Machine Learning Based Solution for a Leading Hotel Owner

About the Customer

Industry: Hospitality

The client is a leading hotel owner based in India, registered with multiple online hotel booking service providers’ platforms.

The client needs to determine the optimal rent based on the dynamics of the multiple accommodation booking platforms. The client requires understanding the competitor analysis and different trends in the market based on varied criteria like a number of rooms, beds, bedrooms, washrooms, etc.

Key Challenges

The client is facing the following challenges while deciding the per day rent for online hotel booking service providers’ platform

Hitting the right price for the would-be renters
Balancing between the price not being too low to face lesser revenue or being too high to lose out on potential clients
Judging the possible rate for rooms depending upon the dynamism of the market

They wanted a software solution that could help them to decide per day hotel room rental prices so that it could attract renters and bring more revenue too.

Our Solution

Diagnosing the challenges of the client, SPEC INDIA helped the customer by designing and developing a machine learning model that decides the rental price to be put online for bookings.

We built the solution to automate their process of getting the best possible rent for rooms, from amongst all those listed, using a technique called ‘k-nearest neighbors (KNN) algorithm’.

Process flow of solution is as under:

Find a few listings that are similar
Average the listed price for all those who provide similar services
Set the listing price to this calculated average price

A variety of graphical representations are available depending upon different criteria like accommodates, bedrooms, beds, bathrooms, etc. These visuals offer a great deal of clarity in taking the right decisions.

Following are the supporting variables that play a role in decision making: