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Airbnb’s Marketing Strategy with Data

Watch Raj Venkatesan explain the mental model behind Airbnb's strategy and the data necessary to test it.
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Let’s revisit the strategic challenge of Airbnb. Airbnb wants to improve the rental prospects for hosts and identify better rental options for guests and they want to use the user generated data, the reviews that are available on the website and price of the property as levels that they can use to improve their rental prospects for hosts and guests. Now, let me tell you that we’re going to look at data and analytics and how to improve the marketing planning process. So I have to warn you this is going to be some hard work and some math and it is going to be like eating vegetables and we are going to do this. I am here with you.
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We’re going to get through this. I’m sure you can do this. Let’s get started. So the first step in this analytics process is to construct something called a mental model. So we’re going to work through developing this mental model for Airbnb and it starts by identifying the metric that Airbnb is trying to maximize and that metric is profit per property. Now profit per property is obtained by multiplying gross margin. What is a margin that Airbnb makes from each property that gets rented? And the price that the property is charged, the number of rentals that the property gets rented, and the minimum stay or the minimum duration that the property gets rented for each time it gets rented.
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So the product of all these; price, number of rentals, minimum stay and gross margin gives you profit per property. Now of all of these aspects what is the one thing that the customer influences? The customer influences number of rentals. Now how does the customer decide which property to rent? Now that could be based on the star ratings, whether it is two stars or three stars or five stars. It could be based on reading the text like we saw in the Fred’s apartment we surveyed the reviews and we saw what people talked about their experience renting from Fred’s apartment and also the properties. What kind of apartment is this? How many bedrooms? What location?
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All of these determine whether the customer rents an apartment or a home from Airbnb and that eventually determines the number of renters of the property. So here you are. This is the mental model that we are working with for Airbnb. Now what kind of data is necessary to build this mental model? The first place we look at is the reviews because that’s what we see as say, one of our hypothesis is that customers read these reviews and then make up their mind as to whether they should rent this place or not. And here are all the reviews that we had for Fred and his apartment.
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Now what we are going to try to do is look at all this information and take that and build it into a predictive model that will tell us how many renters are possible based on the star rating, the reviews and the property attributes and that’s what we are going to see in the next video.

Airbnb hypothesizes several factors that affect its ability to maximize the profit it earns on each property listing and uses a lot of data to create a predictive model that will allow it to tweak each factor.

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