- April 18, 2018
- Posted by: Karanbir Singh
- Category: Machine Learning
“We are going to completely change what it means to do advanced analytics with our data solutions. We have machine-learning stuff that is about really bringing advanced analytics and statistical machine learning into data-science departments everywhere.” – Satya Nadella
“Google. The ultimate search engine that would understand everything on the web. It would understand exactly what you wanted, and it would give you the right thing. We’re nowhere near doing that now. However, we can get incrementally closer to that, and that is basically what we work on.” —Larry Page
Machine Learning, Deep learning, Artificial intelligence, and related technologies have definitely been the front runners as far as technological revolution is concerned. Every Tech giant has acknowledged the power of these technologies and the potential to impact the human race in a huge way.
Now, let us understand what these terms mean.
What is Machine Learning?
Simply put, Machine Learning refers to machines capable of evolving and improving by themselves by “Learning.” Here, machines can “Learn” to be better. Artificial Intelligence and related fields help to evolve Machine Learning which can then take machines beyond their cliched role of programmable equipment and give them the capability to think for themselves. They can recognize patterns, build skills, and knowledge to make themselves better, and do most of the currently programmed work on their own. This process eliminates the need for constant human supervision and improves efficiency.
What is Deep Learning?
This method is related to learning that allows a system to find out the means to make raw data organized. It is much more Data Analysis than conventional Machine Learning involving job specific algorithms, even though it belongs to the same family as machine learning. There are two types of Deep Learning, Supervised and Unsupervised.
Both Machine Learning and Deep Learning are futuristic fields of technology that have untapped potential. They have applications in many disciplines, mainly Artificial Intelligence, Data Analysis, and Automation.
Let’s understand their application in the Hospitality industry.
The Hospitality Industry-At A Glance
The Hospitality industry is a humungous service based industry which includes tourism, event planning, transport, lodging, and similar services. In the broad sense, it can be considered as any product or service related to hosting. It is a complex ecosystem in which billions of dollars change hands every day. So, just like every other multibillion-dollar industry, it is dependant on technology for its day to day operations. In such a vast sector, there is a constant need for fresh and innovative technology to make business processes more efficient and increase profitability.
Applications of Machine and Deep Learning In The Hospitality Industry
Hospitality sector needs popular demand for its survival. It is an industry that caters to the wants of the customers more than their needs. Hence, competing firms in this sector employ methods and machines to ensure that they can deliver better service at a lesser price to their clientele. The application of ML and DL can improve some of these strategies.
Predicting Seasonal Demands for Services
The Hospitality industry has certain ‘seasons’ in which some of their services are at a higher demand than others. These seasons may or may not be linked to actual climatic seasons. Whatever be the case, these are the times when service providers can make the most money, and they want to capitalize on this opportunity.
Deep learning can be applied to do this job. A computer can easily find the correlation between factors that cause this seasonal demand by analyzing raw data from the past and predicting the future trend accurately. This process is called Predictive Analysis where patterns of the past are used to predict events of the future.
Hospitality Service Providers use competitive pricing as one of their most significant strategies to attract customers. Companies try to provide services at the best price without compromising their profits to attract maximum customers. Here, Machine Learning can be helpful.
Based on seasonality, hotel history, local events, local competition, 3rd party promotions, and external real-time events, the data can be run through predictive models and analyzed which can then be used to give the best possible pricing for any service and provide companies an edge in the market.
Recommendation engines are being used by prominent tourism sites like TripAdvisor and Expedia since a decade to provide users with the best tour packages. Here, the engines collect data specific to the budget, preferences, and details of a customer to give him personalized recommendations for trips. Information acquired from various sources and service providers is used to come up with suitable alternatives by comparing options using a Deep Learning program.
Custom Services and Customer Satisfaction
People who use Hospitality Services come from a variety of backgrounds, and their demands and expectations may vary. Catering to them so that every customer is satisfied is the measure of success for any company in this sector. All customers want to be treated according to their preferences, and to ensure this, a process called Market segmentation is employed in every industry which caters to a broad audience. In the Hospitality industry also, this process is very efficient.
Here, the whole customer spectrum is divided into segments which have similar characteristics and more or less the same demands and expectations. This makes service much more personalized and specialized.
Using Machine Learning, the classification becomes more diverse into smaller and smaller groups. This may include subgroups that are unseen before, and the quality of service improves as it becomes much more tailored for individual customers. This process leads to happier customers, and in turn a better, and more profitable business.
These are a few places where machine learning and deep learning is currently used in the industry. There is a multitude of futuristic applications which can revolutionize the industry.
Robotics, for example, can lead to automation of almost all processes, and make everything infinitely faster.
Deep Learning and Machine Learning are leading the way for innovation in all fields. They continue to be explored and applied in new sectors every day. It is a promising field with substantial untapped potential, and the capability to change the face of the industry.