Airbnb is a traveler’s most preferred method to explore a new city and stay in residential spaces. It’s one of the best online homestay networks where you can rent out houses, and it's the closest you can get to live like the locals. Airbnb is a trusted community and is preferred by travelers around the globe. Instead of living out of lifeless pods in exorbitantly priced hotels, tourists now prefer to dwell in homes that are managed by locals. Airbnb helps tourists immerse themselves in the land’s culture.

Airbnb on a world stage

Since the inception, the organization has evolved at a tremendous pace. Airbnb has transformed itself into a huge empire spanning continents. It offers world-class service and assistance to domestic and international tourists. Have you ever wondered how the website suggests locations that suit your preferences and how Airbnb helps suggest the best price ranges and proximity to major attractions like the beach or the venue of the event you are about to attend? The repository of back data and all the data logs are instrumental in predicting the behavior of the clients and provides a clear understanding of the importance of amenities and facilities.

The data science team at Airbnb uses data from the past to predict the probability of a match between the host and the visitor.

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Data is the New Science

To accommodate travelers around the world and to help them find the most preferred properties, Airbnb actively engages in extensive research. How can the organization cater to the diverse needs and preferences of travelers around the world? The answer to this lies in Big Data.

Undoubtedly, data science has a massive role in serving over 80 million guests worldwide and providing impeccable service. Machine learning and big data provide valuable information that helps Airbnb to retain its essence while catering to its clientele at an individual level. An analysis of the back data gives clear suggestive recommendations to upscale the level of service and bridge the gap between what can be beneficial and profitable to the guests and to the organization.

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Here is an interesting video on how Airbnb uses the data to form predictive analysis. 

 

Basically, Airbnb draws the data from the list of preferences selected by the guests. Depending on this, it lists properties through keywords and pricing. The data also determines if the pricing is too high or if any property is underpriced during a major event in the area.

Having said that, the data scientists at Airbnb feel that there are significant factors that affect the business.  Amenities and vital factors influence the rate at which one venue is considered over another.

Riley Newman, one of Airbnb’s core team members, stated that Data Science has helped them design the best model to enable a better match between a host and a guest. Newman said that the team juggles over 11 petabytes of data and considers the hosts’ preferences on the duration of stay and if they want their place to be continually occupied or if they prefer to have breaks between guests.

The research team says that the preferences fall into 4 categories, and these are vital factors that influence a guest to select a venue:

  • Behavioral Aspect: determined by how the user interacts with the Airbnb website.
  • Dimensional Factor: device used, language and location preferred
  • Sentiment: lodging reviews, survey results, and ratings are vital deciding factors
  • Imputed: sorts the location preference of the traveler, for example, city vs. local towns

 Various amenities could also increase the chances of guests picking a place: proximity to attractions, basic amenities like air conditioner in a particularly humid location, the availability of wi-fi, etc. We have seen how data science really helps the organization to pitch the right place to a client based on the clients’ past behavior.

There are several factors here that remind us how important data really is. Airbnb is a perfect example of how Big Data was used to provide the best service to customers. Here is a synopsis of how instrumental raw data was in enabling Airbnb to make a predictive analysis.

We have seen how important back data is to tailor the custom search requests and build a unique customer experience. It plays an instrumental role in helping the customer connect with the company at a personal level. Airbnb focuses on building a memorable, delightful, and unique customer experience, and it has big plans for enhancing its service in the coming days. Here is Airbnb’s vision for the future.

Airbnb looks ahead to the future

Big data has been instrumental in helping Airbnb offer a unique experience where the search engine is designed to suggest places based on the customers’ preferences. Factors like pricing and demographic location are considered while suggesting a place, and this personalizes the entire experience. Keeping the customer at the center of your business is sure to win the hearts of millions. 

Data Science & Business Analytics Courses Duration and Fees

Data Science & Business Analytics programs typically range from a few weeks to several months, with fees varying based on program and institution.

Program NameDurationFees
Professional Certificate Program in Data Engineering

Cohort Starts: 16 Dec, 2024

7 months$ 3,850
Post Graduate Program in Data Analytics

Cohort Starts: 20 Dec, 2024

8 months$ 3,500
Professional Certificate in Data Analytics and Generative AI

Cohort Starts: 20 Dec, 2024

22 weeks$ 4,000
Caltech Post Graduate Program in Data Science

Cohort Starts: 23 Dec, 2024

11 months$ 4,000
Post Graduate Program in Data Science

Cohort Starts: 2 Jan, 2025

11 months$ 3,800
Data Scientist11 months$ 1,449
Data Analyst11 months$ 1,449

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