This article is another example of how geography can enhance business.

Early versions of our pricing algorithms plotted an expanding circle around a listing, considering similar properties at varying radii from the listing location. This seemed to work well for a while, but we eventually discovered a crucial flaw.

We therefore got a cartographer to map the boundaries of every neighborhood in our top cities all over the world. This information created extremely accurate and relevant geospatial definitions we could use to accurately cluster listings around major geographical and structural features like rivers, highways, and transportation connections.

We improved our algorithms over time until they were able to consider thousands of different factors and understand geographic location on a very detailed level.

I’d be curious to know the workflow process of their cartographer, how manual or automated was that process, and what criteria were used in defining those boundaries.  Whatever the answer, it appears the secret sauce worked for Airbnb.

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