The promise of Data Science for the Hospitality industry
Today, the Hospitality industry has access to more data than ever, and especially new unstructured data from the Web. Insights and opportunities offered by these new sets of data can be used by all divisions of major hotel groups to increase brand value, customer experience or profit, and make optimal investments.
From the Real Estate side: knowing where to invest
One of the very first problematic of every hotel group concerns the Real Estate division. How can they get relevant and timely insights that will help them determine where and when to invest for the construction or the acquisition of new hotels? New players with expertise in Data Science and Data extraction are now able to provide precise analytics in real-time – from the Macro and Micro point of view – that can be used to estimate the long-term profitability of a hotel, relative to a specific location
QuantCube Technology is one of these players. By crossing in real-time multiple sources of information, such as air traffic data, hotels prices, conferences occupancy rates, social media comments, consumer reviews of stores and restaurants…, we have developed a series of predictive Macro indicators that can help hotel groups anticipate the future activity of a country, region or city.
From the micro point of view, the monitoring of building constructions and infrastructures through Satellite Imagery Analytics, as well as the monitoring of prices and activity of the local Real Estate market through the extraction of listings from specialized websites, are also indicators that can be fully used to provide to complete the analysis and make the optimal investment decision to build or acquire new hotels.
Increasing Brand Value and Customer Experience with Natural Language Processing
Nowadays, almost every hotel started to pay attention to its e-reputation by monitoring comments and consumer reviews posted by guests on social media, OTA websites… The objective is straightforward: to improve brand value and customer experience through customer feedbacks. However, this process often appears to be a daunting task, as the amount of textual data available on the web keeps increasing every day. Handling these data manually to get exhaustive and up-to-date feedbacks on customer satisfaction takes a lot of time and energy.
With the development over the past few years of a new field of Artificial Intelligence – Natural Language Processing – used to derive meaning from human language input, it is now possible to perform automatically real-time analytics on thousand or million comments to get actionable insights on past and current customers. Various algorithms have been developed in the field of Natural Language Processing, and the precision of Analytics directly depends on the type of model that has been implemented.
Profile Analytics: the future of Data Science
The algorithms of tomorrow are not only focusing on comments but also on the profile of consumers. Through in-depth profile Analytics and the use of external data, building graphs and modeling interests and expectations of customers based on the same sources of information than the ones used for NLP algorithms, the most advanced Artificial Intelligence systems are now able to realize a precise and thorough segmentation of population. Clusters of users sharing the same characteristics that result from these algorithms allow hotel groups to design the perfect packages and adapt their offer extremely fast to increase customer satisfaction and therefore, profit.