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Airbnb Booking Rate Prediction with XGBoost

1. Executive Summary

The major part of our analysis focused on identifying the factors which can help investors achieve a high booking rate. Prediction was an integral part of our study. Accurate prediction would help an investor in focusing on properties that could give him a competitive edge. Our approach focused on looking at the data through a customer’s eyes. We tried to include in our model all variables that a customer might deem important in choosing an Airbnb. We were able to decipher some interesting facts from our results.

Location does not play a significant role in getting a high booking rate. So for any existing property owner in DC, listing it as Airbnb would get more revenue, than renting the property to a tenant. And diversifying the investment is a good strategy to make sure your portfolio is profitable. Achieving Superhost Status will significantly increase your chances of high booking rate. While Airbnb has its own criteria for that status, things of utmost importance are catering and matching the user requirements, and maintaining a good image. Having a good response time, honouring all bookings made and great reviews will get you closer to superhost status and bring your listing to the top.

We have tried at every point to make sure that all our findings can be explained and it is not just a black box prediction methodology. This helped us in building a strong business case with clearly explained variables and results. Still, the degree of reliance on the model would depend on what the business requirements are. Combining human judgement and the insights from the model for decision making would be an optimal solution.

2. Research Questions

  1. What factors affected the booking rates of an Airbnb listing? i) What kind of Airbnb - rooms, facilities, number of beds and bathrooms - have a higher booking rate? ii) Do Airbnb hosts with multiple listings achieve better booking rates? iii) What kind of services and facilities affect the booking rate of Airbnb?

  2. What are the relevant statistics about the DC short term rental market? i) Is there any clustering in type of airbnb in areas? ii) Which areas have higher booking rates? iii) What kind of people visit dc, and what is their purpose? iv) What type of housing they might be looking for? In what price range? v) Generally what is the trip duration/stay in dc?

We focussed mainly on the above two questions because our goal is to provide the investor with recommendations backed up with evidence. If we have knowledge about the factors which affect the booking rates of an Airbnb listing, then the investor would have a fair amount of idea about the amenities that hold most importance, type of properties to invest in, the areas which are more profitable than others. Secondly, understanding specifics about the Washington DC market will help in making right decisions while investing in DC. Some factors which are profitable in one market might not be of any significance in another market.

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Airbnb booking rate prediction using XGBoost

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