By Edwin Chen
I love marketplaces and marketplace data, so a couple months ago I grabbed some Airbnb data and made a slide deck. A few people have asked me about it, so here it is along with a short summary.
My goal was to gather data around potential product strategy, focusing on the following questions.
- You can’t book a great place if you can’t find one. How good is Airbnb’s search ranking algorithm? What are its problems (are listings returned on the high end of the price filters? are too many poorly reviewed listings being shown?), and how can we fix them?
- A big chunk of Amazon purchases comes from its related book algorithms. How well does Airbnb’s Similar Listings model perform? Does it showcase great related properties, or are its suggestions generally irrelevant?
- Airbnb probably wants (and needs) to evolve. Where do users find the booking experience difficult and confusing, and what kinds of new products would improve it?
- Different people use Airbnb differently. What are the archetypical patterns of travel, and is it worth improving their experience in different ways?
- Hotels are Airbnb’s major competitor. When do users still prefer staying in a hotel and why?
I’ll give an overview of what I found below, and check the slide deck for more detail.
Let’s start with Airbnb’s Search. In order to understand the problems and benefits of their algorithm, I asked 100 Airbnb users (from a digital labor platform of my own that I created) to think about a trip they wanted to take in the next year, to search for a place to stay on Airbnb, and to rank the quality of the results.
For example, here’s one Airbnb user who described a trip she wanted to take with her husband and kids to Disneyland:
“We love going to Disneyland and would like to go back sometime this year …read more
Source:: r-bloggers.com