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How to become a good earner in Airbnb?

A data based approach using Seattle airbnb data in 2016.

Introduction

Airbnb is an online marketplace which lets people to rent their properties, rooms in their house, or share their rooms to the guests. This blog is an effort to interpret the Airbnb, Seattle dataset retrieved from Kaggle and answer few business questions, mentioned below.

The dataset retrieved is a collection of property listings, their key features and types, such as property type, host type, neighborhood, reviews and much more.

  • What time of year has the highest rental prices?
  • What factors have an influence on booking price ?
  • What aspects correlate well to host earnings?

Part I: What time of year has the highest rental prices?

The line chart of Number of listings per month in 2016 depicts a seasonal trend in the change in monthly pricing. The pricing trend looks increasing throughout the months, starting from January, where the largest leap in pricing is identified in July and drops between July and November.

As we can see from line chart Number of listings per month, listing numbers have opposite trending compare with average rental price in 2016. This is because fewer listings cause higher price. July is the most popular time to visit in Seattle and rental prices is the highest.

Part II: What factors have an influence on booking price ?

From below several bar chart, we can see neighbourhood cleansed, property type, bed type and room type have an influence on rental house price. The hosue neighbourhood is Southeast Magnolia have 240$ approximately, Magnolia is the second largest neighborhood of Seattle.

Boat property houses have the highest rental price, twice as much as the second highest price. Travellers must be curious about how boat house looks like

The Real bed have highest rental price, it is no surprising that real bed is the most expensive.

Rental houses which room type is Entire home have 175$ average price, because this room type is the biggest.

From above correlations heatmap, number of accommadates, bathrooms, bedrooms, beds have a high positive correlation with price.

Part III:What aspects correlate well to host earnings?

As we want to make recommendations for the low earner hosts and make their listings more profitable and gain more revenue than before. This part do features comparison between listings that have high earning versus low earning listings based on listing score (in term of number of reviews and rating of reviews).

I subset the entire host listings into two type, top90 and low25. Top90 means host listings which have higher score than 90 percent of listings. Low25 means host listings which have lower score than 25 percent of listings.

As we can see, host is superhost, host response time within an hour, house property type Cabin, cancellation policy moderate, instant bookable have significant more pertantage of top90 listings than low25 listings. Host response rate is almost the same beween two types. Host identity verified of top90 listings is about 20 percent more than low25.

Conclusion

In this article, we took a look at hosting price influences and how top earner become a top earner compare to low earner according to Seattle Airbnb 2016 data.

Suggestion for airbnb hosts

Therefore, to conclude the analysis there are several points that low-performer could do to increase their probability to get more bookings, reviews, and higher number of reviews:

  1. Become a superhost.
  2. Response guest within an hour.
  3. Change hosue property type to Cabin.
  4. Change cancellation policy to moderate level.
  5. Activate the instant bookable feature.
  6. Make your account verified by Airbnb.

To see more technology detail about this analysis, see the link to my Github available here.