such as Airbnb. Hotels do, however, have one distinct advantage: they can engage with guests, collect data about them and provide a customised experience that third-party distribution partners cannot.

To create a holistic view of a hotel's guests, and to offer opportunities for personalising a guest's stay, predictive modelling must also be applied to the consumer demographic and behavioural data that is gathered from all hotel interactions.

This approach allows hotels to improve their segmentation and group similarly behaved customers together so they can more effectively target messaging and stay experiences to them.

With predictive modelling, a hotel can also better calculate a guest's likely lifetime value, understand how to nurture and grow the value of their most valuable guests, and determine where to source more of those high lifetime value guests in the future.

It can help predict the next-best-offer for each guest to maximise their likelihood of responding, or even encourage them to purchase additional products or services during the purchase or stay process.

Without today's predictive modelling, marketing efforts are based on generic business rules that face limitations in influencing behaviour.

Big data drives the business

Data is central to nearly every operational decision a hotel makes today. Those savvy hoteliers that embrace the benefits that quality data and advanced analytics can bring to their property will be able to better attract the right guest, at the right time, for the right price, via the right channel and position themselves for success in a competitive market.